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COVID-19 Monoclonal Antibody Infusions: A Multidisciplinary Initiative to Operationalize EUA Novel Treatment Options

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COVID-19 Monoclonal Antibody Infusions: A Multidisciplinary Initiative to Operationalize EUA Novel Treatment Options

From Mount Sinai Medical Center, Miami Beach, FL.

Abstract

Objective: To develop and implement a process for administering COVID-19 monoclonal antibody infusions for outpatients with mild or moderate COVID-19 at high risk for hospitalization, using multidisciplinary collaboration, US Food and Drug Administration (FDA) guidance, and infection prevention standards.

Methods: When monoclonal antibody therapy became available for mild or moderate COVID-19 outpatients via Emergency Use Authorization (EUA), our institution sought to provide this therapy option to our patients. We describe the process for planning, implementing, and maintaining a successful program for administering novel therapies based on FDA guidance and infection prevention standards. Key components of our implementation process were multidisciplinary planning involving decision makers and stakeholders; setting realistic goals in the process; team communication; and measuring and reporting quality improvement on a regular basis.

Results: A total of 790 COVID-19 monoclonal antibody infusions were administered from November 20, 2020 to March 5, 2021. Steps to minimize the likelihood of adverse drug reactions were implemented and a low incidence (< 1%) has occurred. There has been no concern from staff regarding infection during the process. Rarely, patients have raised cost-related concerns, typically due to incomplete communication regarding billing prior to the infusion. Patients, families, nursing staff, physicians, pharmacy, and hospital administration have expressed satisfaction with the program.

Conclusion: This process can provide a template for other hospitals or health care delivery facilities to provide novel therapies to patients with mild or moderate COVID-19 in a safe and effective manner.

Keywords: COVID-19; monoclonal antibody; infusion; emergency use authorization.

SARS-CoV-2 and the disease it causes, COVID-19, have transformed from scientific vernacular to common household terms. It began with a cluster of pneumonia cases of unknown etiology in December 2019 in Wuhan, China, with physicians there reporting a novel coronavirus strain (2019-nCoV), now referred to as SARS-CoV-2. Rapid spread of this virus resulted in the World Health Organization (WHO) declaring an international public health emergency. Since this time, the virus has evolved into a worldwide pandemic. COVID-19 has dramatically impacted our society, resulting in more than 2.63 million global deaths as of this writing, of which more than 527,000 deaths have occurred in the United States.1 This novel virus has resulted in a flurry of literature, research, therapies, and collaboration across multiple disciplines in an effort to prevent, treat, and mitigate cases and complications of this disease.

 

 

On November 9, 2020, and November 21, 2020, the US Food and Drug Administration (FDA) issued Emergency Use Authorizations (EUA) for 2 novel COVID-19 monoclonal therapies, bamlanivimab2-3 and casirivimab/imdevimab,3-4 respectively. The EUAs granted permission for these therapies to be administered for the treatment of mild to moderate COVID-19 in adult and pediatric patients (≥ 12 years and weighing at least 40 kg) with positive results of direct SARS-CoV-2 viral testing and who are at high risk for progressing to severe COVID-19 and/or hospitalization. The therapies work by targeting the SARS-CoV-2 spike protein and subsequent attachment to human angiotensin-converting enzyme 2 receptors. Clinical trial data leading to the EUA demonstrated a reduction in viral load, safe outcome, and most importantly, fewer hospitalization and emergency room visits, as compared to the placebo group.5-7 The use of monoclonal antibodies is not new and gained recognition during the Ebola crisis, when the monoclonal antibody to the Ebola virus showed a significant survival benefit.8 Providing monoclonal antibody therapy soon after symptom onset aligns with a shift from the onset of the pandemic to the current focus on the administration of pharmaceutical therapy early in the disease course. This shift prevents progression to severe COVID-19, with the goal of reducing patient mortality, hospitalizations, and strain on health care systems.

The availability of novel neutralizing monoclonal antibodies for COVID-19 led to discussions of how to incorporate these therapies as new options for patients. Our institution networked with colleagues from multiple disciplines to discuss processes and policies for the safe administration of the monoclonal antibody infusion therapies. Federal health leaders urge more use of monoclonal antibodies, but many hospitals have been unable to successfully implement infusions due to staff and logistical challenges.9 This article presents a viable process that hospitals can use to provide these novel therapies to outpatients with mild to moderate COVID-19.

The Mount Sinai Medical Center, Florida Experience

Mount Sinai Medical Center in Miami Beach, Florida, is the largest private, independent, not-for-profit teaching hospital in South Florida, comprising 672 licensed beds and supporting 150,000 emergency department (ED) visits annually. Per the EUA criteria for use, COVID-19 monoclonal antibody therapies are not authorized for patients who are hospitalized or who require oxygen therapy due to COVID-19. Therefore, options for outpatient administration needed to be evaluated. Directly following the first EUA press release, a task force of key stakeholders was assembled to brainstorm and develop a process to offer this therapy to the community. A multidisciplinary task force with representation from the ED, nursing, primary care, hospital medicine, pharmacy, risk management, billing, information technology, infection prevention, and senior level leadership participated (Table).

List of Key Stakeholders and Responsibilities

The task force reviewed institutional outpatient locations to determine whether offering this service would be feasible (eg, ED, ambulatory care facilities, cancer center). The ED was selected because it would offer the largest array of appointment times to meet the community needs with around-the-clock availability. While Mount Sinai Medical Center offers care in 3 emergency center locations in Aventura, Hialeah, and Miami Beach, it was determined to initiate the infusions at the main campus center in Miami Beach only. The main campus affords an onsite pharmacy with suitable staffing to prepare the anticipated volume of infusions in a timely manner, as both therapies have short stabilities following preparation. Thus, it was decided that patients from freestanding emergency centers in Aventura and Hialeah would be moved to the Miami Beach ED location to receive therapy. Operating at a single site also allowed for more rapid implementation, monitoring, and ability to make modifications more easily. Discussions for the possible expansion of COVID-19 monoclonal antibody infusions at satellite locations are underway.

Process implementation timeline

On November 20, 2020, 11 days after the formation of the multidisciplinary task force, the first COVID-19 monoclonal infusion was successfully administered. Figure 1 depicts the timeline from assessment to program implementation. Critical to implementation was the involvement of decision makers from all necessary departments early in the planning process to ensure that standard operating procedures were followed and that the patients, community, and organization had a positive experience. This allowed for simultaneous planning of electronic health record (Epic; EHR) builds, departmental workflows, and staff education, as described in the following section. Figure 2 shows the patient safety activities included in the implementation process.

Important patient safety initiatives

 

 

Key Stakeholder Involvement and Workflow

On the day of bamlanivimab EUA release, email communication was shared among hospital leadership with details of the press release. Departments were quickly involved to initiate a task force to assess if and how this therapy could be offered at Mount Sinai Medical Center. The following sections explain the role of each stakeholder and their essential role to operationalize these novel EUA treatment options. The task force was organized and led by our chief medical officer and chief nursing officer.

Information Technology

Medication Ordering and Documentation EHR and Smart Pumps. Early in the pandemic, the antimicrobial stewardship (ASP) clinical coordinator became the designated point person for pharmacy assessment of novel COVID-19 therapies. As such, this pharmacist began reviewing the bamlanivimab and, later, the casirivimab/imdevimab EUA Fact Sheet for Health Care Providers. All necessary elements for the complete and safe ordering and dispensing of the medication were developed and reviewed by pharmacy administration and ED nursing leadership for input, prior to submitting to the information technology team for implementation. Building the COVID-19 monoclonal medication records into the EHR allowed for detailed direction (ie, administration and preparation instructions) to be consistently applied. The medication records were also built into hospital smart pumps so that nurses could access prepopulated, accurate volumes and infusion rates to minimize errors.

Order Set Development. The pharmacy medication build was added to a comprehensive order set (Figure 3), which was then developed to guide prescribers and standardize the process around ordering of COVID-19 monoclonal therapies. While these therapies are new, oncology monoclonal therapies are regularly administered to outpatients at Mount Sinai Cancer Center. The cancer center was therefore consulted on their process surrounding best practices in administration of monoclonal antibody therapies. This included protocols for medications used in pretreatment and management of hypersensitivity reactions and potential adverse drug reactions of both COVID-19 monoclonal therapies. These medication orders were selected by default in the order set to ensure that all patients received premedications aimed at minimizing the risk of hypersensitivity reaction, and had as-needed medication orders, in the event a hypersensitivity reaction occurred. Reducing hypersensitivity reaction risk is important as well to increase the likelihood that the patient would receive full therapy, as management of this adverse drug reactions involves possible cessation of therapy depending on the level of severity. The pharmacy department also ensured these medications were stocked in ED automated dispensing cabinets to promote quick access. In addition to the aforementioned nursing orders, we added EUA criteria for use and hyperlinks to the Fact Sheets for Patients and Caregivers and Health Care Providers for each monoclonal therapy, and restricted ordering to ED physicians, nurse practitioners, and physician assistants.

COVID-19 monoclonal antibody order set

The order set underwent multidisciplinary review by pharmacy administration, the chair of emergency medicine, physicians, and ED nursing leadership prior to presentation and approval by the Pharmacy and Therapeutics Committee. Lastly, at time of implementation, the order set was added to the ED preference list, preventing inpatient access. Additionally, as a patient safety action, free- standing orders of COVID-19 monoclonal therapies were disabled, so providers could only order therapies via the approved, comprehensive order set.

Preliminary Assessment Tool. A provider assessment tool was developed to document patient-specific EUA criteria for use during initial assessment (Figure 4). This tool serves as a checklist and is visible to the full multidisciplinary team in the patient’s EHR. It is used as a resource at the time of pharmacist verification and ED physician assessment to ensure criteria for use are met.

Workflow for COVID-19 monoclonal antibody infusion

 

 

Outpatient Offices

Patient Referral. Patients with symptoms or concerns of COVID-19 exposure can make physician appointments via telemedicine or in person at Mount Sinai Medical Center’s primary care and specialty offices. At the time of patient encounter, physicians suspecting a COVID-19 diagnosis will refer patients for outpatient COVID-19 polymerase chain reaction (PCR) laboratory testing, which has an approximate 24-hour turnaround to results. Physicians also assess whether the patient meets EUA criteria for use, pending results of testing. In the event a patient meets EUA criteria for use, the physician provides patient counseling and requests verbal consent. Following this, the physician enters a note in the EHR describing the patient’s condition, criteria for use evaluation, and the patient’s verbal agreement to therapy. This preliminary screening is beneficial to begin planning with both the patient and ED to minimize delays. Patients are notified of the results of their test once available. If the COVID-19 PCR test returns positive, the physician will call the ED at the main campus and schedule the patient for COVID-19 monoclonal therapy. As the desired timeframe for administering COVID-19 monoclonal therapies is within less than 10 days of symptom onset, timely scheduling of appointments is crucial. Infusion appointments are typically provided the same or next day. The patients are informed that they must bring documentation of their positive COVID-19 PCR test to their ED visit. Lastly, because patients are pretreated with medication that may potentially impair driving, they are instructed that they cannot drive themselves home; ride shares also are not allowed in order to limit the spread of infection.

Emergency Department

Patient Arrival and Screening. A COVID-19 patient can be evaluated in the ED 1 of 2 ways. The first option is via outpatient office referral, as described previously. Upon arrival to the ED, a second screening is performed to ensure the patient still meets EUA criteria for use and the positive COVID-19 PCR test result is confirmed. If the patient no longer meets criteria, the patient is triaged accordingly, including evaluation for higher-level care (eg, supplemental oxygen, hospital admission). The second optoion is via new patient walk-ins without outpatient physician referral (Figure 4). In these cases, an initial screening is performed, documenting EUA criteria for use in the preliminary assessment (Figure 5). Physicians will consider an outside COVID-19 test as valid, so long as documentation is readily available confirming a positive PCR result. Otherwise, an in-house COVID-19 PCR test will be performed, which has a 2-hour turnaround time.

Electronic health record preliminary assessment

Infusion Schedule. The ED offers a total of 16 COVID-19 monoclonal infusions slots daily. These are broken up into 4 infusion time blocks (eg, 8 am, 12 pm, 4 pm, 8 pm), with each infusion time block consisting of 4 available patient appointments. A list of scheduled infusions for the day is emailed to the pharmacy department every morning, and patients are instructed to arrive 1 hour prior to their appointment time. This allows time for patient registration, assessment, and pharmacy notification in advance of order entry. For logistical purposes, and as a patient safety initiative to reduce the likelihood of medication errors, each of the available COVID-19 monoclonal antibodies is offered on a designated day. Bamlanivimab is offered on Tuesday, Thursday, Saturday, and Sunday, while casirivimab/imdevimab is offered Monday, Wednesday, and Friday. This provides flexibility to adjust should supply deviate based on Department of Health allocation or should new therapy options within this class of medication become available.

Patient Education. Prior to administration of the monoclonal therapy, physician and nursing staff obtain a formal, written patient consent for therapy and provide patients with the option of participating in the institutional review board (IRB) approved study. Details of this are discussed in the risk management and IRB sections of the article. Nursing staff also provides the medication-specific Fact Sheet for Patients and Caregivers in either Spanish or English, which is also included as a hyperlink on the COVID-19 Monoclonal Antibody Order Set for ease of access. Interpreter services are available for patients who speak other languages. An ED decentralized pharmacist is also available onsite Monday through Friday from 12 pm to 8:30 pm to supplement education and serve as a resource for any questions.

Infusion Ordering. Once the patient is ready to begin therapy, the he/she is brought to a dedicated overflow area of the ED. There are few, if any, patients in this location, and it is adjacent to the main emergency center for easy access by the patients, nurses, pharmacists, and physicians. The physician then enters orders in the EHR using the COVID-19 Monoclonal Antibody Order Set (Figure 3). Three discrete questions were built into the medication order: (1) Was patient consent obtained? (2) Was the Fact Sheet for Patient/Caregiver provided to the patient? (3) Is the patient COVID-19 PCR-positive? These questions were built as hard stops so that the medication orders cannot be placed without a response. This serves as another double-check to ensure processes are followed and helps facilitate timely verification by the pharmacist.

 

 

Medication Administration. One nurse is dedicated to administering the monoclonal therapies scheduled at 8 am and 12 pm and another at 4 pm and 8 pm. Each appointment block is 4 hours in duration to allow adequate time for patient registration, infusion, and postinfusion observation. The nurse administers the premedications and COVID-19 monoclonal therapy, and observes the patient for the required 1-hour postadministration observation period. Nursing orders detailing monitoring parameters for mild, moderate, and severe reactions, along with associated medication orders to administer in the event they occur, are detailed in the nursing orders of the COVID-19 Monoclonal Antibody Order Set (Figure 3). Prior to administration, the nurse scans each medication and the patient’s wrist identification band, and documents the time of administration within the EHR medication administration report.

Pharmacy Department

Medication Receipt Process. Inventory is currently allocated biweekly from the state department of health and will soon be transitioning to a direct order system. The pharmacy technician in charge of deliveries notifies the pharmacy Antimicrobial Stewardship Program (ASP) clinical coordinator upon receipt of the monoclonal therapies. Bamlanivimab is supplied as 1 vial per dose, whereas casirivimab/imdevimab is supplied as 4 vials or 8 vials per dose, depending how it is shipped. To reduce the likelihood of medication errors, the ASP clinical coordinator assembles each of the casirivimab/imdevimab vials into kits, where 1 kit equals 1 dose. Labels are then affixed to each kit indicating the medication name, number of vials which equal a full dose, and pharmacist signature. The kits are stored in a dedicated refrigerator, and inventory logs are affixed to the outside of the refrigerator and updated daily. This inventory is also communicated daily to ED physician, nursing, and pharmacy leadership, as well as the director of patient safety, who reports weekly usage to the state Department of Health and Human Services. These weekly reports are used to determine allocation amounts.

Medication Verification and Delivery. The Mount Sinai Medical Center pharmacist staffing model consists of centralized order entry and specialized, decentralized positions. All orders are verified by the ED pharmacist when scheduled (not a 24/7 service) and by the designated pharmacist for all other times. At the time of medication verification, the pharmacist documents patient-specific EUA criteria for use and confirms that consent was obtained and the Fact Sheet for Patients/Caregivers was provided. A pharmacist intervention was developed to assist with this documentation. Pharmacists input smart text “.COVIDmonoclonal” and a drop-down menu of EUA criteria for use appears. The pharmacist reviews the patient care notes and medication order question responses to ascertain this information, contacting the ED prescriber if further clarification is required. This verification serves as another check to ensure processes put in place are followed. Lastly, intravenous preparation and delivery are electronically recorded in the EHR, and the medications require nursing signature at the time of delivery to ensure a formal chain of custody.

Risk Management

At Mount Sinai Medical Center, all EUA and investigational therapies require patient consent. Consistent with this requirement, a COVID-19 monoclonal specific consent was developed by risk management. This is provided to every patient receiving a COVID-19 monoclonal infusion, in addition to the FDA EUA Fact Sheet for Patients and Caregivers, and documented as part of their EHR. The questions providers must answer are built into the order set to ensure this process is followed and these patient safety checks are incorporated into the workflow.

Billing and Finance Department

In alignment with Mount Sinai Medical Center’s mission to provide high-quality health care to its diverse community through teaching, research, charity care, and financial responsibility, it was determined that this therapy would be provided to all patients regardless of insurance type, including those who are uninsured. The billing and finance department was consulted prior to this service being offered, to provide patients with accurate and pertinent information. The billing and finance department provided guidance on how to document patient encounters at time of registration to facilitate appropriate billing. At this time, the medication is free of charge, but nonmedication-related ED fees apply. This is explained to patients so there is a clear understanding prior to booking their appointment.

 

 

Infection Prevention

As patients receiving COVID-19 monoclonal therapies can transmit the virus to others, measures to ensure protection for other patients and staff are vital. To minimize exposure, specific nursing and physician staff from the ED are assigned to the treatment of these patients, and patients receive infusions and postobservation monitoring in a designated wing of the ED. Additionally, all staff who interact with these patients are required to don full personal protective equipment. This includes not only physicians and nurses but all specialties such as physician assistants, nurse practitioners, pharmacists, and laboratory technicians. Moreover, patients are not permitted to go home in a ride share and are counseled on Centers for Disease Control and Prevention quarantining following infusion.

Measurement of Process and Outcomes and Reporting

IRB approval was sought and obtained early during initiation of this service, allowing study consent to be offered to patients at the time general consent was obtained, which maximized patient recruitment and streamlined workflow. The study is a prospective observational research study to determine the impact of administration of COVID-19 monoclonal antibody therapy on length of symptoms, chronic illness, and rate of hospitalization. Most patients were eager to participate and offer their assistance to the scientific community during this pandemic.

Staff Education

In order to successfully implement this multidisciplinary EUA treatment option, comprehensive staff education was paramount after the workflow was developed. Prior to the first day of infusions, nurses and pharmacists were provided education during multiple huddle announcements. The pharmacy team also provided screen captures via email to the pharmacists so they could become familiar with the order set, intervention documentation, and location of the preliminary assessment of EUA criteria for use at the time of order verification. The emergency medicine department chair and chief medical officer also provided education via several virtual meetings and email to referring physicians (specialists and primary care) and residents in the emergency centers involved in COVID-19 monoclonal therapy-related patient care.

Factors Contributing to Success

We believe the reasons for continued success of this process are multifactorial and include the following key elements. Multidisciplinary planning, which included decision makers and all stakeholders, began at the time the idea was conceived. This allowed quick implementation of this service by efficiently navigating barriers to engaging impacted staff early on. Throughout this process, the authors set realistic step-wise goals. While navigating through the many details to implementation described, we also kept in mind the big picture, which was to provide this potentially lifesaving therapy to as many qualifying members of our community as possible. This included being flexible with the process and adapting when needed to achieve this ultimate goal. A focus on safety remained a priority to minimize possible errors and enhance patient and staff satisfaction. The optimization of the EHR streamlined workflow, provided point-of-care resources, and enhanced patient safety. Additionally, the target date set for implementation allowed staff and department leads adequate time to plan for and anticipate the changes. Serving only 1 patient on the first day allowed time for staff to experience this new process hands-on and provided opportunity for focused education. This team communication was essential to implementing this project, including staff training of processes and procedures prior to go-live. Early incorporation of IRB approval allowed the experience to be assessed and considered for contribution to the scientific literature to tackle this novel virus that has impacted our communities locally, nationally, and abroad. Moreover, continued measurement and reporting on a regular basis leads to performance improvement. The process outlined here can be adapted to incorporate other new therapies in the future, such as the recent February 9, 2021, EUA of the COVID-19 monoclonal antibody combination bamlanivimab and etesevimab.10

Conclusion

We administered 790 COVID-19 monoclonal antibody infusions between November 20, 2020 and March 5, 2021. Steps to minimize the likelihood of hypersensitivity reactions were implemented, and a low incidence (< 1%) has been observed. There has been no incidence of infection, concern from staff about infection prevention, or risk of infection during the processes. There have been very infrequent cost-related concerns raised by patients, typically due to incomplete communication regarding billing prior to the infusion. To address these issues, staff education has been provided to enhance patient instruction on this topic. The program has provided patient and family satisfaction, as well nursing, physician, pharmacist, clinical staff, and hospital administration pride and gratification. Setting up a new program to provide a 4-hour patient encounter to infuse therapy to high-risk patients with COVID-19 requires commitment and effort. This article describes the experience, ideas, and formula others may consider using to set up such a program. Through networking and formal phone calls and meetings about monoclonal antibody therapy, we have heard about other institutions who have not been able to institute this program due to various barriers to implementation. We hope our experience serves as a resource for others to provide this therapy to their patients and expand access in an effort to mitigate COVID-19 consequences and cases affecting our communities.

Corresponding author: Kathleen Jodoin, PharmD, BCPS, Mount Sinai Medical Center, 4300 Alton Rd, Miami Beach, FL 33140; kathleen.jodoin@msmc.com.

Financial disclosures: None.

References

1. COVID Data Tracker. Center for Disease Control and Prevention. https://covid.cdc.gov/covid-data-tracker/#global-counts-rates. Accessed March 12, 2021.

2. Fact Sheet for Health Care Providers Emergency Use Authorization (EUA) of Bamlanivimab. US Food and Drug Administration. Updated February 2021. Accessed March 9, 2021. https://www.fda.gov/media/143603/download

3. Coronavirus (COVID-19) Update: FDA Authorizes Monoclonal Antibodies for Treatment of COVID-19 | FDA. https://www.fda.gov/news-events/press-announcements/coronavirus-covid-19-update-fda-authorizes-monoclonal-antibodies-treatment-covid-19. Accessed February 14, 2021.

4. Fact Sheet for Health Care Providers Emergency Use Authorization (EUA) of Casirivimab and Imdevimab. US Food and Drug Administration. Updated December 2020. Accessed March 9, 2021. https://www.fda.gov/media/143892/download

5. Chen P, Nirula A, Heller B, et al. SARS-CoV-2 Neutralizing antibody LY-CoV555 in outpatients with COVID-19. N Engl J Med. 2021;384(3):229-237. doi:10.1056/NEJMoa2029849

6. Gottlieb RL, Nirula A, Chen P, et al. Effect of bamlanivimab as monotherapy or in combination with etesevimab on viral load in patients with mild to moderate COVID-19: a randomized clinical trial. 10.1JAMA. 2021;325(7):632-644. doi:10.1001/jama.2021.0202

7. Weinreich DM, Sivapalasingam S, Norton T, et al. REGN-COV2, a neutralizing antibody cocktail, in outpatients with COVID-19. 10.1N Engl J Med. 2021;384:238-251. doi:10.1056/nejmoa2035002

8. Mulangu S, Dodd LE, Davey RT Jr, et al. A randomized, controlled trial of Ebola virus disease therapeutics. 10.1N Engl J Med. 2019;381:2293-2303. doi:10.1056/NEJMoa1910993

9. Boyle, P. Can an experimental treatment keep COVID-19 patients out of hospitals? Association of American Medical Colleges. January 29, 2021. Accessed March 9, 2021. https://www.aamc.org/news-insights/can-experimental-treatment-keep-covid-19-patients-out-hospitals

10. Fact Sheet for Health Care Providers Emergency Use Authorization (EUA) of Bamlanivimab and Etesevimab. US Food and Drug Administration. Updated February 2021. Accessed March 9, 2021. https://www.fda.gov/media/145802/download

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From Mount Sinai Medical Center, Miami Beach, FL.

Abstract

Objective: To develop and implement a process for administering COVID-19 monoclonal antibody infusions for outpatients with mild or moderate COVID-19 at high risk for hospitalization, using multidisciplinary collaboration, US Food and Drug Administration (FDA) guidance, and infection prevention standards.

Methods: When monoclonal antibody therapy became available for mild or moderate COVID-19 outpatients via Emergency Use Authorization (EUA), our institution sought to provide this therapy option to our patients. We describe the process for planning, implementing, and maintaining a successful program for administering novel therapies based on FDA guidance and infection prevention standards. Key components of our implementation process were multidisciplinary planning involving decision makers and stakeholders; setting realistic goals in the process; team communication; and measuring and reporting quality improvement on a regular basis.

Results: A total of 790 COVID-19 monoclonal antibody infusions were administered from November 20, 2020 to March 5, 2021. Steps to minimize the likelihood of adverse drug reactions were implemented and a low incidence (< 1%) has occurred. There has been no concern from staff regarding infection during the process. Rarely, patients have raised cost-related concerns, typically due to incomplete communication regarding billing prior to the infusion. Patients, families, nursing staff, physicians, pharmacy, and hospital administration have expressed satisfaction with the program.

Conclusion: This process can provide a template for other hospitals or health care delivery facilities to provide novel therapies to patients with mild or moderate COVID-19 in a safe and effective manner.

Keywords: COVID-19; monoclonal antibody; infusion; emergency use authorization.

SARS-CoV-2 and the disease it causes, COVID-19, have transformed from scientific vernacular to common household terms. It began with a cluster of pneumonia cases of unknown etiology in December 2019 in Wuhan, China, with physicians there reporting a novel coronavirus strain (2019-nCoV), now referred to as SARS-CoV-2. Rapid spread of this virus resulted in the World Health Organization (WHO) declaring an international public health emergency. Since this time, the virus has evolved into a worldwide pandemic. COVID-19 has dramatically impacted our society, resulting in more than 2.63 million global deaths as of this writing, of which more than 527,000 deaths have occurred in the United States.1 This novel virus has resulted in a flurry of literature, research, therapies, and collaboration across multiple disciplines in an effort to prevent, treat, and mitigate cases and complications of this disease.

 

 

On November 9, 2020, and November 21, 2020, the US Food and Drug Administration (FDA) issued Emergency Use Authorizations (EUA) for 2 novel COVID-19 monoclonal therapies, bamlanivimab2-3 and casirivimab/imdevimab,3-4 respectively. The EUAs granted permission for these therapies to be administered for the treatment of mild to moderate COVID-19 in adult and pediatric patients (≥ 12 years and weighing at least 40 kg) with positive results of direct SARS-CoV-2 viral testing and who are at high risk for progressing to severe COVID-19 and/or hospitalization. The therapies work by targeting the SARS-CoV-2 spike protein and subsequent attachment to human angiotensin-converting enzyme 2 receptors. Clinical trial data leading to the EUA demonstrated a reduction in viral load, safe outcome, and most importantly, fewer hospitalization and emergency room visits, as compared to the placebo group.5-7 The use of monoclonal antibodies is not new and gained recognition during the Ebola crisis, when the monoclonal antibody to the Ebola virus showed a significant survival benefit.8 Providing monoclonal antibody therapy soon after symptom onset aligns with a shift from the onset of the pandemic to the current focus on the administration of pharmaceutical therapy early in the disease course. This shift prevents progression to severe COVID-19, with the goal of reducing patient mortality, hospitalizations, and strain on health care systems.

The availability of novel neutralizing monoclonal antibodies for COVID-19 led to discussions of how to incorporate these therapies as new options for patients. Our institution networked with colleagues from multiple disciplines to discuss processes and policies for the safe administration of the monoclonal antibody infusion therapies. Federal health leaders urge more use of monoclonal antibodies, but many hospitals have been unable to successfully implement infusions due to staff and logistical challenges.9 This article presents a viable process that hospitals can use to provide these novel therapies to outpatients with mild to moderate COVID-19.

The Mount Sinai Medical Center, Florida Experience

Mount Sinai Medical Center in Miami Beach, Florida, is the largest private, independent, not-for-profit teaching hospital in South Florida, comprising 672 licensed beds and supporting 150,000 emergency department (ED) visits annually. Per the EUA criteria for use, COVID-19 monoclonal antibody therapies are not authorized for patients who are hospitalized or who require oxygen therapy due to COVID-19. Therefore, options for outpatient administration needed to be evaluated. Directly following the first EUA press release, a task force of key stakeholders was assembled to brainstorm and develop a process to offer this therapy to the community. A multidisciplinary task force with representation from the ED, nursing, primary care, hospital medicine, pharmacy, risk management, billing, information technology, infection prevention, and senior level leadership participated (Table).

List of Key Stakeholders and Responsibilities

The task force reviewed institutional outpatient locations to determine whether offering this service would be feasible (eg, ED, ambulatory care facilities, cancer center). The ED was selected because it would offer the largest array of appointment times to meet the community needs with around-the-clock availability. While Mount Sinai Medical Center offers care in 3 emergency center locations in Aventura, Hialeah, and Miami Beach, it was determined to initiate the infusions at the main campus center in Miami Beach only. The main campus affords an onsite pharmacy with suitable staffing to prepare the anticipated volume of infusions in a timely manner, as both therapies have short stabilities following preparation. Thus, it was decided that patients from freestanding emergency centers in Aventura and Hialeah would be moved to the Miami Beach ED location to receive therapy. Operating at a single site also allowed for more rapid implementation, monitoring, and ability to make modifications more easily. Discussions for the possible expansion of COVID-19 monoclonal antibody infusions at satellite locations are underway.

Process implementation timeline

On November 20, 2020, 11 days after the formation of the multidisciplinary task force, the first COVID-19 monoclonal infusion was successfully administered. Figure 1 depicts the timeline from assessment to program implementation. Critical to implementation was the involvement of decision makers from all necessary departments early in the planning process to ensure that standard operating procedures were followed and that the patients, community, and organization had a positive experience. This allowed for simultaneous planning of electronic health record (Epic; EHR) builds, departmental workflows, and staff education, as described in the following section. Figure 2 shows the patient safety activities included in the implementation process.

Important patient safety initiatives

 

 

Key Stakeholder Involvement and Workflow

On the day of bamlanivimab EUA release, email communication was shared among hospital leadership with details of the press release. Departments were quickly involved to initiate a task force to assess if and how this therapy could be offered at Mount Sinai Medical Center. The following sections explain the role of each stakeholder and their essential role to operationalize these novel EUA treatment options. The task force was organized and led by our chief medical officer and chief nursing officer.

Information Technology

Medication Ordering and Documentation EHR and Smart Pumps. Early in the pandemic, the antimicrobial stewardship (ASP) clinical coordinator became the designated point person for pharmacy assessment of novel COVID-19 therapies. As such, this pharmacist began reviewing the bamlanivimab and, later, the casirivimab/imdevimab EUA Fact Sheet for Health Care Providers. All necessary elements for the complete and safe ordering and dispensing of the medication were developed and reviewed by pharmacy administration and ED nursing leadership for input, prior to submitting to the information technology team for implementation. Building the COVID-19 monoclonal medication records into the EHR allowed for detailed direction (ie, administration and preparation instructions) to be consistently applied. The medication records were also built into hospital smart pumps so that nurses could access prepopulated, accurate volumes and infusion rates to minimize errors.

Order Set Development. The pharmacy medication build was added to a comprehensive order set (Figure 3), which was then developed to guide prescribers and standardize the process around ordering of COVID-19 monoclonal therapies. While these therapies are new, oncology monoclonal therapies are regularly administered to outpatients at Mount Sinai Cancer Center. The cancer center was therefore consulted on their process surrounding best practices in administration of monoclonal antibody therapies. This included protocols for medications used in pretreatment and management of hypersensitivity reactions and potential adverse drug reactions of both COVID-19 monoclonal therapies. These medication orders were selected by default in the order set to ensure that all patients received premedications aimed at minimizing the risk of hypersensitivity reaction, and had as-needed medication orders, in the event a hypersensitivity reaction occurred. Reducing hypersensitivity reaction risk is important as well to increase the likelihood that the patient would receive full therapy, as management of this adverse drug reactions involves possible cessation of therapy depending on the level of severity. The pharmacy department also ensured these medications were stocked in ED automated dispensing cabinets to promote quick access. In addition to the aforementioned nursing orders, we added EUA criteria for use and hyperlinks to the Fact Sheets for Patients and Caregivers and Health Care Providers for each monoclonal therapy, and restricted ordering to ED physicians, nurse practitioners, and physician assistants.

COVID-19 monoclonal antibody order set

The order set underwent multidisciplinary review by pharmacy administration, the chair of emergency medicine, physicians, and ED nursing leadership prior to presentation and approval by the Pharmacy and Therapeutics Committee. Lastly, at time of implementation, the order set was added to the ED preference list, preventing inpatient access. Additionally, as a patient safety action, free- standing orders of COVID-19 monoclonal therapies were disabled, so providers could only order therapies via the approved, comprehensive order set.

Preliminary Assessment Tool. A provider assessment tool was developed to document patient-specific EUA criteria for use during initial assessment (Figure 4). This tool serves as a checklist and is visible to the full multidisciplinary team in the patient’s EHR. It is used as a resource at the time of pharmacist verification and ED physician assessment to ensure criteria for use are met.

Workflow for COVID-19 monoclonal antibody infusion

 

 

Outpatient Offices

Patient Referral. Patients with symptoms or concerns of COVID-19 exposure can make physician appointments via telemedicine or in person at Mount Sinai Medical Center’s primary care and specialty offices. At the time of patient encounter, physicians suspecting a COVID-19 diagnosis will refer patients for outpatient COVID-19 polymerase chain reaction (PCR) laboratory testing, which has an approximate 24-hour turnaround to results. Physicians also assess whether the patient meets EUA criteria for use, pending results of testing. In the event a patient meets EUA criteria for use, the physician provides patient counseling and requests verbal consent. Following this, the physician enters a note in the EHR describing the patient’s condition, criteria for use evaluation, and the patient’s verbal agreement to therapy. This preliminary screening is beneficial to begin planning with both the patient and ED to minimize delays. Patients are notified of the results of their test once available. If the COVID-19 PCR test returns positive, the physician will call the ED at the main campus and schedule the patient for COVID-19 monoclonal therapy. As the desired timeframe for administering COVID-19 monoclonal therapies is within less than 10 days of symptom onset, timely scheduling of appointments is crucial. Infusion appointments are typically provided the same or next day. The patients are informed that they must bring documentation of their positive COVID-19 PCR test to their ED visit. Lastly, because patients are pretreated with medication that may potentially impair driving, they are instructed that they cannot drive themselves home; ride shares also are not allowed in order to limit the spread of infection.

Emergency Department

Patient Arrival and Screening. A COVID-19 patient can be evaluated in the ED 1 of 2 ways. The first option is via outpatient office referral, as described previously. Upon arrival to the ED, a second screening is performed to ensure the patient still meets EUA criteria for use and the positive COVID-19 PCR test result is confirmed. If the patient no longer meets criteria, the patient is triaged accordingly, including evaluation for higher-level care (eg, supplemental oxygen, hospital admission). The second optoion is via new patient walk-ins without outpatient physician referral (Figure 4). In these cases, an initial screening is performed, documenting EUA criteria for use in the preliminary assessment (Figure 5). Physicians will consider an outside COVID-19 test as valid, so long as documentation is readily available confirming a positive PCR result. Otherwise, an in-house COVID-19 PCR test will be performed, which has a 2-hour turnaround time.

Electronic health record preliminary assessment

Infusion Schedule. The ED offers a total of 16 COVID-19 monoclonal infusions slots daily. These are broken up into 4 infusion time blocks (eg, 8 am, 12 pm, 4 pm, 8 pm), with each infusion time block consisting of 4 available patient appointments. A list of scheduled infusions for the day is emailed to the pharmacy department every morning, and patients are instructed to arrive 1 hour prior to their appointment time. This allows time for patient registration, assessment, and pharmacy notification in advance of order entry. For logistical purposes, and as a patient safety initiative to reduce the likelihood of medication errors, each of the available COVID-19 monoclonal antibodies is offered on a designated day. Bamlanivimab is offered on Tuesday, Thursday, Saturday, and Sunday, while casirivimab/imdevimab is offered Monday, Wednesday, and Friday. This provides flexibility to adjust should supply deviate based on Department of Health allocation or should new therapy options within this class of medication become available.

Patient Education. Prior to administration of the monoclonal therapy, physician and nursing staff obtain a formal, written patient consent for therapy and provide patients with the option of participating in the institutional review board (IRB) approved study. Details of this are discussed in the risk management and IRB sections of the article. Nursing staff also provides the medication-specific Fact Sheet for Patients and Caregivers in either Spanish or English, which is also included as a hyperlink on the COVID-19 Monoclonal Antibody Order Set for ease of access. Interpreter services are available for patients who speak other languages. An ED decentralized pharmacist is also available onsite Monday through Friday from 12 pm to 8:30 pm to supplement education and serve as a resource for any questions.

Infusion Ordering. Once the patient is ready to begin therapy, the he/she is brought to a dedicated overflow area of the ED. There are few, if any, patients in this location, and it is adjacent to the main emergency center for easy access by the patients, nurses, pharmacists, and physicians. The physician then enters orders in the EHR using the COVID-19 Monoclonal Antibody Order Set (Figure 3). Three discrete questions were built into the medication order: (1) Was patient consent obtained? (2) Was the Fact Sheet for Patient/Caregiver provided to the patient? (3) Is the patient COVID-19 PCR-positive? These questions were built as hard stops so that the medication orders cannot be placed without a response. This serves as another double-check to ensure processes are followed and helps facilitate timely verification by the pharmacist.

 

 

Medication Administration. One nurse is dedicated to administering the monoclonal therapies scheduled at 8 am and 12 pm and another at 4 pm and 8 pm. Each appointment block is 4 hours in duration to allow adequate time for patient registration, infusion, and postinfusion observation. The nurse administers the premedications and COVID-19 monoclonal therapy, and observes the patient for the required 1-hour postadministration observation period. Nursing orders detailing monitoring parameters for mild, moderate, and severe reactions, along with associated medication orders to administer in the event they occur, are detailed in the nursing orders of the COVID-19 Monoclonal Antibody Order Set (Figure 3). Prior to administration, the nurse scans each medication and the patient’s wrist identification band, and documents the time of administration within the EHR medication administration report.

Pharmacy Department

Medication Receipt Process. Inventory is currently allocated biweekly from the state department of health and will soon be transitioning to a direct order system. The pharmacy technician in charge of deliveries notifies the pharmacy Antimicrobial Stewardship Program (ASP) clinical coordinator upon receipt of the monoclonal therapies. Bamlanivimab is supplied as 1 vial per dose, whereas casirivimab/imdevimab is supplied as 4 vials or 8 vials per dose, depending how it is shipped. To reduce the likelihood of medication errors, the ASP clinical coordinator assembles each of the casirivimab/imdevimab vials into kits, where 1 kit equals 1 dose. Labels are then affixed to each kit indicating the medication name, number of vials which equal a full dose, and pharmacist signature. The kits are stored in a dedicated refrigerator, and inventory logs are affixed to the outside of the refrigerator and updated daily. This inventory is also communicated daily to ED physician, nursing, and pharmacy leadership, as well as the director of patient safety, who reports weekly usage to the state Department of Health and Human Services. These weekly reports are used to determine allocation amounts.

Medication Verification and Delivery. The Mount Sinai Medical Center pharmacist staffing model consists of centralized order entry and specialized, decentralized positions. All orders are verified by the ED pharmacist when scheduled (not a 24/7 service) and by the designated pharmacist for all other times. At the time of medication verification, the pharmacist documents patient-specific EUA criteria for use and confirms that consent was obtained and the Fact Sheet for Patients/Caregivers was provided. A pharmacist intervention was developed to assist with this documentation. Pharmacists input smart text “.COVIDmonoclonal” and a drop-down menu of EUA criteria for use appears. The pharmacist reviews the patient care notes and medication order question responses to ascertain this information, contacting the ED prescriber if further clarification is required. This verification serves as another check to ensure processes put in place are followed. Lastly, intravenous preparation and delivery are electronically recorded in the EHR, and the medications require nursing signature at the time of delivery to ensure a formal chain of custody.

Risk Management

At Mount Sinai Medical Center, all EUA and investigational therapies require patient consent. Consistent with this requirement, a COVID-19 monoclonal specific consent was developed by risk management. This is provided to every patient receiving a COVID-19 monoclonal infusion, in addition to the FDA EUA Fact Sheet for Patients and Caregivers, and documented as part of their EHR. The questions providers must answer are built into the order set to ensure this process is followed and these patient safety checks are incorporated into the workflow.

Billing and Finance Department

In alignment with Mount Sinai Medical Center’s mission to provide high-quality health care to its diverse community through teaching, research, charity care, and financial responsibility, it was determined that this therapy would be provided to all patients regardless of insurance type, including those who are uninsured. The billing and finance department was consulted prior to this service being offered, to provide patients with accurate and pertinent information. The billing and finance department provided guidance on how to document patient encounters at time of registration to facilitate appropriate billing. At this time, the medication is free of charge, but nonmedication-related ED fees apply. This is explained to patients so there is a clear understanding prior to booking their appointment.

 

 

Infection Prevention

As patients receiving COVID-19 monoclonal therapies can transmit the virus to others, measures to ensure protection for other patients and staff are vital. To minimize exposure, specific nursing and physician staff from the ED are assigned to the treatment of these patients, and patients receive infusions and postobservation monitoring in a designated wing of the ED. Additionally, all staff who interact with these patients are required to don full personal protective equipment. This includes not only physicians and nurses but all specialties such as physician assistants, nurse practitioners, pharmacists, and laboratory technicians. Moreover, patients are not permitted to go home in a ride share and are counseled on Centers for Disease Control and Prevention quarantining following infusion.

Measurement of Process and Outcomes and Reporting

IRB approval was sought and obtained early during initiation of this service, allowing study consent to be offered to patients at the time general consent was obtained, which maximized patient recruitment and streamlined workflow. The study is a prospective observational research study to determine the impact of administration of COVID-19 monoclonal antibody therapy on length of symptoms, chronic illness, and rate of hospitalization. Most patients were eager to participate and offer their assistance to the scientific community during this pandemic.

Staff Education

In order to successfully implement this multidisciplinary EUA treatment option, comprehensive staff education was paramount after the workflow was developed. Prior to the first day of infusions, nurses and pharmacists were provided education during multiple huddle announcements. The pharmacy team also provided screen captures via email to the pharmacists so they could become familiar with the order set, intervention documentation, and location of the preliminary assessment of EUA criteria for use at the time of order verification. The emergency medicine department chair and chief medical officer also provided education via several virtual meetings and email to referring physicians (specialists and primary care) and residents in the emergency centers involved in COVID-19 monoclonal therapy-related patient care.

Factors Contributing to Success

We believe the reasons for continued success of this process are multifactorial and include the following key elements. Multidisciplinary planning, which included decision makers and all stakeholders, began at the time the idea was conceived. This allowed quick implementation of this service by efficiently navigating barriers to engaging impacted staff early on. Throughout this process, the authors set realistic step-wise goals. While navigating through the many details to implementation described, we also kept in mind the big picture, which was to provide this potentially lifesaving therapy to as many qualifying members of our community as possible. This included being flexible with the process and adapting when needed to achieve this ultimate goal. A focus on safety remained a priority to minimize possible errors and enhance patient and staff satisfaction. The optimization of the EHR streamlined workflow, provided point-of-care resources, and enhanced patient safety. Additionally, the target date set for implementation allowed staff and department leads adequate time to plan for and anticipate the changes. Serving only 1 patient on the first day allowed time for staff to experience this new process hands-on and provided opportunity for focused education. This team communication was essential to implementing this project, including staff training of processes and procedures prior to go-live. Early incorporation of IRB approval allowed the experience to be assessed and considered for contribution to the scientific literature to tackle this novel virus that has impacted our communities locally, nationally, and abroad. Moreover, continued measurement and reporting on a regular basis leads to performance improvement. The process outlined here can be adapted to incorporate other new therapies in the future, such as the recent February 9, 2021, EUA of the COVID-19 monoclonal antibody combination bamlanivimab and etesevimab.10

Conclusion

We administered 790 COVID-19 monoclonal antibody infusions between November 20, 2020 and March 5, 2021. Steps to minimize the likelihood of hypersensitivity reactions were implemented, and a low incidence (< 1%) has been observed. There has been no incidence of infection, concern from staff about infection prevention, or risk of infection during the processes. There have been very infrequent cost-related concerns raised by patients, typically due to incomplete communication regarding billing prior to the infusion. To address these issues, staff education has been provided to enhance patient instruction on this topic. The program has provided patient and family satisfaction, as well nursing, physician, pharmacist, clinical staff, and hospital administration pride and gratification. Setting up a new program to provide a 4-hour patient encounter to infuse therapy to high-risk patients with COVID-19 requires commitment and effort. This article describes the experience, ideas, and formula others may consider using to set up such a program. Through networking and formal phone calls and meetings about monoclonal antibody therapy, we have heard about other institutions who have not been able to institute this program due to various barriers to implementation. We hope our experience serves as a resource for others to provide this therapy to their patients and expand access in an effort to mitigate COVID-19 consequences and cases affecting our communities.

Corresponding author: Kathleen Jodoin, PharmD, BCPS, Mount Sinai Medical Center, 4300 Alton Rd, Miami Beach, FL 33140; kathleen.jodoin@msmc.com.

Financial disclosures: None.

From Mount Sinai Medical Center, Miami Beach, FL.

Abstract

Objective: To develop and implement a process for administering COVID-19 monoclonal antibody infusions for outpatients with mild or moderate COVID-19 at high risk for hospitalization, using multidisciplinary collaboration, US Food and Drug Administration (FDA) guidance, and infection prevention standards.

Methods: When monoclonal antibody therapy became available for mild or moderate COVID-19 outpatients via Emergency Use Authorization (EUA), our institution sought to provide this therapy option to our patients. We describe the process for planning, implementing, and maintaining a successful program for administering novel therapies based on FDA guidance and infection prevention standards. Key components of our implementation process were multidisciplinary planning involving decision makers and stakeholders; setting realistic goals in the process; team communication; and measuring and reporting quality improvement on a regular basis.

Results: A total of 790 COVID-19 monoclonal antibody infusions were administered from November 20, 2020 to March 5, 2021. Steps to minimize the likelihood of adverse drug reactions were implemented and a low incidence (< 1%) has occurred. There has been no concern from staff regarding infection during the process. Rarely, patients have raised cost-related concerns, typically due to incomplete communication regarding billing prior to the infusion. Patients, families, nursing staff, physicians, pharmacy, and hospital administration have expressed satisfaction with the program.

Conclusion: This process can provide a template for other hospitals or health care delivery facilities to provide novel therapies to patients with mild or moderate COVID-19 in a safe and effective manner.

Keywords: COVID-19; monoclonal antibody; infusion; emergency use authorization.

SARS-CoV-2 and the disease it causes, COVID-19, have transformed from scientific vernacular to common household terms. It began with a cluster of pneumonia cases of unknown etiology in December 2019 in Wuhan, China, with physicians there reporting a novel coronavirus strain (2019-nCoV), now referred to as SARS-CoV-2. Rapid spread of this virus resulted in the World Health Organization (WHO) declaring an international public health emergency. Since this time, the virus has evolved into a worldwide pandemic. COVID-19 has dramatically impacted our society, resulting in more than 2.63 million global deaths as of this writing, of which more than 527,000 deaths have occurred in the United States.1 This novel virus has resulted in a flurry of literature, research, therapies, and collaboration across multiple disciplines in an effort to prevent, treat, and mitigate cases and complications of this disease.

 

 

On November 9, 2020, and November 21, 2020, the US Food and Drug Administration (FDA) issued Emergency Use Authorizations (EUA) for 2 novel COVID-19 monoclonal therapies, bamlanivimab2-3 and casirivimab/imdevimab,3-4 respectively. The EUAs granted permission for these therapies to be administered for the treatment of mild to moderate COVID-19 in adult and pediatric patients (≥ 12 years and weighing at least 40 kg) with positive results of direct SARS-CoV-2 viral testing and who are at high risk for progressing to severe COVID-19 and/or hospitalization. The therapies work by targeting the SARS-CoV-2 spike protein and subsequent attachment to human angiotensin-converting enzyme 2 receptors. Clinical trial data leading to the EUA demonstrated a reduction in viral load, safe outcome, and most importantly, fewer hospitalization and emergency room visits, as compared to the placebo group.5-7 The use of monoclonal antibodies is not new and gained recognition during the Ebola crisis, when the monoclonal antibody to the Ebola virus showed a significant survival benefit.8 Providing monoclonal antibody therapy soon after symptom onset aligns with a shift from the onset of the pandemic to the current focus on the administration of pharmaceutical therapy early in the disease course. This shift prevents progression to severe COVID-19, with the goal of reducing patient mortality, hospitalizations, and strain on health care systems.

The availability of novel neutralizing monoclonal antibodies for COVID-19 led to discussions of how to incorporate these therapies as new options for patients. Our institution networked with colleagues from multiple disciplines to discuss processes and policies for the safe administration of the monoclonal antibody infusion therapies. Federal health leaders urge more use of monoclonal antibodies, but many hospitals have been unable to successfully implement infusions due to staff and logistical challenges.9 This article presents a viable process that hospitals can use to provide these novel therapies to outpatients with mild to moderate COVID-19.

The Mount Sinai Medical Center, Florida Experience

Mount Sinai Medical Center in Miami Beach, Florida, is the largest private, independent, not-for-profit teaching hospital in South Florida, comprising 672 licensed beds and supporting 150,000 emergency department (ED) visits annually. Per the EUA criteria for use, COVID-19 monoclonal antibody therapies are not authorized for patients who are hospitalized or who require oxygen therapy due to COVID-19. Therefore, options for outpatient administration needed to be evaluated. Directly following the first EUA press release, a task force of key stakeholders was assembled to brainstorm and develop a process to offer this therapy to the community. A multidisciplinary task force with representation from the ED, nursing, primary care, hospital medicine, pharmacy, risk management, billing, information technology, infection prevention, and senior level leadership participated (Table).

List of Key Stakeholders and Responsibilities

The task force reviewed institutional outpatient locations to determine whether offering this service would be feasible (eg, ED, ambulatory care facilities, cancer center). The ED was selected because it would offer the largest array of appointment times to meet the community needs with around-the-clock availability. While Mount Sinai Medical Center offers care in 3 emergency center locations in Aventura, Hialeah, and Miami Beach, it was determined to initiate the infusions at the main campus center in Miami Beach only. The main campus affords an onsite pharmacy with suitable staffing to prepare the anticipated volume of infusions in a timely manner, as both therapies have short stabilities following preparation. Thus, it was decided that patients from freestanding emergency centers in Aventura and Hialeah would be moved to the Miami Beach ED location to receive therapy. Operating at a single site also allowed for more rapid implementation, monitoring, and ability to make modifications more easily. Discussions for the possible expansion of COVID-19 monoclonal antibody infusions at satellite locations are underway.

Process implementation timeline

On November 20, 2020, 11 days after the formation of the multidisciplinary task force, the first COVID-19 monoclonal infusion was successfully administered. Figure 1 depicts the timeline from assessment to program implementation. Critical to implementation was the involvement of decision makers from all necessary departments early in the planning process to ensure that standard operating procedures were followed and that the patients, community, and organization had a positive experience. This allowed for simultaneous planning of electronic health record (Epic; EHR) builds, departmental workflows, and staff education, as described in the following section. Figure 2 shows the patient safety activities included in the implementation process.

Important patient safety initiatives

 

 

Key Stakeholder Involvement and Workflow

On the day of bamlanivimab EUA release, email communication was shared among hospital leadership with details of the press release. Departments were quickly involved to initiate a task force to assess if and how this therapy could be offered at Mount Sinai Medical Center. The following sections explain the role of each stakeholder and their essential role to operationalize these novel EUA treatment options. The task force was organized and led by our chief medical officer and chief nursing officer.

Information Technology

Medication Ordering and Documentation EHR and Smart Pumps. Early in the pandemic, the antimicrobial stewardship (ASP) clinical coordinator became the designated point person for pharmacy assessment of novel COVID-19 therapies. As such, this pharmacist began reviewing the bamlanivimab and, later, the casirivimab/imdevimab EUA Fact Sheet for Health Care Providers. All necessary elements for the complete and safe ordering and dispensing of the medication were developed and reviewed by pharmacy administration and ED nursing leadership for input, prior to submitting to the information technology team for implementation. Building the COVID-19 monoclonal medication records into the EHR allowed for detailed direction (ie, administration and preparation instructions) to be consistently applied. The medication records were also built into hospital smart pumps so that nurses could access prepopulated, accurate volumes and infusion rates to minimize errors.

Order Set Development. The pharmacy medication build was added to a comprehensive order set (Figure 3), which was then developed to guide prescribers and standardize the process around ordering of COVID-19 monoclonal therapies. While these therapies are new, oncology monoclonal therapies are regularly administered to outpatients at Mount Sinai Cancer Center. The cancer center was therefore consulted on their process surrounding best practices in administration of monoclonal antibody therapies. This included protocols for medications used in pretreatment and management of hypersensitivity reactions and potential adverse drug reactions of both COVID-19 monoclonal therapies. These medication orders were selected by default in the order set to ensure that all patients received premedications aimed at minimizing the risk of hypersensitivity reaction, and had as-needed medication orders, in the event a hypersensitivity reaction occurred. Reducing hypersensitivity reaction risk is important as well to increase the likelihood that the patient would receive full therapy, as management of this adverse drug reactions involves possible cessation of therapy depending on the level of severity. The pharmacy department also ensured these medications were stocked in ED automated dispensing cabinets to promote quick access. In addition to the aforementioned nursing orders, we added EUA criteria for use and hyperlinks to the Fact Sheets for Patients and Caregivers and Health Care Providers for each monoclonal therapy, and restricted ordering to ED physicians, nurse practitioners, and physician assistants.

COVID-19 monoclonal antibody order set

The order set underwent multidisciplinary review by pharmacy administration, the chair of emergency medicine, physicians, and ED nursing leadership prior to presentation and approval by the Pharmacy and Therapeutics Committee. Lastly, at time of implementation, the order set was added to the ED preference list, preventing inpatient access. Additionally, as a patient safety action, free- standing orders of COVID-19 monoclonal therapies were disabled, so providers could only order therapies via the approved, comprehensive order set.

Preliminary Assessment Tool. A provider assessment tool was developed to document patient-specific EUA criteria for use during initial assessment (Figure 4). This tool serves as a checklist and is visible to the full multidisciplinary team in the patient’s EHR. It is used as a resource at the time of pharmacist verification and ED physician assessment to ensure criteria for use are met.

Workflow for COVID-19 monoclonal antibody infusion

 

 

Outpatient Offices

Patient Referral. Patients with symptoms or concerns of COVID-19 exposure can make physician appointments via telemedicine or in person at Mount Sinai Medical Center’s primary care and specialty offices. At the time of patient encounter, physicians suspecting a COVID-19 diagnosis will refer patients for outpatient COVID-19 polymerase chain reaction (PCR) laboratory testing, which has an approximate 24-hour turnaround to results. Physicians also assess whether the patient meets EUA criteria for use, pending results of testing. In the event a patient meets EUA criteria for use, the physician provides patient counseling and requests verbal consent. Following this, the physician enters a note in the EHR describing the patient’s condition, criteria for use evaluation, and the patient’s verbal agreement to therapy. This preliminary screening is beneficial to begin planning with both the patient and ED to minimize delays. Patients are notified of the results of their test once available. If the COVID-19 PCR test returns positive, the physician will call the ED at the main campus and schedule the patient for COVID-19 monoclonal therapy. As the desired timeframe for administering COVID-19 monoclonal therapies is within less than 10 days of symptom onset, timely scheduling of appointments is crucial. Infusion appointments are typically provided the same or next day. The patients are informed that they must bring documentation of their positive COVID-19 PCR test to their ED visit. Lastly, because patients are pretreated with medication that may potentially impair driving, they are instructed that they cannot drive themselves home; ride shares also are not allowed in order to limit the spread of infection.

Emergency Department

Patient Arrival and Screening. A COVID-19 patient can be evaluated in the ED 1 of 2 ways. The first option is via outpatient office referral, as described previously. Upon arrival to the ED, a second screening is performed to ensure the patient still meets EUA criteria for use and the positive COVID-19 PCR test result is confirmed. If the patient no longer meets criteria, the patient is triaged accordingly, including evaluation for higher-level care (eg, supplemental oxygen, hospital admission). The second optoion is via new patient walk-ins without outpatient physician referral (Figure 4). In these cases, an initial screening is performed, documenting EUA criteria for use in the preliminary assessment (Figure 5). Physicians will consider an outside COVID-19 test as valid, so long as documentation is readily available confirming a positive PCR result. Otherwise, an in-house COVID-19 PCR test will be performed, which has a 2-hour turnaround time.

Electronic health record preliminary assessment

Infusion Schedule. The ED offers a total of 16 COVID-19 monoclonal infusions slots daily. These are broken up into 4 infusion time blocks (eg, 8 am, 12 pm, 4 pm, 8 pm), with each infusion time block consisting of 4 available patient appointments. A list of scheduled infusions for the day is emailed to the pharmacy department every morning, and patients are instructed to arrive 1 hour prior to their appointment time. This allows time for patient registration, assessment, and pharmacy notification in advance of order entry. For logistical purposes, and as a patient safety initiative to reduce the likelihood of medication errors, each of the available COVID-19 monoclonal antibodies is offered on a designated day. Bamlanivimab is offered on Tuesday, Thursday, Saturday, and Sunday, while casirivimab/imdevimab is offered Monday, Wednesday, and Friday. This provides flexibility to adjust should supply deviate based on Department of Health allocation or should new therapy options within this class of medication become available.

Patient Education. Prior to administration of the monoclonal therapy, physician and nursing staff obtain a formal, written patient consent for therapy and provide patients with the option of participating in the institutional review board (IRB) approved study. Details of this are discussed in the risk management and IRB sections of the article. Nursing staff also provides the medication-specific Fact Sheet for Patients and Caregivers in either Spanish or English, which is also included as a hyperlink on the COVID-19 Monoclonal Antibody Order Set for ease of access. Interpreter services are available for patients who speak other languages. An ED decentralized pharmacist is also available onsite Monday through Friday from 12 pm to 8:30 pm to supplement education and serve as a resource for any questions.

Infusion Ordering. Once the patient is ready to begin therapy, the he/she is brought to a dedicated overflow area of the ED. There are few, if any, patients in this location, and it is adjacent to the main emergency center for easy access by the patients, nurses, pharmacists, and physicians. The physician then enters orders in the EHR using the COVID-19 Monoclonal Antibody Order Set (Figure 3). Three discrete questions were built into the medication order: (1) Was patient consent obtained? (2) Was the Fact Sheet for Patient/Caregiver provided to the patient? (3) Is the patient COVID-19 PCR-positive? These questions were built as hard stops so that the medication orders cannot be placed without a response. This serves as another double-check to ensure processes are followed and helps facilitate timely verification by the pharmacist.

 

 

Medication Administration. One nurse is dedicated to administering the monoclonal therapies scheduled at 8 am and 12 pm and another at 4 pm and 8 pm. Each appointment block is 4 hours in duration to allow adequate time for patient registration, infusion, and postinfusion observation. The nurse administers the premedications and COVID-19 monoclonal therapy, and observes the patient for the required 1-hour postadministration observation period. Nursing orders detailing monitoring parameters for mild, moderate, and severe reactions, along with associated medication orders to administer in the event they occur, are detailed in the nursing orders of the COVID-19 Monoclonal Antibody Order Set (Figure 3). Prior to administration, the nurse scans each medication and the patient’s wrist identification band, and documents the time of administration within the EHR medication administration report.

Pharmacy Department

Medication Receipt Process. Inventory is currently allocated biweekly from the state department of health and will soon be transitioning to a direct order system. The pharmacy technician in charge of deliveries notifies the pharmacy Antimicrobial Stewardship Program (ASP) clinical coordinator upon receipt of the monoclonal therapies. Bamlanivimab is supplied as 1 vial per dose, whereas casirivimab/imdevimab is supplied as 4 vials or 8 vials per dose, depending how it is shipped. To reduce the likelihood of medication errors, the ASP clinical coordinator assembles each of the casirivimab/imdevimab vials into kits, where 1 kit equals 1 dose. Labels are then affixed to each kit indicating the medication name, number of vials which equal a full dose, and pharmacist signature. The kits are stored in a dedicated refrigerator, and inventory logs are affixed to the outside of the refrigerator and updated daily. This inventory is also communicated daily to ED physician, nursing, and pharmacy leadership, as well as the director of patient safety, who reports weekly usage to the state Department of Health and Human Services. These weekly reports are used to determine allocation amounts.

Medication Verification and Delivery. The Mount Sinai Medical Center pharmacist staffing model consists of centralized order entry and specialized, decentralized positions. All orders are verified by the ED pharmacist when scheduled (not a 24/7 service) and by the designated pharmacist for all other times. At the time of medication verification, the pharmacist documents patient-specific EUA criteria for use and confirms that consent was obtained and the Fact Sheet for Patients/Caregivers was provided. A pharmacist intervention was developed to assist with this documentation. Pharmacists input smart text “.COVIDmonoclonal” and a drop-down menu of EUA criteria for use appears. The pharmacist reviews the patient care notes and medication order question responses to ascertain this information, contacting the ED prescriber if further clarification is required. This verification serves as another check to ensure processes put in place are followed. Lastly, intravenous preparation and delivery are electronically recorded in the EHR, and the medications require nursing signature at the time of delivery to ensure a formal chain of custody.

Risk Management

At Mount Sinai Medical Center, all EUA and investigational therapies require patient consent. Consistent with this requirement, a COVID-19 monoclonal specific consent was developed by risk management. This is provided to every patient receiving a COVID-19 monoclonal infusion, in addition to the FDA EUA Fact Sheet for Patients and Caregivers, and documented as part of their EHR. The questions providers must answer are built into the order set to ensure this process is followed and these patient safety checks are incorporated into the workflow.

Billing and Finance Department

In alignment with Mount Sinai Medical Center’s mission to provide high-quality health care to its diverse community through teaching, research, charity care, and financial responsibility, it was determined that this therapy would be provided to all patients regardless of insurance type, including those who are uninsured. The billing and finance department was consulted prior to this service being offered, to provide patients with accurate and pertinent information. The billing and finance department provided guidance on how to document patient encounters at time of registration to facilitate appropriate billing. At this time, the medication is free of charge, but nonmedication-related ED fees apply. This is explained to patients so there is a clear understanding prior to booking their appointment.

 

 

Infection Prevention

As patients receiving COVID-19 monoclonal therapies can transmit the virus to others, measures to ensure protection for other patients and staff are vital. To minimize exposure, specific nursing and physician staff from the ED are assigned to the treatment of these patients, and patients receive infusions and postobservation monitoring in a designated wing of the ED. Additionally, all staff who interact with these patients are required to don full personal protective equipment. This includes not only physicians and nurses but all specialties such as physician assistants, nurse practitioners, pharmacists, and laboratory technicians. Moreover, patients are not permitted to go home in a ride share and are counseled on Centers for Disease Control and Prevention quarantining following infusion.

Measurement of Process and Outcomes and Reporting

IRB approval was sought and obtained early during initiation of this service, allowing study consent to be offered to patients at the time general consent was obtained, which maximized patient recruitment and streamlined workflow. The study is a prospective observational research study to determine the impact of administration of COVID-19 monoclonal antibody therapy on length of symptoms, chronic illness, and rate of hospitalization. Most patients were eager to participate and offer their assistance to the scientific community during this pandemic.

Staff Education

In order to successfully implement this multidisciplinary EUA treatment option, comprehensive staff education was paramount after the workflow was developed. Prior to the first day of infusions, nurses and pharmacists were provided education during multiple huddle announcements. The pharmacy team also provided screen captures via email to the pharmacists so they could become familiar with the order set, intervention documentation, and location of the preliminary assessment of EUA criteria for use at the time of order verification. The emergency medicine department chair and chief medical officer also provided education via several virtual meetings and email to referring physicians (specialists and primary care) and residents in the emergency centers involved in COVID-19 monoclonal therapy-related patient care.

Factors Contributing to Success

We believe the reasons for continued success of this process are multifactorial and include the following key elements. Multidisciplinary planning, which included decision makers and all stakeholders, began at the time the idea was conceived. This allowed quick implementation of this service by efficiently navigating barriers to engaging impacted staff early on. Throughout this process, the authors set realistic step-wise goals. While navigating through the many details to implementation described, we also kept in mind the big picture, which was to provide this potentially lifesaving therapy to as many qualifying members of our community as possible. This included being flexible with the process and adapting when needed to achieve this ultimate goal. A focus on safety remained a priority to minimize possible errors and enhance patient and staff satisfaction. The optimization of the EHR streamlined workflow, provided point-of-care resources, and enhanced patient safety. Additionally, the target date set for implementation allowed staff and department leads adequate time to plan for and anticipate the changes. Serving only 1 patient on the first day allowed time for staff to experience this new process hands-on and provided opportunity for focused education. This team communication was essential to implementing this project, including staff training of processes and procedures prior to go-live. Early incorporation of IRB approval allowed the experience to be assessed and considered for contribution to the scientific literature to tackle this novel virus that has impacted our communities locally, nationally, and abroad. Moreover, continued measurement and reporting on a regular basis leads to performance improvement. The process outlined here can be adapted to incorporate other new therapies in the future, such as the recent February 9, 2021, EUA of the COVID-19 monoclonal antibody combination bamlanivimab and etesevimab.10

Conclusion

We administered 790 COVID-19 monoclonal antibody infusions between November 20, 2020 and March 5, 2021. Steps to minimize the likelihood of hypersensitivity reactions were implemented, and a low incidence (< 1%) has been observed. There has been no incidence of infection, concern from staff about infection prevention, or risk of infection during the processes. There have been very infrequent cost-related concerns raised by patients, typically due to incomplete communication regarding billing prior to the infusion. To address these issues, staff education has been provided to enhance patient instruction on this topic. The program has provided patient and family satisfaction, as well nursing, physician, pharmacist, clinical staff, and hospital administration pride and gratification. Setting up a new program to provide a 4-hour patient encounter to infuse therapy to high-risk patients with COVID-19 requires commitment and effort. This article describes the experience, ideas, and formula others may consider using to set up such a program. Through networking and formal phone calls and meetings about monoclonal antibody therapy, we have heard about other institutions who have not been able to institute this program due to various barriers to implementation. We hope our experience serves as a resource for others to provide this therapy to their patients and expand access in an effort to mitigate COVID-19 consequences and cases affecting our communities.

Corresponding author: Kathleen Jodoin, PharmD, BCPS, Mount Sinai Medical Center, 4300 Alton Rd, Miami Beach, FL 33140; kathleen.jodoin@msmc.com.

Financial disclosures: None.

References

1. COVID Data Tracker. Center for Disease Control and Prevention. https://covid.cdc.gov/covid-data-tracker/#global-counts-rates. Accessed March 12, 2021.

2. Fact Sheet for Health Care Providers Emergency Use Authorization (EUA) of Bamlanivimab. US Food and Drug Administration. Updated February 2021. Accessed March 9, 2021. https://www.fda.gov/media/143603/download

3. Coronavirus (COVID-19) Update: FDA Authorizes Monoclonal Antibodies for Treatment of COVID-19 | FDA. https://www.fda.gov/news-events/press-announcements/coronavirus-covid-19-update-fda-authorizes-monoclonal-antibodies-treatment-covid-19. Accessed February 14, 2021.

4. Fact Sheet for Health Care Providers Emergency Use Authorization (EUA) of Casirivimab and Imdevimab. US Food and Drug Administration. Updated December 2020. Accessed March 9, 2021. https://www.fda.gov/media/143892/download

5. Chen P, Nirula A, Heller B, et al. SARS-CoV-2 Neutralizing antibody LY-CoV555 in outpatients with COVID-19. N Engl J Med. 2021;384(3):229-237. doi:10.1056/NEJMoa2029849

6. Gottlieb RL, Nirula A, Chen P, et al. Effect of bamlanivimab as monotherapy or in combination with etesevimab on viral load in patients with mild to moderate COVID-19: a randomized clinical trial. 10.1JAMA. 2021;325(7):632-644. doi:10.1001/jama.2021.0202

7. Weinreich DM, Sivapalasingam S, Norton T, et al. REGN-COV2, a neutralizing antibody cocktail, in outpatients with COVID-19. 10.1N Engl J Med. 2021;384:238-251. doi:10.1056/nejmoa2035002

8. Mulangu S, Dodd LE, Davey RT Jr, et al. A randomized, controlled trial of Ebola virus disease therapeutics. 10.1N Engl J Med. 2019;381:2293-2303. doi:10.1056/NEJMoa1910993

9. Boyle, P. Can an experimental treatment keep COVID-19 patients out of hospitals? Association of American Medical Colleges. January 29, 2021. Accessed March 9, 2021. https://www.aamc.org/news-insights/can-experimental-treatment-keep-covid-19-patients-out-hospitals

10. Fact Sheet for Health Care Providers Emergency Use Authorization (EUA) of Bamlanivimab and Etesevimab. US Food and Drug Administration. Updated February 2021. Accessed March 9, 2021. https://www.fda.gov/media/145802/download

References

1. COVID Data Tracker. Center for Disease Control and Prevention. https://covid.cdc.gov/covid-data-tracker/#global-counts-rates. Accessed March 12, 2021.

2. Fact Sheet for Health Care Providers Emergency Use Authorization (EUA) of Bamlanivimab. US Food and Drug Administration. Updated February 2021. Accessed March 9, 2021. https://www.fda.gov/media/143603/download

3. Coronavirus (COVID-19) Update: FDA Authorizes Monoclonal Antibodies for Treatment of COVID-19 | FDA. https://www.fda.gov/news-events/press-announcements/coronavirus-covid-19-update-fda-authorizes-monoclonal-antibodies-treatment-covid-19. Accessed February 14, 2021.

4. Fact Sheet for Health Care Providers Emergency Use Authorization (EUA) of Casirivimab and Imdevimab. US Food and Drug Administration. Updated December 2020. Accessed March 9, 2021. https://www.fda.gov/media/143892/download

5. Chen P, Nirula A, Heller B, et al. SARS-CoV-2 Neutralizing antibody LY-CoV555 in outpatients with COVID-19. N Engl J Med. 2021;384(3):229-237. doi:10.1056/NEJMoa2029849

6. Gottlieb RL, Nirula A, Chen P, et al. Effect of bamlanivimab as monotherapy or in combination with etesevimab on viral load in patients with mild to moderate COVID-19: a randomized clinical trial. 10.1JAMA. 2021;325(7):632-644. doi:10.1001/jama.2021.0202

7. Weinreich DM, Sivapalasingam S, Norton T, et al. REGN-COV2, a neutralizing antibody cocktail, in outpatients with COVID-19. 10.1N Engl J Med. 2021;384:238-251. doi:10.1056/nejmoa2035002

8. Mulangu S, Dodd LE, Davey RT Jr, et al. A randomized, controlled trial of Ebola virus disease therapeutics. 10.1N Engl J Med. 2019;381:2293-2303. doi:10.1056/NEJMoa1910993

9. Boyle, P. Can an experimental treatment keep COVID-19 patients out of hospitals? Association of American Medical Colleges. January 29, 2021. Accessed March 9, 2021. https://www.aamc.org/news-insights/can-experimental-treatment-keep-covid-19-patients-out-hospitals

10. Fact Sheet for Health Care Providers Emergency Use Authorization (EUA) of Bamlanivimab and Etesevimab. US Food and Drug Administration. Updated February 2021. Accessed March 9, 2021. https://www.fda.gov/media/145802/download

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Use of Fecal Immunochemical Testing in Acute Patient Care in a Safety Net Hospital System

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Use of Fecal Immunochemical Testing in Acute Patient Care in a Safety Net Hospital System

From Baylor College of Medicine, Houston, TX (Drs. Spezia-Lindner, Montealegre, Muldrew, and Suarez) and Harris Health System, Houston, TX (Shanna L. Harris, Maria Daheri, and Drs. Muldrew and Suarez).

Abstract

Objective: To characterize and analyze the prevalence, indications for, and outcomes of fecal immunochemical testing (FIT) in acute patient care within a safety net health care system’s emergency departments (EDs) and inpatient settings.

Design: Retrospective cohort study derived from administrative data.

Setting: A large, urban, safety net health care delivery system in Texas. The data gathered were from the health care system’s 2 primary hospitals and their associated EDs. This health care system utilizes FIT exclusively for fecal occult blood testing.

Participants: Adults ≥18 years who underwent FIT in the ED or inpatient setting between August 2016 and March 2017. Chart review abstractions were performed on a sample (n = 382) from the larger subset.

Measurements: Primary data points included total FITs performed in acute patient care during the study period, basic demographic data, FIT indications, FIT result, receipt of invasive diagnostic follow-up, and result of invasive diagnostic follow-up. Multivariable log-binomial regression was used to calculate risk ratios (RRs) to assess the association between FIT result and receipt of diagnostic follow-up. Chi-square analysis was used to compare the proportion of abnormal findings on diagnostic follow-up by FIT result.

Results: During the 8-month study period, 2718 FITs were performed in the ED and inpatient setting, comprising 5.7% of system-wide FITs. Of the 382 patients included in the chart review who underwent acute care FIT, a majority had their test performed in the ED (304, 79.6%), 133 of which were positive (34.8%). The most common indication for FIT was evidence of overt gastrointestinal (GI) bleed (207, 54.2%), followed by anemia (84, 22.0%). While a positive FIT result was significantly associated with obtaining a diagnostic exam in multivariate analysis (RR, 1.72; P < 0.001), having signs of overt GI bleeding was a stronger predictor of diagnostic follow-up (RR, 2.00; P = 0.003). Of patients who underwent FIT and received diagnostic follow-up (n = 110), 48.2% were FIT negative. These patients were just as likely to have an abnormal finding as FIT-positive patients (90.6% vs 91.2%; P = 0.86). Of the 382 patients in the study, 4 (1.0%) were subsequently diagnosed with colorectal cancer (CRC). Of those 4 patients, 1 (25%) was FIT positive.

Conclusion: FIT is being utilized in acute patient care outside of its established indication for CRC screening in asymptomatic, average-risk adults. Our study demonstrates that FIT is not useful in acute patient care.

Keywords: FOBT; FIT; fecal immunochemical testing; inpatient.

 

 

Colorectal cancer (CRC) is the second leading cause of cancer-related mortality in the United States. It is estimated that in 2020, 147,950 individuals will be diagnosed with invasive CRC and 53,200 will die from it.1 While the overall incidence has been declining for decades, it is rising in young adults.2–4 Screening using direct visualization procedures (colonoscopy and sigmoidoscopy) and stool-based tests has been demonstrated to improve detection of precancerous and early cancerous lesions, thereby reducing CRC mortality.5 However, screening rates in the United States are suboptimal, with only 68.8% of adults aged 50 to 75 years screened according to guidelines in 2018.6Stool-based testing is a well-established and validated screening measure for CRC in asymptomatic individuals at average risk. Its widespread use in this population has been shown to cost-effectively screen for CRC among adults 50 years of age and older.5,7 Presently, the 2 most commonly used stool-based assays in the US health care system are guaiac-based tests (guaiac fecal occult blood test [gFOBT], Hemoccult) and fecal immunochemical tests (FITs, immunochemical fecal occult blood test [iFOBT]). FITs, which rely on the detection of globin in stool, have increasingly replaced guaiac-based tests in many health care systems. The frequency of FIT use is growing, in part, due to its lack of restrictions relative to traditional guaiac-based methods. FITs require a single stool sample and are not affected by foods with peroxidase activity; also, the predictive value of their results is not skewed by medications that can cause clinically insignificant GI bleeding (GIB), such as aspirin.8 Moreover, there is a growing body of evidence that FIT has improved sensitivity and specificity over guaiac-based tests in the detection of CRC and advanced adenomas.9-12

Despite the exclusive validation of FOBTs for use in CRC screening, studies have demonstrated that they are commonly used for a multitude of additional indications in emergency department (ED) and inpatient settings, most aimed at detecting or confirming GI blood loss. This may lead to inappropriate patient management, including the receipt of unnecessary follow-up procedures, which can incur significant costs to the patient and the health system.13-19 These costs may be particularly burdensome in safety net health systems (ie, those that offer access to care regardless of the patient’s ability to pay), which serve a large proportion of socioeconomically disadvantaged individuals in the United States.20,21 To our knowledge, no published study to date has specifically investigated the role of FIT in acute patient management.

This study characterizes the use of FIT in acute patient care within a large, urban, safety net health care system. Through a retrospective review of administrative data and patient charts, we evaluated FIT use prevalence, indications, and patient outcomes in the ED and inpatient settings.

 

 

Methods

Setting

This study was conducted in a large, urban, county-based integrated delivery system in Houston, Texas, that provides health care services to one of the largest uninsured and underinsured populations in the country.22 The health system includes 2 main hospitals and more than 20 ambulatory care clinics. Within its ambulatory care clinics, the health system implements a population-based screening strategy using stool-based testing. All adults aged 50 years or older who are due for FIT are identified through the health-maintenance module of the electronic medical record (EMR) and offered a take-home FIT. The health system utilizes FIT exclusively (OC-Light S FIT, Polymedco, Cortlandt Manor, NY); no guaiac-based assays are available.

Design and Data Collection

We began by using administrative records to determine the proportion of FITs conducted health system-wide that were ordered and completed in the acute care setting over the study period (August 2016-March 2017). Specifically, we used aggregate quality metric reports, which quantify the number of FITs conducted at each health system clinic and hospital each month, to calculate the proportion of FITs done in the ED and inpatient hospital setting.

We then conducted a retrospective cohort study of 382 adult patients who received FIT in the EDs and inpatient wards in both of the health system’s hospitals over the study period. All data were collected by retrospective chart review in Epic (Madison, WI) EMRs. Sampling was performed by selecting the medical record numbers corresponding to the first 50 completed FITs chronologically each month over the 8-month period, with a total of 400 charts reviewed.

Data collected included basic patient demographics, location of FIT ordering (ED vs inpatient), primary service ordering FIT, FIT indication, FIT result, and receipt and results of invasive diagnostic follow-up. Demographics collected included age, biological sex, race (self-selected), and insurance coverage.

 

 

FIT indication was determined based on resident or attending physician notes. The history of present illness, physical exam, and assessment and plan section of notes were reviewed by the lead author for a specific statement of indication for FIT or for evidence of clinical presentation for which FIT could reasonably be ordered. Indications were iteratively reviewed and collapsed into 6 different categories: anemia, iron deficiency with or without anemia, overt GIB, suspected GIB/miscellaneous, non-bloody diarrhea, and no indication identified. Overt GIB was defined as reported or witnessed hematemesis, coffee-ground emesis, hematochezia, bright red blood per rectum, or melena irrespective of time frame (current or remote) or chronicity (acute, subacute, or chronic). In cases where signs of overt bleed were not witnessed by medical professionals, determination of conditions such as melena or coffee-ground emesis were made based on health care providers’ assessment of patient history as documented in his or her notes. Suspected GIB/miscellaneous was defined with the following parameters: any new drop in hemoglobin, abdominal pain, anorectal pain, non-bloody vomiting, hemoptysis, isolated rising blood urea nitrogen, or patient noticing blood on self, clothing, or in the commode without an identified source. Patients who were anemic and found to have iron deficiency on recent lab studies (within 6 months) were reflexively categorized into iron deficiency with or without anemia as opposed to the “anemia” category, which was comprised of any anemia without recent iron studies or non-iron deficient anemia. FIT result was determined by test result entry in Epic, with results either reading positive or negative.

Diagnostic follow-up, for our purposes, was defined as receipt of an invasive procedure or surgery, including esophagogastroduodenoscopy (EGD), colonoscopy, flexible sigmoidoscopy, diagnostic and/or therapeutic abdominal surgical intervention, or any combination of these. Results of diagnostic follow-up were coded as normal or abnormal. A normal result was determined if all procedures performed were listed as normal or as “no pathological findings” on the operative or endoscopic report. Any reported pathologic findings on the operative/endoscopic report were coded as abnormal.

Statistical Analysis

Proportions were used to describe demographic characteristics of patients who received a FIT in acute hospital settings. Bivariable tables and Chi-square tests were used to compare indications and outcomes for FIT-positive and FIT-negative patients. The association between receipt of an invasive diagnostic follow-up (outcome) and the results of an inpatient FIT (predictor) was assessed using multivariable log-binomial regression to calculate risk ratios (RRs) and corresponding 95% confidence intervals. Log-binomial regression was used over logistic regression given that adjusted odds ratios generated by logistic regression often overestimate the association between the risk factor and the outcome when the outcome is common,23 as in the case of diagnostic follow-up. The model was adjusted for variables selected a priori, specifically, age, gender, and FIT indication. Chi-square analysis was used to compare the proportion of abnormal findings on diagnostic follow-up by FIT result (negative vs positive).

Results

During the 8-month study period, there were 2718 FITs ordered and completed in the acute care setting, compared to 44,662 FITs ordered and completed in the outpatient setting (5.7% performed during acute care).

Among the 400 charts reviewed, 7 were excluded from the analysis because they were duplicates from the same patient, and 11 were excluded due to insufficient information in the patient’s medical record, resulting in 382 patients included in the analysis. Patient demographic characteristics are described in Table 1. Patients were predominantly Hispanic/Latino or Black/African American (51.0% and 32.5%, respectively), a majority had insurance through the county health system (50.5%), and most were male (58.1%). The average age of those receiving FIT was 52 years (standard deviation, 14.8 years), with 40.8% being under the age of 50. For a majority of patients, FIT was ordered in the ED by emergency medicine providers (79.8%). The remaining FITs were ordered by providers in 12 different inpatient departments. Of the FITs ordered, 35.1% were positive.

Demographics of Patients Receiving FIT in the Acute Hospital Setting

 

 

Indications for ordering FIT are listed in Table 2. The largest proportion of FITs were ordered for overt signs of GIB (54.2%), followed by anemia (22.0%), suspected GIB/miscellaneous reasons (12.3%), iron deficiency with or without anemia (7.6%), and non-bloody diarrhea (2.1%). In 1.8% of cases, no indication for FIT was found in the EMR. No FITs were ordered for the indication of CRC detection. Of these indication categories, overt GIB yielded the highest percentage of FIT positive results (44.0%), and non-bloody diarrhea yielded the lowest (0%).

Indications and Outcomes of FIT Testing

A total of 110 patients (28.7%) underwent FIT and received invasive diagnostic follow-up. Of these 110 patients, 57 (51.8%) underwent EGD (2 of whom had further surgical intervention), 21 (19.1%) underwent colonoscopy (1 of whom had further surgical intervention), 25 (22.7%) underwent dual EGD and colonoscopy, 1 (0.9%) underwent flexible sigmoidoscopy, and 6 (5.5%) directly underwent abdominal surgical intervention. There was a significantly higher rate of diagnostic follow-up for FIT-positive vs FIT-negative patients (42.9% vs 21.3%; P < 0.001). However, of the 110 patients who underwent subsequent diagnostic follow-up, 48.2% were FIT negative. FIT-negative patients who received diagnostic follow-up were just as likely to have an abnormal finding as FIT-positive patients (90.6% vs 91.2%; P = 0.86).

Of the 382 patients in the study, 4 were diagnosed with CRC through diagnostic follow-up (1.0%). Of those 4 patients, 1 was FIT positive.

The results of the multivariable analyses to evaluate predictors of diagnostic colonoscopy are described in Table 3. Variables in the final model were FITresult, age, and FIT indication. After adjusting for other variables in the model, receipt of diagnostic follow-up was significantly associated with having a positive FIT (adjusted RR, 1.72; P < 0.001) and an overt GIB as an indication (adjusted RR, 2.00; P < 0.01).

Predictors of Receipt of Diagnostic Follow-Up

Discussion

During the time frame of our study, 5.7% of all FITs ordered within our health system were ordered in the acute patient care setting at our hospitals. The most common indication was overt GIB, which was the indication for 54.2% of patients. Of note, none of the FITs ordered in the acute patient care setting were ordered for CRC screening. These findings support the evidence in the literature that stool-based screening tests, including FIT, are commonly used in US health care systems for diagnostic purposes and risk stratification in acute patient care to detect GIBs.13-18

 

 

Our data suggest that FIT was not a clinically useful test in determining a patient’s need for diagnostic follow-up. While having a positive FIT was significantly associated with obtaining a diagnostic exam in multivariate analysis (RR, 1.72), having signs of overt GI bleeding was a stronger predictor of diagnostic follow-up (RR, 2.00). This salient finding is evidence that a thorough clinical history and physical exam may more strongly predict whether a patient will undergo endoscopy or other follow-up than a FIT result. These findings support other studies in the literature that have called into question the utility of FOBTs in these acute settings.13-19 Under such circumstances, FOBTs have been shown to rarely influence patient management and thus represent an unnecessary expense.13–17 Additionally, in some cases, FOBT use in these settings may negatively affect patient outcomes. Such adverse effects include delaying treatment until results are returned or obfuscating indicated management with the results (eg, a patient with indications for colonoscopy not being referred due to a negative FOBT).13,14,17

We found that, for patients who subsequently went on to have diagnostic follow-up (most commonly endoscopy), there was no difference in the likelihood of FIT-positive and FIT-negative patients to have an abnormality discovered (91.2% vs 90.6%; P = 0.86). This analysis demonstrates no post-hoc support for FIT positivity as a predictor of presence of pathology in patients who were discriminately selected for diagnostic follow-up on clinical grounds by gastroenterologists and surgeons. It does, however, further support that clinical judgment about the need for diagnostic follow-up—irrespective of FIT result—has a very high yield for discovery of pathology in the acute setting.

There are multiple reasons why FOBTs, and specifically FIT, contribute little in management decisions for patients with suspected GI blood loss. Use of FIT raises concern for both false-negatives and false-positives when used outside of its indication. Regarding false- negatives, FIT is an unreliable test for detection of blood loss from the upper GI tract. As FITs utilize antibodies to detect the presence of globin, a byproduct of red blood cell breakdown, it is expected that FIT would fail to detect many cases of upper GI bleeding, as globin is broken down in the upper GI tract.24 This fact is part of what has made FIT a more effective CRC screening test than its guaiac-based counterparts—it has greater specificity for lower GI tract blood loss compared to tests relying on detection of heme.8 While guaiac-based assays like Hemoccult have also been shown to be poor tests in acute patient care, they may more frequently, though still unreliably, detect blood of upper GI origin. We believe that part of the ongoing use of FIT in patients with a suspected upper GIB may be from lack of understanding among providers on the mechanistic difference between gFOBTs and FITs, even though gFOBTs also yield highly unreliable results.

FIT does not have the same risk of false-positive results that guaiac-based tests have, which can yield positive results with extra-intestinal blood ingestion, aspirin, or alcohol use; insignificant GI bleeding; and consumption of peroxidase-containing foods.13,17,25 However, from a clinical standpoint, there are several scenarios of insignificant bleeding that would yield a positive FIT result, such as hemorrhoids, which are common in the US population.26,27 Additionally, in the ED, where most FITs were performed in our study, it is possible that samples for FITs are being obtained via digital rectal exam (DRE) given patients’ acuity of medical conditions and time constraints. However, FIT has been validated when using a formed stool sample. Obtaining FIT via DRE may lead to microtrauma to the rectum, which could hypothetically yield a positive FIT.

Strengths of this study include its use of in-depth chart data on a large number of FIT-positive patients, which allowed us to discern indications, outcomes, and other clinical data that may have influenced clinical decision-making. Additionally, whereas other studies that address FOBT use in acute patient care have focused on guaiac-based assays, our findings regarding the lack of utility of FIT are novel and have particular relevance as FITs continue to grow in popularity. Nonetheless, there are certain limitations future research should seek to address. In this study, the diagnostic follow-up result was coded by presence or absence of pathologic findings but did not qualify findings by severity or attempt to determine whether the pathology noted on diagnostic follow-up was the definitive source of the suspected GI bleed. These variables could help determine whether there was a difference in severity of bleeding between FIT-positive and FIT-negative patients and could potentially be studied with a prospective research design. Our own study was not designed to address the question of whether FIT result informs patient management decisions. To answer this directly, interviews would have to be conducted with those making the follow-up decision (ie, endoscopists and surgeons). Additionally, this study was not adequately powered to make determinations on the efficacy of FIT in the acute care setting for detection of CRC. As mentioned, only 1 of the 4 patients (25%) who went on to be diagnosed with CRC on follow-up was initially FIT-positive. This would require further investigation.

 

 

Conclusion

FIT is being utilized for diagnostic purposes in the acute care of symptomatic patients, which is a misuse of an established screening test for CRC. While our study was not designed to answer whether and how often a FIT result informs subsequent patient management, our results indicate that FIT is an ineffective diagnostic and risk-stratification tool when used in the acute care setting. Our findings add to existing evidence that indicates FOBTs should not be used in acute patient care.

Taken as a whole, the results of our study add to a growing body of evidence demonstrating no role for FOBTs, and specifically FIT, in acute patient care. In light of this evidence, some health care systems have already demonstrated success with system-wide disinvestment from the test in acute patient care settings, with one group publishing about their disinvestment process.28 After completion of our study, our preliminary data were presented to leadership from the internal medicine, emergency medicine, and laboratory divisions within our health care delivery system to galvanize complete disinvestment of FIT from acute care at our hospitals, a policy that was put into effect in July 2019.

Corresponding author: Nathaniel J. Spezia-Lindner, MD, Baylor College of Medicine, 7200 Cambridge St, BCM 903, Ste A10.197, Houston, TX 77030; speziali@bcm.edu.

Financial disclosures: None.

Funding: Cancer Prevention and Research Institute of Texas, CPRIT (PP170094, PDs: ML Jibaja-Weiss and JR Montealegre).

References

1. Siegel RL, Miller KD, Jemal A. Cancer statistics, 2020. 10.1CA Cancer 10.1J Clin. 2020;70(1):7-30.

2. Howlader NN, Noone AM, Krapcho M, et al. SEER cancer statistics review, 1975-2014. National Cancer Institute; 2017:1-2.

3. Siegel RL, Fedewa SA, Anderson WF, et al. Colorectal cancer incidence patterns in the United States, 1974–2013. 10.1J Natl Cancer Inst. 2017;109(8):djw322.

4. Bailey CE, Hu CY, You YN, et al. Increasing disparities in the age-related incidences of colon and rectal cancers in the United States, 1975-2010. 10.25JAMA Surg. 2015;150(1):17-22.

5. Lin JS, Piper MA, Perdue LA, et al. Screening for colorectal cancer: updated evidence report and systematic review for the US Preventive Services Task Force. 10.25JAMA. 2016;315(23):2576-2594.

6. Centers for Disease Control and Prevention (CDC). Use of colorectal cancer screening tests. Behavioral Risk Factor Surveillance System. October 22, 2019. Accessed February 10, 2021. https://www.cdc.gov/cancer/colorectal/statistics/use-screening-tests-BRFSS.htm

7. Hewitson P, Glasziou PP, Irwig L, et al. Screening for colorectal cancer using the fecal occult blood test, Hemoccult. 10.25Cochrane Database Syst Rev. 2007;2007(1):CD001216.

8. Bujanda L, Lanas Á, Quintero E, et al. Effect of aspirin and antiplatelet drugs on the outcome of the fecal immunochemical test. 10.25Mayo Clin Proc. 2013;88(7):683-689.

9. Allison JE, Sakoda LC, Levin TR, et al. Screening for colorectal neoplasms with new fecal occult blood tests: update on performance characteristics. 10.25J Natl Cancer Inst. 2007;99(19):1462-1470.

10. Dancourt V, Lejeune C, Lepage C, et al. Immunochemical faecal occult blood tests are superior to guaiac-based tests for the detection of colorectal neoplasms. 10.25Eur J Cancer. 2008;44(15):2254-2258.

11. Hol L, Wilschut JA, van Ballegooijen M, et al. Screening for colorectal cancer: random comparison of guaiac and immunochemical faecal occult blood testing at different cut-off levels. 10.25Br J Cancer. 2009;100(7):1103-1110.

12. Levi Z, Birkenfeld S, Vilkin A, et al. A higher detection rate for colorectal cancer and advanced adenomatous polyp for screening with immunochemical fecal occult blood test than guaiac fecal occult blood test, despite lower compliance rate. A prospective, controlled, feasibility study. Int J Cancer. 2011;128(10):2415-2424.

13. Friedman A, Chan A, Chin LC, et al. Use and abuse of faecal occult blood tests in an acute hospital inpatient setting. Intern Med J. 2010;40(2):107-111.

14. Narula N, Ulic D, Al-Dabbagh R, et al. Fecal occult blood testing as a diagnostic test in symptomatic patients is not useful: a retrospective chart review. Can J Gastroenterol Hepatol. 2014;28(8):421-426.

15. Ip S, Sokoro AA, Kaita L, et al. Use of fecal occult blood testing in hospitalized patients: results of an audit. Can J Gastroenterol Hepatol. 2014;28(9):489-494.

16. Mosadeghi S, Ren H, Catungal J, et al. Utilization of fecal occult blood test in the acute hospital setting and its impact on clinical management and outcomes. J Postgrad Med. 2016;62(2):91-95.

17. van Rijn AF, Stroobants AK, Deutekom M, et al. Inappropriate use of the faecal occult blood test in a university hospital in the Netherlands. Eur J Gastroenterol Hepatol. 2012;24(11):1266-1269.

18. Sharma VK, Komanduri S, Nayyar S, et al. An audit of the utility of in-patient fecal occult blood testing. Am J Gastroenterol. 2001;96(4):1256-1260.

19. Chiang TH, Lee YC, Tu CH, et al. Performance of the immunochemical fecal occult blood test in predicting lesions in the lower gastrointestinal tract. CMAJ. 2011;183(13):1474-1481.

20. Chokshi DA, Chang JE, Wilson RM. Health reform and the changing safety net in the United States.  N Engl J Med. 2016;375(18):1790-1796.

21. Nguyen OK, Makam AN, Halm EA. National use of safety net clinics for primary care among adults with non-Medicaid insurance in the United States. PLoS One. 2016;11(3):e0151610.

22. United States Census Bureau. American Community Survey. Selected Economic Characteristics. 2019. Accessed February 20, 2021. https://data.census.gov/cedsci/table?q=ACSDP1Y2019.DP03%20Texas&g=0400000US48&tid=ACSDP1Y2019.DP03&hidePreview=true

23. McNutt LA, Wu C, Xue X, et al. Estimating the relative risk in cohort studies and clinical trials of common outcomes. Am J Epidemiol. 2003;157(10):940-943.

24. Rockey DC. Occult gastrointestinal bleeding. Gastroenterol Clin North Am. 2005;34(4):699-718.

25. Macrae FA, St John DJ. Relationship between patterns of bleeding and Hemoccult sensitivity in patients with colorectal cancers or adenomas. Gastroenterology. 1982;82(5 pt 1):891-898.

26. Johanson JF, Sonnenberg A. The prevalence of hemorrhoids and chronic constipation: an epidemiologic study. Gastroenterology. 1990;98(2):380-386.

27. Fleming JL, Ahlquist DA, McGill DB, et al. Influence of aspirin and ethanol on fecal blood levels as determined by using the HemoQuant assay. Mayo Clin Proc. 1987;62(3):159-163.

28. Gupta A, Tang Z, Agrawal D. Eliminating in-hospital fecal occult blood testing: our experience with disinvestment. Am J Med. 2018;131(7):760-763.

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From Baylor College of Medicine, Houston, TX (Drs. Spezia-Lindner, Montealegre, Muldrew, and Suarez) and Harris Health System, Houston, TX (Shanna L. Harris, Maria Daheri, and Drs. Muldrew and Suarez).

Abstract

Objective: To characterize and analyze the prevalence, indications for, and outcomes of fecal immunochemical testing (FIT) in acute patient care within a safety net health care system’s emergency departments (EDs) and inpatient settings.

Design: Retrospective cohort study derived from administrative data.

Setting: A large, urban, safety net health care delivery system in Texas. The data gathered were from the health care system’s 2 primary hospitals and their associated EDs. This health care system utilizes FIT exclusively for fecal occult blood testing.

Participants: Adults ≥18 years who underwent FIT in the ED or inpatient setting between August 2016 and March 2017. Chart review abstractions were performed on a sample (n = 382) from the larger subset.

Measurements: Primary data points included total FITs performed in acute patient care during the study period, basic demographic data, FIT indications, FIT result, receipt of invasive diagnostic follow-up, and result of invasive diagnostic follow-up. Multivariable log-binomial regression was used to calculate risk ratios (RRs) to assess the association between FIT result and receipt of diagnostic follow-up. Chi-square analysis was used to compare the proportion of abnormal findings on diagnostic follow-up by FIT result.

Results: During the 8-month study period, 2718 FITs were performed in the ED and inpatient setting, comprising 5.7% of system-wide FITs. Of the 382 patients included in the chart review who underwent acute care FIT, a majority had their test performed in the ED (304, 79.6%), 133 of which were positive (34.8%). The most common indication for FIT was evidence of overt gastrointestinal (GI) bleed (207, 54.2%), followed by anemia (84, 22.0%). While a positive FIT result was significantly associated with obtaining a diagnostic exam in multivariate analysis (RR, 1.72; P < 0.001), having signs of overt GI bleeding was a stronger predictor of diagnostic follow-up (RR, 2.00; P = 0.003). Of patients who underwent FIT and received diagnostic follow-up (n = 110), 48.2% were FIT negative. These patients were just as likely to have an abnormal finding as FIT-positive patients (90.6% vs 91.2%; P = 0.86). Of the 382 patients in the study, 4 (1.0%) were subsequently diagnosed with colorectal cancer (CRC). Of those 4 patients, 1 (25%) was FIT positive.

Conclusion: FIT is being utilized in acute patient care outside of its established indication for CRC screening in asymptomatic, average-risk adults. Our study demonstrates that FIT is not useful in acute patient care.

Keywords: FOBT; FIT; fecal immunochemical testing; inpatient.

 

 

Colorectal cancer (CRC) is the second leading cause of cancer-related mortality in the United States. It is estimated that in 2020, 147,950 individuals will be diagnosed with invasive CRC and 53,200 will die from it.1 While the overall incidence has been declining for decades, it is rising in young adults.2–4 Screening using direct visualization procedures (colonoscopy and sigmoidoscopy) and stool-based tests has been demonstrated to improve detection of precancerous and early cancerous lesions, thereby reducing CRC mortality.5 However, screening rates in the United States are suboptimal, with only 68.8% of adults aged 50 to 75 years screened according to guidelines in 2018.6Stool-based testing is a well-established and validated screening measure for CRC in asymptomatic individuals at average risk. Its widespread use in this population has been shown to cost-effectively screen for CRC among adults 50 years of age and older.5,7 Presently, the 2 most commonly used stool-based assays in the US health care system are guaiac-based tests (guaiac fecal occult blood test [gFOBT], Hemoccult) and fecal immunochemical tests (FITs, immunochemical fecal occult blood test [iFOBT]). FITs, which rely on the detection of globin in stool, have increasingly replaced guaiac-based tests in many health care systems. The frequency of FIT use is growing, in part, due to its lack of restrictions relative to traditional guaiac-based methods. FITs require a single stool sample and are not affected by foods with peroxidase activity; also, the predictive value of their results is not skewed by medications that can cause clinically insignificant GI bleeding (GIB), such as aspirin.8 Moreover, there is a growing body of evidence that FIT has improved sensitivity and specificity over guaiac-based tests in the detection of CRC and advanced adenomas.9-12

Despite the exclusive validation of FOBTs for use in CRC screening, studies have demonstrated that they are commonly used for a multitude of additional indications in emergency department (ED) and inpatient settings, most aimed at detecting or confirming GI blood loss. This may lead to inappropriate patient management, including the receipt of unnecessary follow-up procedures, which can incur significant costs to the patient and the health system.13-19 These costs may be particularly burdensome in safety net health systems (ie, those that offer access to care regardless of the patient’s ability to pay), which serve a large proportion of socioeconomically disadvantaged individuals in the United States.20,21 To our knowledge, no published study to date has specifically investigated the role of FIT in acute patient management.

This study characterizes the use of FIT in acute patient care within a large, urban, safety net health care system. Through a retrospective review of administrative data and patient charts, we evaluated FIT use prevalence, indications, and patient outcomes in the ED and inpatient settings.

 

 

Methods

Setting

This study was conducted in a large, urban, county-based integrated delivery system in Houston, Texas, that provides health care services to one of the largest uninsured and underinsured populations in the country.22 The health system includes 2 main hospitals and more than 20 ambulatory care clinics. Within its ambulatory care clinics, the health system implements a population-based screening strategy using stool-based testing. All adults aged 50 years or older who are due for FIT are identified through the health-maintenance module of the electronic medical record (EMR) and offered a take-home FIT. The health system utilizes FIT exclusively (OC-Light S FIT, Polymedco, Cortlandt Manor, NY); no guaiac-based assays are available.

Design and Data Collection

We began by using administrative records to determine the proportion of FITs conducted health system-wide that were ordered and completed in the acute care setting over the study period (August 2016-March 2017). Specifically, we used aggregate quality metric reports, which quantify the number of FITs conducted at each health system clinic and hospital each month, to calculate the proportion of FITs done in the ED and inpatient hospital setting.

We then conducted a retrospective cohort study of 382 adult patients who received FIT in the EDs and inpatient wards in both of the health system’s hospitals over the study period. All data were collected by retrospective chart review in Epic (Madison, WI) EMRs. Sampling was performed by selecting the medical record numbers corresponding to the first 50 completed FITs chronologically each month over the 8-month period, with a total of 400 charts reviewed.

Data collected included basic patient demographics, location of FIT ordering (ED vs inpatient), primary service ordering FIT, FIT indication, FIT result, and receipt and results of invasive diagnostic follow-up. Demographics collected included age, biological sex, race (self-selected), and insurance coverage.

 

 

FIT indication was determined based on resident or attending physician notes. The history of present illness, physical exam, and assessment and plan section of notes were reviewed by the lead author for a specific statement of indication for FIT or for evidence of clinical presentation for which FIT could reasonably be ordered. Indications were iteratively reviewed and collapsed into 6 different categories: anemia, iron deficiency with or without anemia, overt GIB, suspected GIB/miscellaneous, non-bloody diarrhea, and no indication identified. Overt GIB was defined as reported or witnessed hematemesis, coffee-ground emesis, hematochezia, bright red blood per rectum, or melena irrespective of time frame (current or remote) or chronicity (acute, subacute, or chronic). In cases where signs of overt bleed were not witnessed by medical professionals, determination of conditions such as melena or coffee-ground emesis were made based on health care providers’ assessment of patient history as documented in his or her notes. Suspected GIB/miscellaneous was defined with the following parameters: any new drop in hemoglobin, abdominal pain, anorectal pain, non-bloody vomiting, hemoptysis, isolated rising blood urea nitrogen, or patient noticing blood on self, clothing, or in the commode without an identified source. Patients who were anemic and found to have iron deficiency on recent lab studies (within 6 months) were reflexively categorized into iron deficiency with or without anemia as opposed to the “anemia” category, which was comprised of any anemia without recent iron studies or non-iron deficient anemia. FIT result was determined by test result entry in Epic, with results either reading positive or negative.

Diagnostic follow-up, for our purposes, was defined as receipt of an invasive procedure or surgery, including esophagogastroduodenoscopy (EGD), colonoscopy, flexible sigmoidoscopy, diagnostic and/or therapeutic abdominal surgical intervention, or any combination of these. Results of diagnostic follow-up were coded as normal or abnormal. A normal result was determined if all procedures performed were listed as normal or as “no pathological findings” on the operative or endoscopic report. Any reported pathologic findings on the operative/endoscopic report were coded as abnormal.

Statistical Analysis

Proportions were used to describe demographic characteristics of patients who received a FIT in acute hospital settings. Bivariable tables and Chi-square tests were used to compare indications and outcomes for FIT-positive and FIT-negative patients. The association between receipt of an invasive diagnostic follow-up (outcome) and the results of an inpatient FIT (predictor) was assessed using multivariable log-binomial regression to calculate risk ratios (RRs) and corresponding 95% confidence intervals. Log-binomial regression was used over logistic regression given that adjusted odds ratios generated by logistic regression often overestimate the association between the risk factor and the outcome when the outcome is common,23 as in the case of diagnostic follow-up. The model was adjusted for variables selected a priori, specifically, age, gender, and FIT indication. Chi-square analysis was used to compare the proportion of abnormal findings on diagnostic follow-up by FIT result (negative vs positive).

Results

During the 8-month study period, there were 2718 FITs ordered and completed in the acute care setting, compared to 44,662 FITs ordered and completed in the outpatient setting (5.7% performed during acute care).

Among the 400 charts reviewed, 7 were excluded from the analysis because they were duplicates from the same patient, and 11 were excluded due to insufficient information in the patient’s medical record, resulting in 382 patients included in the analysis. Patient demographic characteristics are described in Table 1. Patients were predominantly Hispanic/Latino or Black/African American (51.0% and 32.5%, respectively), a majority had insurance through the county health system (50.5%), and most were male (58.1%). The average age of those receiving FIT was 52 years (standard deviation, 14.8 years), with 40.8% being under the age of 50. For a majority of patients, FIT was ordered in the ED by emergency medicine providers (79.8%). The remaining FITs were ordered by providers in 12 different inpatient departments. Of the FITs ordered, 35.1% were positive.

Demographics of Patients Receiving FIT in the Acute Hospital Setting

 

 

Indications for ordering FIT are listed in Table 2. The largest proportion of FITs were ordered for overt signs of GIB (54.2%), followed by anemia (22.0%), suspected GIB/miscellaneous reasons (12.3%), iron deficiency with or without anemia (7.6%), and non-bloody diarrhea (2.1%). In 1.8% of cases, no indication for FIT was found in the EMR. No FITs were ordered for the indication of CRC detection. Of these indication categories, overt GIB yielded the highest percentage of FIT positive results (44.0%), and non-bloody diarrhea yielded the lowest (0%).

Indications and Outcomes of FIT Testing

A total of 110 patients (28.7%) underwent FIT and received invasive diagnostic follow-up. Of these 110 patients, 57 (51.8%) underwent EGD (2 of whom had further surgical intervention), 21 (19.1%) underwent colonoscopy (1 of whom had further surgical intervention), 25 (22.7%) underwent dual EGD and colonoscopy, 1 (0.9%) underwent flexible sigmoidoscopy, and 6 (5.5%) directly underwent abdominal surgical intervention. There was a significantly higher rate of diagnostic follow-up for FIT-positive vs FIT-negative patients (42.9% vs 21.3%; P < 0.001). However, of the 110 patients who underwent subsequent diagnostic follow-up, 48.2% were FIT negative. FIT-negative patients who received diagnostic follow-up were just as likely to have an abnormal finding as FIT-positive patients (90.6% vs 91.2%; P = 0.86).

Of the 382 patients in the study, 4 were diagnosed with CRC through diagnostic follow-up (1.0%). Of those 4 patients, 1 was FIT positive.

The results of the multivariable analyses to evaluate predictors of diagnostic colonoscopy are described in Table 3. Variables in the final model were FITresult, age, and FIT indication. After adjusting for other variables in the model, receipt of diagnostic follow-up was significantly associated with having a positive FIT (adjusted RR, 1.72; P < 0.001) and an overt GIB as an indication (adjusted RR, 2.00; P < 0.01).

Predictors of Receipt of Diagnostic Follow-Up

Discussion

During the time frame of our study, 5.7% of all FITs ordered within our health system were ordered in the acute patient care setting at our hospitals. The most common indication was overt GIB, which was the indication for 54.2% of patients. Of note, none of the FITs ordered in the acute patient care setting were ordered for CRC screening. These findings support the evidence in the literature that stool-based screening tests, including FIT, are commonly used in US health care systems for diagnostic purposes and risk stratification in acute patient care to detect GIBs.13-18

 

 

Our data suggest that FIT was not a clinically useful test in determining a patient’s need for diagnostic follow-up. While having a positive FIT was significantly associated with obtaining a diagnostic exam in multivariate analysis (RR, 1.72), having signs of overt GI bleeding was a stronger predictor of diagnostic follow-up (RR, 2.00). This salient finding is evidence that a thorough clinical history and physical exam may more strongly predict whether a patient will undergo endoscopy or other follow-up than a FIT result. These findings support other studies in the literature that have called into question the utility of FOBTs in these acute settings.13-19 Under such circumstances, FOBTs have been shown to rarely influence patient management and thus represent an unnecessary expense.13–17 Additionally, in some cases, FOBT use in these settings may negatively affect patient outcomes. Such adverse effects include delaying treatment until results are returned or obfuscating indicated management with the results (eg, a patient with indications for colonoscopy not being referred due to a negative FOBT).13,14,17

We found that, for patients who subsequently went on to have diagnostic follow-up (most commonly endoscopy), there was no difference in the likelihood of FIT-positive and FIT-negative patients to have an abnormality discovered (91.2% vs 90.6%; P = 0.86). This analysis demonstrates no post-hoc support for FIT positivity as a predictor of presence of pathology in patients who were discriminately selected for diagnostic follow-up on clinical grounds by gastroenterologists and surgeons. It does, however, further support that clinical judgment about the need for diagnostic follow-up—irrespective of FIT result—has a very high yield for discovery of pathology in the acute setting.

There are multiple reasons why FOBTs, and specifically FIT, contribute little in management decisions for patients with suspected GI blood loss. Use of FIT raises concern for both false-negatives and false-positives when used outside of its indication. Regarding false- negatives, FIT is an unreliable test for detection of blood loss from the upper GI tract. As FITs utilize antibodies to detect the presence of globin, a byproduct of red blood cell breakdown, it is expected that FIT would fail to detect many cases of upper GI bleeding, as globin is broken down in the upper GI tract.24 This fact is part of what has made FIT a more effective CRC screening test than its guaiac-based counterparts—it has greater specificity for lower GI tract blood loss compared to tests relying on detection of heme.8 While guaiac-based assays like Hemoccult have also been shown to be poor tests in acute patient care, they may more frequently, though still unreliably, detect blood of upper GI origin. We believe that part of the ongoing use of FIT in patients with a suspected upper GIB may be from lack of understanding among providers on the mechanistic difference between gFOBTs and FITs, even though gFOBTs also yield highly unreliable results.

FIT does not have the same risk of false-positive results that guaiac-based tests have, which can yield positive results with extra-intestinal blood ingestion, aspirin, or alcohol use; insignificant GI bleeding; and consumption of peroxidase-containing foods.13,17,25 However, from a clinical standpoint, there are several scenarios of insignificant bleeding that would yield a positive FIT result, such as hemorrhoids, which are common in the US population.26,27 Additionally, in the ED, where most FITs were performed in our study, it is possible that samples for FITs are being obtained via digital rectal exam (DRE) given patients’ acuity of medical conditions and time constraints. However, FIT has been validated when using a formed stool sample. Obtaining FIT via DRE may lead to microtrauma to the rectum, which could hypothetically yield a positive FIT.

Strengths of this study include its use of in-depth chart data on a large number of FIT-positive patients, which allowed us to discern indications, outcomes, and other clinical data that may have influenced clinical decision-making. Additionally, whereas other studies that address FOBT use in acute patient care have focused on guaiac-based assays, our findings regarding the lack of utility of FIT are novel and have particular relevance as FITs continue to grow in popularity. Nonetheless, there are certain limitations future research should seek to address. In this study, the diagnostic follow-up result was coded by presence or absence of pathologic findings but did not qualify findings by severity or attempt to determine whether the pathology noted on diagnostic follow-up was the definitive source of the suspected GI bleed. These variables could help determine whether there was a difference in severity of bleeding between FIT-positive and FIT-negative patients and could potentially be studied with a prospective research design. Our own study was not designed to address the question of whether FIT result informs patient management decisions. To answer this directly, interviews would have to be conducted with those making the follow-up decision (ie, endoscopists and surgeons). Additionally, this study was not adequately powered to make determinations on the efficacy of FIT in the acute care setting for detection of CRC. As mentioned, only 1 of the 4 patients (25%) who went on to be diagnosed with CRC on follow-up was initially FIT-positive. This would require further investigation.

 

 

Conclusion

FIT is being utilized for diagnostic purposes in the acute care of symptomatic patients, which is a misuse of an established screening test for CRC. While our study was not designed to answer whether and how often a FIT result informs subsequent patient management, our results indicate that FIT is an ineffective diagnostic and risk-stratification tool when used in the acute care setting. Our findings add to existing evidence that indicates FOBTs should not be used in acute patient care.

Taken as a whole, the results of our study add to a growing body of evidence demonstrating no role for FOBTs, and specifically FIT, in acute patient care. In light of this evidence, some health care systems have already demonstrated success with system-wide disinvestment from the test in acute patient care settings, with one group publishing about their disinvestment process.28 After completion of our study, our preliminary data were presented to leadership from the internal medicine, emergency medicine, and laboratory divisions within our health care delivery system to galvanize complete disinvestment of FIT from acute care at our hospitals, a policy that was put into effect in July 2019.

Corresponding author: Nathaniel J. Spezia-Lindner, MD, Baylor College of Medicine, 7200 Cambridge St, BCM 903, Ste A10.197, Houston, TX 77030; speziali@bcm.edu.

Financial disclosures: None.

Funding: Cancer Prevention and Research Institute of Texas, CPRIT (PP170094, PDs: ML Jibaja-Weiss and JR Montealegre).

From Baylor College of Medicine, Houston, TX (Drs. Spezia-Lindner, Montealegre, Muldrew, and Suarez) and Harris Health System, Houston, TX (Shanna L. Harris, Maria Daheri, and Drs. Muldrew and Suarez).

Abstract

Objective: To characterize and analyze the prevalence, indications for, and outcomes of fecal immunochemical testing (FIT) in acute patient care within a safety net health care system’s emergency departments (EDs) and inpatient settings.

Design: Retrospective cohort study derived from administrative data.

Setting: A large, urban, safety net health care delivery system in Texas. The data gathered were from the health care system’s 2 primary hospitals and their associated EDs. This health care system utilizes FIT exclusively for fecal occult blood testing.

Participants: Adults ≥18 years who underwent FIT in the ED or inpatient setting between August 2016 and March 2017. Chart review abstractions were performed on a sample (n = 382) from the larger subset.

Measurements: Primary data points included total FITs performed in acute patient care during the study period, basic demographic data, FIT indications, FIT result, receipt of invasive diagnostic follow-up, and result of invasive diagnostic follow-up. Multivariable log-binomial regression was used to calculate risk ratios (RRs) to assess the association between FIT result and receipt of diagnostic follow-up. Chi-square analysis was used to compare the proportion of abnormal findings on diagnostic follow-up by FIT result.

Results: During the 8-month study period, 2718 FITs were performed in the ED and inpatient setting, comprising 5.7% of system-wide FITs. Of the 382 patients included in the chart review who underwent acute care FIT, a majority had their test performed in the ED (304, 79.6%), 133 of which were positive (34.8%). The most common indication for FIT was evidence of overt gastrointestinal (GI) bleed (207, 54.2%), followed by anemia (84, 22.0%). While a positive FIT result was significantly associated with obtaining a diagnostic exam in multivariate analysis (RR, 1.72; P < 0.001), having signs of overt GI bleeding was a stronger predictor of diagnostic follow-up (RR, 2.00; P = 0.003). Of patients who underwent FIT and received diagnostic follow-up (n = 110), 48.2% were FIT negative. These patients were just as likely to have an abnormal finding as FIT-positive patients (90.6% vs 91.2%; P = 0.86). Of the 382 patients in the study, 4 (1.0%) were subsequently diagnosed with colorectal cancer (CRC). Of those 4 patients, 1 (25%) was FIT positive.

Conclusion: FIT is being utilized in acute patient care outside of its established indication for CRC screening in asymptomatic, average-risk adults. Our study demonstrates that FIT is not useful in acute patient care.

Keywords: FOBT; FIT; fecal immunochemical testing; inpatient.

 

 

Colorectal cancer (CRC) is the second leading cause of cancer-related mortality in the United States. It is estimated that in 2020, 147,950 individuals will be diagnosed with invasive CRC and 53,200 will die from it.1 While the overall incidence has been declining for decades, it is rising in young adults.2–4 Screening using direct visualization procedures (colonoscopy and sigmoidoscopy) and stool-based tests has been demonstrated to improve detection of precancerous and early cancerous lesions, thereby reducing CRC mortality.5 However, screening rates in the United States are suboptimal, with only 68.8% of adults aged 50 to 75 years screened according to guidelines in 2018.6Stool-based testing is a well-established and validated screening measure for CRC in asymptomatic individuals at average risk. Its widespread use in this population has been shown to cost-effectively screen for CRC among adults 50 years of age and older.5,7 Presently, the 2 most commonly used stool-based assays in the US health care system are guaiac-based tests (guaiac fecal occult blood test [gFOBT], Hemoccult) and fecal immunochemical tests (FITs, immunochemical fecal occult blood test [iFOBT]). FITs, which rely on the detection of globin in stool, have increasingly replaced guaiac-based tests in many health care systems. The frequency of FIT use is growing, in part, due to its lack of restrictions relative to traditional guaiac-based methods. FITs require a single stool sample and are not affected by foods with peroxidase activity; also, the predictive value of their results is not skewed by medications that can cause clinically insignificant GI bleeding (GIB), such as aspirin.8 Moreover, there is a growing body of evidence that FIT has improved sensitivity and specificity over guaiac-based tests in the detection of CRC and advanced adenomas.9-12

Despite the exclusive validation of FOBTs for use in CRC screening, studies have demonstrated that they are commonly used for a multitude of additional indications in emergency department (ED) and inpatient settings, most aimed at detecting or confirming GI blood loss. This may lead to inappropriate patient management, including the receipt of unnecessary follow-up procedures, which can incur significant costs to the patient and the health system.13-19 These costs may be particularly burdensome in safety net health systems (ie, those that offer access to care regardless of the patient’s ability to pay), which serve a large proportion of socioeconomically disadvantaged individuals in the United States.20,21 To our knowledge, no published study to date has specifically investigated the role of FIT in acute patient management.

This study characterizes the use of FIT in acute patient care within a large, urban, safety net health care system. Through a retrospective review of administrative data and patient charts, we evaluated FIT use prevalence, indications, and patient outcomes in the ED and inpatient settings.

 

 

Methods

Setting

This study was conducted in a large, urban, county-based integrated delivery system in Houston, Texas, that provides health care services to one of the largest uninsured and underinsured populations in the country.22 The health system includes 2 main hospitals and more than 20 ambulatory care clinics. Within its ambulatory care clinics, the health system implements a population-based screening strategy using stool-based testing. All adults aged 50 years or older who are due for FIT are identified through the health-maintenance module of the electronic medical record (EMR) and offered a take-home FIT. The health system utilizes FIT exclusively (OC-Light S FIT, Polymedco, Cortlandt Manor, NY); no guaiac-based assays are available.

Design and Data Collection

We began by using administrative records to determine the proportion of FITs conducted health system-wide that were ordered and completed in the acute care setting over the study period (August 2016-March 2017). Specifically, we used aggregate quality metric reports, which quantify the number of FITs conducted at each health system clinic and hospital each month, to calculate the proportion of FITs done in the ED and inpatient hospital setting.

We then conducted a retrospective cohort study of 382 adult patients who received FIT in the EDs and inpatient wards in both of the health system’s hospitals over the study period. All data were collected by retrospective chart review in Epic (Madison, WI) EMRs. Sampling was performed by selecting the medical record numbers corresponding to the first 50 completed FITs chronologically each month over the 8-month period, with a total of 400 charts reviewed.

Data collected included basic patient demographics, location of FIT ordering (ED vs inpatient), primary service ordering FIT, FIT indication, FIT result, and receipt and results of invasive diagnostic follow-up. Demographics collected included age, biological sex, race (self-selected), and insurance coverage.

 

 

FIT indication was determined based on resident or attending physician notes. The history of present illness, physical exam, and assessment and plan section of notes were reviewed by the lead author for a specific statement of indication for FIT or for evidence of clinical presentation for which FIT could reasonably be ordered. Indications were iteratively reviewed and collapsed into 6 different categories: anemia, iron deficiency with or without anemia, overt GIB, suspected GIB/miscellaneous, non-bloody diarrhea, and no indication identified. Overt GIB was defined as reported or witnessed hematemesis, coffee-ground emesis, hematochezia, bright red blood per rectum, or melena irrespective of time frame (current or remote) or chronicity (acute, subacute, or chronic). In cases where signs of overt bleed were not witnessed by medical professionals, determination of conditions such as melena or coffee-ground emesis were made based on health care providers’ assessment of patient history as documented in his or her notes. Suspected GIB/miscellaneous was defined with the following parameters: any new drop in hemoglobin, abdominal pain, anorectal pain, non-bloody vomiting, hemoptysis, isolated rising blood urea nitrogen, or patient noticing blood on self, clothing, or in the commode without an identified source. Patients who were anemic and found to have iron deficiency on recent lab studies (within 6 months) were reflexively categorized into iron deficiency with or without anemia as opposed to the “anemia” category, which was comprised of any anemia without recent iron studies or non-iron deficient anemia. FIT result was determined by test result entry in Epic, with results either reading positive or negative.

Diagnostic follow-up, for our purposes, was defined as receipt of an invasive procedure or surgery, including esophagogastroduodenoscopy (EGD), colonoscopy, flexible sigmoidoscopy, diagnostic and/or therapeutic abdominal surgical intervention, or any combination of these. Results of diagnostic follow-up were coded as normal or abnormal. A normal result was determined if all procedures performed were listed as normal or as “no pathological findings” on the operative or endoscopic report. Any reported pathologic findings on the operative/endoscopic report were coded as abnormal.

Statistical Analysis

Proportions were used to describe demographic characteristics of patients who received a FIT in acute hospital settings. Bivariable tables and Chi-square tests were used to compare indications and outcomes for FIT-positive and FIT-negative patients. The association between receipt of an invasive diagnostic follow-up (outcome) and the results of an inpatient FIT (predictor) was assessed using multivariable log-binomial regression to calculate risk ratios (RRs) and corresponding 95% confidence intervals. Log-binomial regression was used over logistic regression given that adjusted odds ratios generated by logistic regression often overestimate the association between the risk factor and the outcome when the outcome is common,23 as in the case of diagnostic follow-up. The model was adjusted for variables selected a priori, specifically, age, gender, and FIT indication. Chi-square analysis was used to compare the proportion of abnormal findings on diagnostic follow-up by FIT result (negative vs positive).

Results

During the 8-month study period, there were 2718 FITs ordered and completed in the acute care setting, compared to 44,662 FITs ordered and completed in the outpatient setting (5.7% performed during acute care).

Among the 400 charts reviewed, 7 were excluded from the analysis because they were duplicates from the same patient, and 11 were excluded due to insufficient information in the patient’s medical record, resulting in 382 patients included in the analysis. Patient demographic characteristics are described in Table 1. Patients were predominantly Hispanic/Latino or Black/African American (51.0% and 32.5%, respectively), a majority had insurance through the county health system (50.5%), and most were male (58.1%). The average age of those receiving FIT was 52 years (standard deviation, 14.8 years), with 40.8% being under the age of 50. For a majority of patients, FIT was ordered in the ED by emergency medicine providers (79.8%). The remaining FITs were ordered by providers in 12 different inpatient departments. Of the FITs ordered, 35.1% were positive.

Demographics of Patients Receiving FIT in the Acute Hospital Setting

 

 

Indications for ordering FIT are listed in Table 2. The largest proportion of FITs were ordered for overt signs of GIB (54.2%), followed by anemia (22.0%), suspected GIB/miscellaneous reasons (12.3%), iron deficiency with or without anemia (7.6%), and non-bloody diarrhea (2.1%). In 1.8% of cases, no indication for FIT was found in the EMR. No FITs were ordered for the indication of CRC detection. Of these indication categories, overt GIB yielded the highest percentage of FIT positive results (44.0%), and non-bloody diarrhea yielded the lowest (0%).

Indications and Outcomes of FIT Testing

A total of 110 patients (28.7%) underwent FIT and received invasive diagnostic follow-up. Of these 110 patients, 57 (51.8%) underwent EGD (2 of whom had further surgical intervention), 21 (19.1%) underwent colonoscopy (1 of whom had further surgical intervention), 25 (22.7%) underwent dual EGD and colonoscopy, 1 (0.9%) underwent flexible sigmoidoscopy, and 6 (5.5%) directly underwent abdominal surgical intervention. There was a significantly higher rate of diagnostic follow-up for FIT-positive vs FIT-negative patients (42.9% vs 21.3%; P < 0.001). However, of the 110 patients who underwent subsequent diagnostic follow-up, 48.2% were FIT negative. FIT-negative patients who received diagnostic follow-up were just as likely to have an abnormal finding as FIT-positive patients (90.6% vs 91.2%; P = 0.86).

Of the 382 patients in the study, 4 were diagnosed with CRC through diagnostic follow-up (1.0%). Of those 4 patients, 1 was FIT positive.

The results of the multivariable analyses to evaluate predictors of diagnostic colonoscopy are described in Table 3. Variables in the final model were FITresult, age, and FIT indication. After adjusting for other variables in the model, receipt of diagnostic follow-up was significantly associated with having a positive FIT (adjusted RR, 1.72; P < 0.001) and an overt GIB as an indication (adjusted RR, 2.00; P < 0.01).

Predictors of Receipt of Diagnostic Follow-Up

Discussion

During the time frame of our study, 5.7% of all FITs ordered within our health system were ordered in the acute patient care setting at our hospitals. The most common indication was overt GIB, which was the indication for 54.2% of patients. Of note, none of the FITs ordered in the acute patient care setting were ordered for CRC screening. These findings support the evidence in the literature that stool-based screening tests, including FIT, are commonly used in US health care systems for diagnostic purposes and risk stratification in acute patient care to detect GIBs.13-18

 

 

Our data suggest that FIT was not a clinically useful test in determining a patient’s need for diagnostic follow-up. While having a positive FIT was significantly associated with obtaining a diagnostic exam in multivariate analysis (RR, 1.72), having signs of overt GI bleeding was a stronger predictor of diagnostic follow-up (RR, 2.00). This salient finding is evidence that a thorough clinical history and physical exam may more strongly predict whether a patient will undergo endoscopy or other follow-up than a FIT result. These findings support other studies in the literature that have called into question the utility of FOBTs in these acute settings.13-19 Under such circumstances, FOBTs have been shown to rarely influence patient management and thus represent an unnecessary expense.13–17 Additionally, in some cases, FOBT use in these settings may negatively affect patient outcomes. Such adverse effects include delaying treatment until results are returned or obfuscating indicated management with the results (eg, a patient with indications for colonoscopy not being referred due to a negative FOBT).13,14,17

We found that, for patients who subsequently went on to have diagnostic follow-up (most commonly endoscopy), there was no difference in the likelihood of FIT-positive and FIT-negative patients to have an abnormality discovered (91.2% vs 90.6%; P = 0.86). This analysis demonstrates no post-hoc support for FIT positivity as a predictor of presence of pathology in patients who were discriminately selected for diagnostic follow-up on clinical grounds by gastroenterologists and surgeons. It does, however, further support that clinical judgment about the need for diagnostic follow-up—irrespective of FIT result—has a very high yield for discovery of pathology in the acute setting.

There are multiple reasons why FOBTs, and specifically FIT, contribute little in management decisions for patients with suspected GI blood loss. Use of FIT raises concern for both false-negatives and false-positives when used outside of its indication. Regarding false- negatives, FIT is an unreliable test for detection of blood loss from the upper GI tract. As FITs utilize antibodies to detect the presence of globin, a byproduct of red blood cell breakdown, it is expected that FIT would fail to detect many cases of upper GI bleeding, as globin is broken down in the upper GI tract.24 This fact is part of what has made FIT a more effective CRC screening test than its guaiac-based counterparts—it has greater specificity for lower GI tract blood loss compared to tests relying on detection of heme.8 While guaiac-based assays like Hemoccult have also been shown to be poor tests in acute patient care, they may more frequently, though still unreliably, detect blood of upper GI origin. We believe that part of the ongoing use of FIT in patients with a suspected upper GIB may be from lack of understanding among providers on the mechanistic difference between gFOBTs and FITs, even though gFOBTs also yield highly unreliable results.

FIT does not have the same risk of false-positive results that guaiac-based tests have, which can yield positive results with extra-intestinal blood ingestion, aspirin, or alcohol use; insignificant GI bleeding; and consumption of peroxidase-containing foods.13,17,25 However, from a clinical standpoint, there are several scenarios of insignificant bleeding that would yield a positive FIT result, such as hemorrhoids, which are common in the US population.26,27 Additionally, in the ED, where most FITs were performed in our study, it is possible that samples for FITs are being obtained via digital rectal exam (DRE) given patients’ acuity of medical conditions and time constraints. However, FIT has been validated when using a formed stool sample. Obtaining FIT via DRE may lead to microtrauma to the rectum, which could hypothetically yield a positive FIT.

Strengths of this study include its use of in-depth chart data on a large number of FIT-positive patients, which allowed us to discern indications, outcomes, and other clinical data that may have influenced clinical decision-making. Additionally, whereas other studies that address FOBT use in acute patient care have focused on guaiac-based assays, our findings regarding the lack of utility of FIT are novel and have particular relevance as FITs continue to grow in popularity. Nonetheless, there are certain limitations future research should seek to address. In this study, the diagnostic follow-up result was coded by presence or absence of pathologic findings but did not qualify findings by severity or attempt to determine whether the pathology noted on diagnostic follow-up was the definitive source of the suspected GI bleed. These variables could help determine whether there was a difference in severity of bleeding between FIT-positive and FIT-negative patients and could potentially be studied with a prospective research design. Our own study was not designed to address the question of whether FIT result informs patient management decisions. To answer this directly, interviews would have to be conducted with those making the follow-up decision (ie, endoscopists and surgeons). Additionally, this study was not adequately powered to make determinations on the efficacy of FIT in the acute care setting for detection of CRC. As mentioned, only 1 of the 4 patients (25%) who went on to be diagnosed with CRC on follow-up was initially FIT-positive. This would require further investigation.

 

 

Conclusion

FIT is being utilized for diagnostic purposes in the acute care of symptomatic patients, which is a misuse of an established screening test for CRC. While our study was not designed to answer whether and how often a FIT result informs subsequent patient management, our results indicate that FIT is an ineffective diagnostic and risk-stratification tool when used in the acute care setting. Our findings add to existing evidence that indicates FOBTs should not be used in acute patient care.

Taken as a whole, the results of our study add to a growing body of evidence demonstrating no role for FOBTs, and specifically FIT, in acute patient care. In light of this evidence, some health care systems have already demonstrated success with system-wide disinvestment from the test in acute patient care settings, with one group publishing about their disinvestment process.28 After completion of our study, our preliminary data were presented to leadership from the internal medicine, emergency medicine, and laboratory divisions within our health care delivery system to galvanize complete disinvestment of FIT from acute care at our hospitals, a policy that was put into effect in July 2019.

Corresponding author: Nathaniel J. Spezia-Lindner, MD, Baylor College of Medicine, 7200 Cambridge St, BCM 903, Ste A10.197, Houston, TX 77030; speziali@bcm.edu.

Financial disclosures: None.

Funding: Cancer Prevention and Research Institute of Texas, CPRIT (PP170094, PDs: ML Jibaja-Weiss and JR Montealegre).

References

1. Siegel RL, Miller KD, Jemal A. Cancer statistics, 2020. 10.1CA Cancer 10.1J Clin. 2020;70(1):7-30.

2. Howlader NN, Noone AM, Krapcho M, et al. SEER cancer statistics review, 1975-2014. National Cancer Institute; 2017:1-2.

3. Siegel RL, Fedewa SA, Anderson WF, et al. Colorectal cancer incidence patterns in the United States, 1974–2013. 10.1J Natl Cancer Inst. 2017;109(8):djw322.

4. Bailey CE, Hu CY, You YN, et al. Increasing disparities in the age-related incidences of colon and rectal cancers in the United States, 1975-2010. 10.25JAMA Surg. 2015;150(1):17-22.

5. Lin JS, Piper MA, Perdue LA, et al. Screening for colorectal cancer: updated evidence report and systematic review for the US Preventive Services Task Force. 10.25JAMA. 2016;315(23):2576-2594.

6. Centers for Disease Control and Prevention (CDC). Use of colorectal cancer screening tests. Behavioral Risk Factor Surveillance System. October 22, 2019. Accessed February 10, 2021. https://www.cdc.gov/cancer/colorectal/statistics/use-screening-tests-BRFSS.htm

7. Hewitson P, Glasziou PP, Irwig L, et al. Screening for colorectal cancer using the fecal occult blood test, Hemoccult. 10.25Cochrane Database Syst Rev. 2007;2007(1):CD001216.

8. Bujanda L, Lanas Á, Quintero E, et al. Effect of aspirin and antiplatelet drugs on the outcome of the fecal immunochemical test. 10.25Mayo Clin Proc. 2013;88(7):683-689.

9. Allison JE, Sakoda LC, Levin TR, et al. Screening for colorectal neoplasms with new fecal occult blood tests: update on performance characteristics. 10.25J Natl Cancer Inst. 2007;99(19):1462-1470.

10. Dancourt V, Lejeune C, Lepage C, et al. Immunochemical faecal occult blood tests are superior to guaiac-based tests for the detection of colorectal neoplasms. 10.25Eur J Cancer. 2008;44(15):2254-2258.

11. Hol L, Wilschut JA, van Ballegooijen M, et al. Screening for colorectal cancer: random comparison of guaiac and immunochemical faecal occult blood testing at different cut-off levels. 10.25Br J Cancer. 2009;100(7):1103-1110.

12. Levi Z, Birkenfeld S, Vilkin A, et al. A higher detection rate for colorectal cancer and advanced adenomatous polyp for screening with immunochemical fecal occult blood test than guaiac fecal occult blood test, despite lower compliance rate. A prospective, controlled, feasibility study. Int J Cancer. 2011;128(10):2415-2424.

13. Friedman A, Chan A, Chin LC, et al. Use and abuse of faecal occult blood tests in an acute hospital inpatient setting. Intern Med J. 2010;40(2):107-111.

14. Narula N, Ulic D, Al-Dabbagh R, et al. Fecal occult blood testing as a diagnostic test in symptomatic patients is not useful: a retrospective chart review. Can J Gastroenterol Hepatol. 2014;28(8):421-426.

15. Ip S, Sokoro AA, Kaita L, et al. Use of fecal occult blood testing in hospitalized patients: results of an audit. Can J Gastroenterol Hepatol. 2014;28(9):489-494.

16. Mosadeghi S, Ren H, Catungal J, et al. Utilization of fecal occult blood test in the acute hospital setting and its impact on clinical management and outcomes. J Postgrad Med. 2016;62(2):91-95.

17. van Rijn AF, Stroobants AK, Deutekom M, et al. Inappropriate use of the faecal occult blood test in a university hospital in the Netherlands. Eur J Gastroenterol Hepatol. 2012;24(11):1266-1269.

18. Sharma VK, Komanduri S, Nayyar S, et al. An audit of the utility of in-patient fecal occult blood testing. Am J Gastroenterol. 2001;96(4):1256-1260.

19. Chiang TH, Lee YC, Tu CH, et al. Performance of the immunochemical fecal occult blood test in predicting lesions in the lower gastrointestinal tract. CMAJ. 2011;183(13):1474-1481.

20. Chokshi DA, Chang JE, Wilson RM. Health reform and the changing safety net in the United States.  N Engl J Med. 2016;375(18):1790-1796.

21. Nguyen OK, Makam AN, Halm EA. National use of safety net clinics for primary care among adults with non-Medicaid insurance in the United States. PLoS One. 2016;11(3):e0151610.

22. United States Census Bureau. American Community Survey. Selected Economic Characteristics. 2019. Accessed February 20, 2021. https://data.census.gov/cedsci/table?q=ACSDP1Y2019.DP03%20Texas&g=0400000US48&tid=ACSDP1Y2019.DP03&hidePreview=true

23. McNutt LA, Wu C, Xue X, et al. Estimating the relative risk in cohort studies and clinical trials of common outcomes. Am J Epidemiol. 2003;157(10):940-943.

24. Rockey DC. Occult gastrointestinal bleeding. Gastroenterol Clin North Am. 2005;34(4):699-718.

25. Macrae FA, St John DJ. Relationship between patterns of bleeding and Hemoccult sensitivity in patients with colorectal cancers or adenomas. Gastroenterology. 1982;82(5 pt 1):891-898.

26. Johanson JF, Sonnenberg A. The prevalence of hemorrhoids and chronic constipation: an epidemiologic study. Gastroenterology. 1990;98(2):380-386.

27. Fleming JL, Ahlquist DA, McGill DB, et al. Influence of aspirin and ethanol on fecal blood levels as determined by using the HemoQuant assay. Mayo Clin Proc. 1987;62(3):159-163.

28. Gupta A, Tang Z, Agrawal D. Eliminating in-hospital fecal occult blood testing: our experience with disinvestment. Am J Med. 2018;131(7):760-763.

References

1. Siegel RL, Miller KD, Jemal A. Cancer statistics, 2020. 10.1CA Cancer 10.1J Clin. 2020;70(1):7-30.

2. Howlader NN, Noone AM, Krapcho M, et al. SEER cancer statistics review, 1975-2014. National Cancer Institute; 2017:1-2.

3. Siegel RL, Fedewa SA, Anderson WF, et al. Colorectal cancer incidence patterns in the United States, 1974–2013. 10.1J Natl Cancer Inst. 2017;109(8):djw322.

4. Bailey CE, Hu CY, You YN, et al. Increasing disparities in the age-related incidences of colon and rectal cancers in the United States, 1975-2010. 10.25JAMA Surg. 2015;150(1):17-22.

5. Lin JS, Piper MA, Perdue LA, et al. Screening for colorectal cancer: updated evidence report and systematic review for the US Preventive Services Task Force. 10.25JAMA. 2016;315(23):2576-2594.

6. Centers for Disease Control and Prevention (CDC). Use of colorectal cancer screening tests. Behavioral Risk Factor Surveillance System. October 22, 2019. Accessed February 10, 2021. https://www.cdc.gov/cancer/colorectal/statistics/use-screening-tests-BRFSS.htm

7. Hewitson P, Glasziou PP, Irwig L, et al. Screening for colorectal cancer using the fecal occult blood test, Hemoccult. 10.25Cochrane Database Syst Rev. 2007;2007(1):CD001216.

8. Bujanda L, Lanas Á, Quintero E, et al. Effect of aspirin and antiplatelet drugs on the outcome of the fecal immunochemical test. 10.25Mayo Clin Proc. 2013;88(7):683-689.

9. Allison JE, Sakoda LC, Levin TR, et al. Screening for colorectal neoplasms with new fecal occult blood tests: update on performance characteristics. 10.25J Natl Cancer Inst. 2007;99(19):1462-1470.

10. Dancourt V, Lejeune C, Lepage C, et al. Immunochemical faecal occult blood tests are superior to guaiac-based tests for the detection of colorectal neoplasms. 10.25Eur J Cancer. 2008;44(15):2254-2258.

11. Hol L, Wilschut JA, van Ballegooijen M, et al. Screening for colorectal cancer: random comparison of guaiac and immunochemical faecal occult blood testing at different cut-off levels. 10.25Br J Cancer. 2009;100(7):1103-1110.

12. Levi Z, Birkenfeld S, Vilkin A, et al. A higher detection rate for colorectal cancer and advanced adenomatous polyp for screening with immunochemical fecal occult blood test than guaiac fecal occult blood test, despite lower compliance rate. A prospective, controlled, feasibility study. Int J Cancer. 2011;128(10):2415-2424.

13. Friedman A, Chan A, Chin LC, et al. Use and abuse of faecal occult blood tests in an acute hospital inpatient setting. Intern Med J. 2010;40(2):107-111.

14. Narula N, Ulic D, Al-Dabbagh R, et al. Fecal occult blood testing as a diagnostic test in symptomatic patients is not useful: a retrospective chart review. Can J Gastroenterol Hepatol. 2014;28(8):421-426.

15. Ip S, Sokoro AA, Kaita L, et al. Use of fecal occult blood testing in hospitalized patients: results of an audit. Can J Gastroenterol Hepatol. 2014;28(9):489-494.

16. Mosadeghi S, Ren H, Catungal J, et al. Utilization of fecal occult blood test in the acute hospital setting and its impact on clinical management and outcomes. J Postgrad Med. 2016;62(2):91-95.

17. van Rijn AF, Stroobants AK, Deutekom M, et al. Inappropriate use of the faecal occult blood test in a university hospital in the Netherlands. Eur J Gastroenterol Hepatol. 2012;24(11):1266-1269.

18. Sharma VK, Komanduri S, Nayyar S, et al. An audit of the utility of in-patient fecal occult blood testing. Am J Gastroenterol. 2001;96(4):1256-1260.

19. Chiang TH, Lee YC, Tu CH, et al. Performance of the immunochemical fecal occult blood test in predicting lesions in the lower gastrointestinal tract. CMAJ. 2011;183(13):1474-1481.

20. Chokshi DA, Chang JE, Wilson RM. Health reform and the changing safety net in the United States.  N Engl J Med. 2016;375(18):1790-1796.

21. Nguyen OK, Makam AN, Halm EA. National use of safety net clinics for primary care among adults with non-Medicaid insurance in the United States. PLoS One. 2016;11(3):e0151610.

22. United States Census Bureau. American Community Survey. Selected Economic Characteristics. 2019. Accessed February 20, 2021. https://data.census.gov/cedsci/table?q=ACSDP1Y2019.DP03%20Texas&g=0400000US48&tid=ACSDP1Y2019.DP03&hidePreview=true

23. McNutt LA, Wu C, Xue X, et al. Estimating the relative risk in cohort studies and clinical trials of common outcomes. Am J Epidemiol. 2003;157(10):940-943.

24. Rockey DC. Occult gastrointestinal bleeding. Gastroenterol Clin North Am. 2005;34(4):699-718.

25. Macrae FA, St John DJ. Relationship between patterns of bleeding and Hemoccult sensitivity in patients with colorectal cancers or adenomas. Gastroenterology. 1982;82(5 pt 1):891-898.

26. Johanson JF, Sonnenberg A. The prevalence of hemorrhoids and chronic constipation: an epidemiologic study. Gastroenterology. 1990;98(2):380-386.

27. Fleming JL, Ahlquist DA, McGill DB, et al. Influence of aspirin and ethanol on fecal blood levels as determined by using the HemoQuant assay. Mayo Clin Proc. 1987;62(3):159-163.

28. Gupta A, Tang Z, Agrawal D. Eliminating in-hospital fecal occult blood testing: our experience with disinvestment. Am J Med. 2018;131(7):760-763.

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Implementing the AMI READMITS Risk Assessment Score to Increase Referrals Among Patients With Type I Myocardial Infarction

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Implementing the AMI READMITS Risk Assessment Score to Increase Referrals Among Patients With Type I Myocardial Infarction

From The Johns Hopkins Hospital, Baltimore, MD (Dr. Muganlinskaya and Dr. Skojec, retired); The George Washington University, Washington, DC (Dr. Posey); and Johns Hopkins University, Baltimore, MD (Dr. Resar).

Abstract

Objective: Assessing the risk characteristics of patients with acute myocardial infarction (MI) can help providers make appropriate referral decisions. This quality improvement project sought to improve timely, appropriate referrals among patients with type I MI by adding a risk assessment, the AMI READMITS score, to the existing referral protocol.

Methods: Patients’ chart data were analyzed to assess changes in referrals and timely follow-up appointments from pre-intervention to intervention. A survey assessed providers’ satisfaction with the new referral protocol.

Results: Among 57 patients (n = 29 preintervention; n = 28 intervention), documented referrals increased significantly from 66% to 89% (χ2 = 4.571, df = 1, P = 0.033); and timely appointments increased by 10%, which was not significant (χ2 = 3.550, df = 2, P = 0.169). Most providers agreed that the new protocol was easy to use, useful in making referral decisions, and improved the referral process. All agreed the risk score should be incorporated into electronic clinical notes. Provider opinions related to implementing the risk score in clinical practice were mixed. Qualitative feedback suggests this was due to limited validation of the AMI READMITS score in reducing readmissions.

Conclusions: Our risk-based referral protocol helped to increase appropriate referrals among patients with type I MI. Provider adoption may be enhanced by incorporating the protocol into electronic clinical notes. Research to further validate the accuracy of the AMI READMITS score in predicting readmissions may support adoption of the protocol in clinical practice.

Keywords: quality improvement; type I myocardial infarction; referral process; readmission risk; risk assessment; chart review.

Early follow-up after discharge is an important strategy to reduce the risk of unplanned hospital readmissions among patients with various conditions.1-3 While patient confounding factors, such as chronic health problems, environment, socioeconomic status, and literacy, make it difficult to avoid all unplanned readmissions, early follow-up may help providers identify and appropriately manage some health-related issues, and as such is a pivotal element of a readmission prevention strategy.4 There is evidence that patients with non-ST elevation myocardial infarction (NSTEMI) who have an outpatient appointment with a physician within 7 days after discharge have a lower risk of 30-day readmission.5

 

 

Our hospital’s postmyocardial infarction clinic was created to prevent unplanned readmissions within 30 days after discharge among patients with type I myocardial infarction (MI). Since inception, the number of referrals has been much lower than expected. In 2018, the total number of patients discharged from the hospital with type I MI and any troponin I level above 0.40 ng/mL was 313. Most of these patients were discharged from the hospital’s cardiac units; however, only 91 referrals were made. To increase referrals, the cardiology nurse practitioners (NPs) developed a post-MI referral protocol (Figure 1). However, this protocol was not consistently used and referrals to the clinic remained low.

Current referral protocol used to guide the hospital’s clinicians to make a referral decision prior to discharge

Evidence-based risk assessment tools have the potential to increase effective patient management. For example, cardiology providers at the hospital utilize various scores, such as CHA2DS2-VASc6 and the Society of Thoracic Surgery risk score,7 to plan patient management. Among the scores used to predict unplanned readmissions for MI patients, the most promising is the AMI READMITS score.8 Unlike other nonspecific prediction models, the AMI READMITS score was developed based on variables extracted from the electronic health records (EHRs) of patients who were hospitalized for MI and readmitted within 30 days after discharge. Recognizing the potential to increase referrals by integrating an MI-specific risk assessment, this quality improvement study modified the existing referral protocol to include the patients’ AMI READMITS score and recommendations for follow-up.

Currently, there are no clear recommendations on how soon after discharge patients with MI should undergo follow-up. As research data vary, we selected 7 days follow-up for patients from high risk groups based on the “See you in 7” initiative for patients with heart failure (HF) and MI,9,10 as well as evidence that patients with NSTEMI have a lower risk of 30-day readmission if they have follow-up within 7 days after discharge5; and we selected 14 days follow-up for patients from low-risk groups based on evidence that postdischarge follow-up within 14 days reduces risk of 30-day readmission in patients with acute myocardial infarction (AMI) and/or acutely decompensated HF.11

Methods

This project was designed to answer the following question: For adult patients with type I MI, does implementation of a readmission risk assessment referral protocol increase the percentage of referrals and appointments scheduled within a recommended time? Anticipated outcomes included: (1) increased referrals to a cardiologist or the post-MI clinic; (2) increased scheduled follow-up appointments within 7 to 14 days; (3) provider satisfaction with the usability and usefulness of the new protocol; and (4) consistent provider adoption of the new risk assessment referral protocol.

To evaluate the degree to which these outcomes were achieved, we reviewed patient charts for 2 months prior and 2 months during implementation of the new referral protocol. As shown in Figure 2, the new protocol added the following process steps to the existing protocol: calculation of the AMI READMITS score, recommendations for follow-up based on patients’ risk score, and guidance to refer patients to the post-MI clinic if patients did not have an appointment with a cardiologist within 7 to 14 days after discharge. Patients’ risk assessment scores were obtained from forms completed by clinicians during the intervention. Clinician’s perceptions related to the usability and usefulness of the new protocol and feedback related to its long-term adoption were assessed using a descriptive survey.

Post-myocardial infarction referral protocol to guide postdischarge referrals process implemented during the study

 

 

The institutional review board classified this project as a quality improvement project. To avoid potential loss of patient privacy, no identifiable data were collected, a unique identifier unrelated to patients’ records was generated for each patient, and data were saved on a password-protected cardiology office computer.

Population

The project population included all adult patients (≥ 18 years old) with type I MI who were admitted or transferred to the hospital, had a percutaneous coronary intervention (PCI), or were managed without PCI and discharged from the hospital’s cardiac care unit (CCU) and progressive cardiac care unit (PCCU). The criteria for type I MI included the “detection of a rise and/or fall of cardiac troponin with at least 1 value above the 99th percentile and with at least 1 of the following: symptoms of acute myocardial ischemia; new ischemic electrocardiographic (ECG) changes; development of new pathological Q waves; imaging evidence of new loss of viable myocardium or new regional wall motion abnormality in a pattern consistent with an ischemic etiology; identification of a coronary thrombus by angiography including intracoronary imaging or by autopsy.”12 The study excluded patients with type I MI who were referred for coronary bypass surgery.

Intervention

The revised risk assessment protocol was implemented within the CCU and PCCU. The lead investigator met with each provider to discuss the role of the post-MI clinic, current referral rates, the purpose of the project, and the new referral process to be completed during the project for each patient discharged with type I MI. Cardiology NPs, fellows, and residents were asked to use the risk-assessment form to calculate patients’ risk for readmission, and refer patients to the post-MI clinic if an appointment with a cardiologist was not available within 7 to 14 days after discharge. Every week during the intervention phase, the investigator sent reminder emails to ensure form completion. Providers were asked to calculate and write the score, the discharge and referral dates, where referrals were made (a cardiologist or the post-MI clinic), date of appointment, and reason for not scheduling an appointment or not referring on the risk assessment form, and to drop the completed forms in specific labeled boxes located at the CCU and PCCU work stations. The investigator collected the completed forms weekly. When the number of discharged patients did not match the number of completed forms, the investigator followed up with discharging providers to understand why.

Data and Data Collection

Data to determine whether the use of the new protocol increased discharge referrals among patients with type I MI within the recommended timeframes were collected by electronic chart review. Data included discharging unit, patients’ age, gender, admission and discharge date, diagnosis, referral to a cardiologist and the post-MI clinic, and appointment date. Clinical data needed to calculate the AMI READMITS score was also collected: PCI within 24 hours, serum creatinine, systolic blood pressure (SBP), brain natriuretic peptide (BNP), and diabetes status.

Data to assess provider satisfaction with the usability and usefulness of the new protocol were gathered through an online survey. The survey included 1 question related to the providers’ role, 1 question asking whether they used the risk assessment for each patient, and 5 Likert-items assessing the ease of usage. An additional open-ended question asked providers to share feedback related to integrating the AMI READMITS risk assessment score to the post-MI referral protocol long term.

To evaluate how consistently providers utilized the new referral protocol when discharging patients with type I MI, the number of completed forms was compared with the number of those patients who were discharged.

 

 

Statistical Analysis

Descriptive statistics were used to summarize patient demographics and to calculate the frequency of referrals before and during the intervention. Chi-square statistics were calculated to determine whether the change in percentage of referrals and timely referrals was significant. Descriptive statistics were used to determine the level of provider satisfaction related to each survey item. A content analysis method was used to synthesize themes from the open-ended question asking clinicians to share their feedback related to the new protocol.

Results

Fifty-seven patients met the study inclusion criteria: 29 patients during the preintervention phase and 28 patients during the intervention phase. There were 35 male (61.4%) and 22 female (38.6%) patients. Twenty-five patients (43.9%) were from age groups 41 through 60 years and 61 through 80 years, respectively, representing the majority of included patients. Seven patients (12.3%) were from the 81 years and older age group. There were no patients in the age group 18 through 40 years. Based on the AMI READMITS score calculation, 57.9% (n = 33) patients were from a low-risk group (includes extremely low and low risk for readmission) and 42.1% (n = 24) were from a high-risk group (includes moderate, high, and extremely high risk for readmission).

Provider adoption of the new protocol during the intervention was high. Referral forms were completed for 82% (n = 23) of the 28 patients during the intervention. Analysis findings showed a statistically significant increase in documented referrals after implementing the new referral protocol. During the preintervention phase, 66% (n = 19) of patients with type I MI were referred to see a cardiologist or an NP at a post-MI clinic and there was no documented referral for 34% (n = 10) of patients. During the intervention phase, 89% (n = 25) of patients were referred and there was no documented referral for 11% (n = 3) of patients. Chi-square results indicated that the increase in referrals was significant (χ2 = 4.571, df = 1, P = 0.033).

Data analysis examined whether patient referrals fell within the recommended timeframe of 7 days for the high-risk group (included moderate-to-extremely high risk) and 14 days for the low-risk group (included low-to-extremely low risk). During the preintervention phase, 31% (n = 9) of patient referrals were scheduled as recommended; 28% (n = 8) of patient referrals were scheduled but delayed; and there was no referral date documented for 41% (n = 12) of patients. During the intervention phase, referrals scheduled as recommended increased to 53% (n = 15); 25% (n = 7) of referrals were scheduled but delayed; and there was no referral date documented for 21.4% (n = 6) of patients. The change in appointments scheduled as recommended was not significant (χ2 = 3.550, df = 2, P = 0.169).

Surveys were emailed to 25 cardiology fellows and 3 cardiology NPs who participated in this study. Eighteen of the 28 clinicians (15 cardiology fellows and 3 cardiology NPs) responded for a response rate of 64%. One of several residents who rotated through the CCU and PCCU during the intervention also completed the survey, for a total of 19 participants. When asked if the protocol was easy to use, 79% agreed or strongly agreed. Eighteen of the 19 participants (95%) agreed or strongly agreed that the protocol was useful in making referral decisions. Sixty-eight percent agreed or strongly agreed that the AMI READMITS risk assessment score improves referral process. All participants agreed or strongly agreed that there should be an option to incorporate the AMI READMITS risk assessment score into electronic clinical notes. When asked whether the AMI READMITS risk score should be implemented in clinical practice, responses were mixed (Figure 3). A common theme among the 4 participants who responded with comments was the need for additional data to validate the usefulness of the AMI READMITS to reduce readmissions. In addition, 1 participant commented that “manual calculation [of the risk score] is not ideal.”

Provider perceptions related to implementing the AMI READMITS score in clinical practice

 

 

Discussion

This project demonstrated that implementing an evidence-based referral protocol integrating the AMI-READMITS score can increase timely postdischarge referrals among patients with type I MI. The percentage of appropriately scheduled appointments increased during the intervention phase; however, a relatively high number of appointments were scheduled outside of the recommended timeframe, similar to preintervention. Thus, while the new protocol increased referrals and provider documentation of these referrals, it appears that challenges in scheduling timely referral appointments remained. This project did not examine the reasons for delayed appointments.

The survey findings indicated that providers were generally satisfied with the usability and usefulness of the new risk assessment protocol. A large majority agreed or strongly agreed that it was easy to use and useful in making referral decisions, and most agreed or strongly agreed that it improves the referral process. Mixed opinions regarding implementing the AMI READMITS score in clinical practice, combined with qualitative findings, suggest that a lack of external validation of the AMI READMITS presents a barrier to its long-term adoption. All providers who participated in the survey agreed or strongly agreed that the risk assessment should be incorporated into electronic clinical notes. We have begun the process of working with the EHR vendor to automate the AMI risk-assessment within the referral work-flow, which will provide an opportunity for a follow-up quality improvement study.

This quality improvement project has several limitations. First, it implemented a small change in 2 inpatient units at 1 hospital using a simple pre- posttest design. Therefore, the findings are not generalizable to other settings. Prior to the intervention, some referrals may have been made without documentation. While the authors were able to trace undocumented referrals for patients who were referred to the post-MI clinic or to a cardiologist affiliated with the hospital, some patients may have been referred to cardiologists who were not affiliated with the hospital. Another limitation was that the self-created provider survey used was not tested in other clinical settings; thus, it cannot be determined whether the sensitivity and specificity of the survey questions are high. In addition, the clinical providers who participated in the study knew the study team, which may have influenced their behavior during the study period. Furthermore, the identified improvement in clinicians’ referral practices may not be sustainable due to the complexity and effort required to manually calculate the risk score. This limitation could be eliminated by integrating the risk score calculation into the EHR.

Conclusion

Early follow-up after discharge plays an important role in supporting patients’ self-management of some risk factors (ie, diet, weight, and smoking) and identifying gaps in postdischarge care which may lead to readmission. This project provides evidence that integrating the AMI READMITS risk assessment score into the referral process can help to guide discharge decision-making and increase timely, appropriate referrals for patients with MI. Integration of a specific risk assessment, such as the AMI READMITS, within the post-MI referral protocol may help clinicians make more efficient, educated referral decisions. Future studies should explore more specifically how and why the new protocol impacts clinicians’ decision-making and behavior related to post-MI referrals. In addition, future studies should investigate challenges associated with scheduling postdischarge appointments. It will be important to investigate how integration of the new protocol within the EHR may increase efficiency, consistency, and provider satisfaction with the new referral process. Additional research investigating the effects of the AMI READMITS score on readmissions reduction will be important to promote long-term adoption of the improved referral protocol in clinical practice.

Acknowledgments: The authors thank Shelly Conaway, ANP-BC, MSN, Angela Street, ANP-BC, MSN, Andrew Geis, ACNP-BC, MSN, Richard P. Jones II, MD, Eunice Young, MD, Joy Rothwell, MSN, RN-BC, Allison Olazo, MBA, MSN, RN-BC, Elizabeth Heck, RN-BC, and Matthew Trojanowski, MHA, MS, RRT, CSSBB for their support of this study.

Corresponding author: Nailya Muganlinskaya, DNP, MPH, ACNP-BC, MSN, The Johns Hopkins Hospital, 1800 Orleans St, Baltimore, MD 21287; nmuganl1@jhmi.edu.

Financial disclosures: None.

References

1. Why it is important to improve care transitions? Society of Hospital Medicine. Accessed June 15, 2020. https://www.hospitalmedicine.org/clinical-topics/care-transitions/

2. Tong L, Arnold T, Yang J, et al. The association between outpatient follow-up visits and all-cause non-elective 30-day readmissions: a retrospective observational cohort study. PloS One. 2018;13(7):e0200691.

3. Jackson C, Shahsahebi M, Wedlake T, DuBard CA. Timeliness of outpatient follow-up: an evidence-based approach for planning after hospital discharge. Ann Fam Med. 2015;13(2):115-22.

4. Health Research & Educational Trust. Preventable Readmissions Change Package. American Hospital Association. Updated December 2015. Accessed June 10, 2020. https://www.aha.org/sites/default/files/hiin/HRETHEN_ChangePackage_Readmissions.pd

5. Tung Y-C, Chang G-M, Chang H-Y, Yu T-H. Relationship between early physician follow-up and 30-day readmission after acute myocardial infarction and heart failure. Plos One. 2017;12(1):e0170061.

6. Kaplan RM, Koehler J, Zieger PD, et al. Stroke risk as a function of atrial fibrillation duration and CHA2DS2-VASc score. Circulation. 2019;140(20):1639-46.

7. Balan P, Zhao Y, Johnson S, et al. The Society of Thoracic Surgery Risk Score as a predictor of 30-day mortality in transcatheter vs surgical aortic valve replacement: a single-center experience and its implications for the development of a TAVR risk-prediction model. J Invasive Cardiol. 2017;29(3):109-14.

8. Smith LN, Makam AN, Darden D, et al. Acute myocardial infarction readmission risk prediction models: A systematic review of model performance. Circ Cardiovasc Qual Outcomes9.9. 2018;11(1):e003885.

9. Baker H, Oliver-McNeil S, Deng L, Hummel SL. See you in 7: regional hospital collaboration and outcomes in Medicare heart failure patients. JACC Heart Fail. 2015;3(10):765-73.

10. Batten A, Jaeger C, Griffen D, et al. See you in 7: improving acute myocardial infarction follow-up care. BMJ Open Qual. 2018;7(2):e000296.

11. Lee DW, Armistead L, Coleman H, et al. Abstract 15387: Post-discharge follow-up within 14 days reduces 30-day hospital readmission rates in patients with acute myocardial infarction and/or acutely decompensated heart failure. Circulation. 2018;134 (1):A 15387.

12. Thygesen K, Alpert JS, Jaffe AS, et al. Fourth universal definition of myocardial infarction. Circulation. 2018;138 (20):e:618-51.

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From The Johns Hopkins Hospital, Baltimore, MD (Dr. Muganlinskaya and Dr. Skojec, retired); The George Washington University, Washington, DC (Dr. Posey); and Johns Hopkins University, Baltimore, MD (Dr. Resar).

Abstract

Objective: Assessing the risk characteristics of patients with acute myocardial infarction (MI) can help providers make appropriate referral decisions. This quality improvement project sought to improve timely, appropriate referrals among patients with type I MI by adding a risk assessment, the AMI READMITS score, to the existing referral protocol.

Methods: Patients’ chart data were analyzed to assess changes in referrals and timely follow-up appointments from pre-intervention to intervention. A survey assessed providers’ satisfaction with the new referral protocol.

Results: Among 57 patients (n = 29 preintervention; n = 28 intervention), documented referrals increased significantly from 66% to 89% (χ2 = 4.571, df = 1, P = 0.033); and timely appointments increased by 10%, which was not significant (χ2 = 3.550, df = 2, P = 0.169). Most providers agreed that the new protocol was easy to use, useful in making referral decisions, and improved the referral process. All agreed the risk score should be incorporated into electronic clinical notes. Provider opinions related to implementing the risk score in clinical practice were mixed. Qualitative feedback suggests this was due to limited validation of the AMI READMITS score in reducing readmissions.

Conclusions: Our risk-based referral protocol helped to increase appropriate referrals among patients with type I MI. Provider adoption may be enhanced by incorporating the protocol into electronic clinical notes. Research to further validate the accuracy of the AMI READMITS score in predicting readmissions may support adoption of the protocol in clinical practice.

Keywords: quality improvement; type I myocardial infarction; referral process; readmission risk; risk assessment; chart review.

Early follow-up after discharge is an important strategy to reduce the risk of unplanned hospital readmissions among patients with various conditions.1-3 While patient confounding factors, such as chronic health problems, environment, socioeconomic status, and literacy, make it difficult to avoid all unplanned readmissions, early follow-up may help providers identify and appropriately manage some health-related issues, and as such is a pivotal element of a readmission prevention strategy.4 There is evidence that patients with non-ST elevation myocardial infarction (NSTEMI) who have an outpatient appointment with a physician within 7 days after discharge have a lower risk of 30-day readmission.5

 

 

Our hospital’s postmyocardial infarction clinic was created to prevent unplanned readmissions within 30 days after discharge among patients with type I myocardial infarction (MI). Since inception, the number of referrals has been much lower than expected. In 2018, the total number of patients discharged from the hospital with type I MI and any troponin I level above 0.40 ng/mL was 313. Most of these patients were discharged from the hospital’s cardiac units; however, only 91 referrals were made. To increase referrals, the cardiology nurse practitioners (NPs) developed a post-MI referral protocol (Figure 1). However, this protocol was not consistently used and referrals to the clinic remained low.

Current referral protocol used to guide the hospital’s clinicians to make a referral decision prior to discharge

Evidence-based risk assessment tools have the potential to increase effective patient management. For example, cardiology providers at the hospital utilize various scores, such as CHA2DS2-VASc6 and the Society of Thoracic Surgery risk score,7 to plan patient management. Among the scores used to predict unplanned readmissions for MI patients, the most promising is the AMI READMITS score.8 Unlike other nonspecific prediction models, the AMI READMITS score was developed based on variables extracted from the electronic health records (EHRs) of patients who were hospitalized for MI and readmitted within 30 days after discharge. Recognizing the potential to increase referrals by integrating an MI-specific risk assessment, this quality improvement study modified the existing referral protocol to include the patients’ AMI READMITS score and recommendations for follow-up.

Currently, there are no clear recommendations on how soon after discharge patients with MI should undergo follow-up. As research data vary, we selected 7 days follow-up for patients from high risk groups based on the “See you in 7” initiative for patients with heart failure (HF) and MI,9,10 as well as evidence that patients with NSTEMI have a lower risk of 30-day readmission if they have follow-up within 7 days after discharge5; and we selected 14 days follow-up for patients from low-risk groups based on evidence that postdischarge follow-up within 14 days reduces risk of 30-day readmission in patients with acute myocardial infarction (AMI) and/or acutely decompensated HF.11

Methods

This project was designed to answer the following question: For adult patients with type I MI, does implementation of a readmission risk assessment referral protocol increase the percentage of referrals and appointments scheduled within a recommended time? Anticipated outcomes included: (1) increased referrals to a cardiologist or the post-MI clinic; (2) increased scheduled follow-up appointments within 7 to 14 days; (3) provider satisfaction with the usability and usefulness of the new protocol; and (4) consistent provider adoption of the new risk assessment referral protocol.

To evaluate the degree to which these outcomes were achieved, we reviewed patient charts for 2 months prior and 2 months during implementation of the new referral protocol. As shown in Figure 2, the new protocol added the following process steps to the existing protocol: calculation of the AMI READMITS score, recommendations for follow-up based on patients’ risk score, and guidance to refer patients to the post-MI clinic if patients did not have an appointment with a cardiologist within 7 to 14 days after discharge. Patients’ risk assessment scores were obtained from forms completed by clinicians during the intervention. Clinician’s perceptions related to the usability and usefulness of the new protocol and feedback related to its long-term adoption were assessed using a descriptive survey.

Post-myocardial infarction referral protocol to guide postdischarge referrals process implemented during the study

 

 

The institutional review board classified this project as a quality improvement project. To avoid potential loss of patient privacy, no identifiable data were collected, a unique identifier unrelated to patients’ records was generated for each patient, and data were saved on a password-protected cardiology office computer.

Population

The project population included all adult patients (≥ 18 years old) with type I MI who were admitted or transferred to the hospital, had a percutaneous coronary intervention (PCI), or were managed without PCI and discharged from the hospital’s cardiac care unit (CCU) and progressive cardiac care unit (PCCU). The criteria for type I MI included the “detection of a rise and/or fall of cardiac troponin with at least 1 value above the 99th percentile and with at least 1 of the following: symptoms of acute myocardial ischemia; new ischemic electrocardiographic (ECG) changes; development of new pathological Q waves; imaging evidence of new loss of viable myocardium or new regional wall motion abnormality in a pattern consistent with an ischemic etiology; identification of a coronary thrombus by angiography including intracoronary imaging or by autopsy.”12 The study excluded patients with type I MI who were referred for coronary bypass surgery.

Intervention

The revised risk assessment protocol was implemented within the CCU and PCCU. The lead investigator met with each provider to discuss the role of the post-MI clinic, current referral rates, the purpose of the project, and the new referral process to be completed during the project for each patient discharged with type I MI. Cardiology NPs, fellows, and residents were asked to use the risk-assessment form to calculate patients’ risk for readmission, and refer patients to the post-MI clinic if an appointment with a cardiologist was not available within 7 to 14 days after discharge. Every week during the intervention phase, the investigator sent reminder emails to ensure form completion. Providers were asked to calculate and write the score, the discharge and referral dates, where referrals were made (a cardiologist or the post-MI clinic), date of appointment, and reason for not scheduling an appointment or not referring on the risk assessment form, and to drop the completed forms in specific labeled boxes located at the CCU and PCCU work stations. The investigator collected the completed forms weekly. When the number of discharged patients did not match the number of completed forms, the investigator followed up with discharging providers to understand why.

Data and Data Collection

Data to determine whether the use of the new protocol increased discharge referrals among patients with type I MI within the recommended timeframes were collected by electronic chart review. Data included discharging unit, patients’ age, gender, admission and discharge date, diagnosis, referral to a cardiologist and the post-MI clinic, and appointment date. Clinical data needed to calculate the AMI READMITS score was also collected: PCI within 24 hours, serum creatinine, systolic blood pressure (SBP), brain natriuretic peptide (BNP), and diabetes status.

Data to assess provider satisfaction with the usability and usefulness of the new protocol were gathered through an online survey. The survey included 1 question related to the providers’ role, 1 question asking whether they used the risk assessment for each patient, and 5 Likert-items assessing the ease of usage. An additional open-ended question asked providers to share feedback related to integrating the AMI READMITS risk assessment score to the post-MI referral protocol long term.

To evaluate how consistently providers utilized the new referral protocol when discharging patients with type I MI, the number of completed forms was compared with the number of those patients who were discharged.

 

 

Statistical Analysis

Descriptive statistics were used to summarize patient demographics and to calculate the frequency of referrals before and during the intervention. Chi-square statistics were calculated to determine whether the change in percentage of referrals and timely referrals was significant. Descriptive statistics were used to determine the level of provider satisfaction related to each survey item. A content analysis method was used to synthesize themes from the open-ended question asking clinicians to share their feedback related to the new protocol.

Results

Fifty-seven patients met the study inclusion criteria: 29 patients during the preintervention phase and 28 patients during the intervention phase. There were 35 male (61.4%) and 22 female (38.6%) patients. Twenty-five patients (43.9%) were from age groups 41 through 60 years and 61 through 80 years, respectively, representing the majority of included patients. Seven patients (12.3%) were from the 81 years and older age group. There were no patients in the age group 18 through 40 years. Based on the AMI READMITS score calculation, 57.9% (n = 33) patients were from a low-risk group (includes extremely low and low risk for readmission) and 42.1% (n = 24) were from a high-risk group (includes moderate, high, and extremely high risk for readmission).

Provider adoption of the new protocol during the intervention was high. Referral forms were completed for 82% (n = 23) of the 28 patients during the intervention. Analysis findings showed a statistically significant increase in documented referrals after implementing the new referral protocol. During the preintervention phase, 66% (n = 19) of patients with type I MI were referred to see a cardiologist or an NP at a post-MI clinic and there was no documented referral for 34% (n = 10) of patients. During the intervention phase, 89% (n = 25) of patients were referred and there was no documented referral for 11% (n = 3) of patients. Chi-square results indicated that the increase in referrals was significant (χ2 = 4.571, df = 1, P = 0.033).

Data analysis examined whether patient referrals fell within the recommended timeframe of 7 days for the high-risk group (included moderate-to-extremely high risk) and 14 days for the low-risk group (included low-to-extremely low risk). During the preintervention phase, 31% (n = 9) of patient referrals were scheduled as recommended; 28% (n = 8) of patient referrals were scheduled but delayed; and there was no referral date documented for 41% (n = 12) of patients. During the intervention phase, referrals scheduled as recommended increased to 53% (n = 15); 25% (n = 7) of referrals were scheduled but delayed; and there was no referral date documented for 21.4% (n = 6) of patients. The change in appointments scheduled as recommended was not significant (χ2 = 3.550, df = 2, P = 0.169).

Surveys were emailed to 25 cardiology fellows and 3 cardiology NPs who participated in this study. Eighteen of the 28 clinicians (15 cardiology fellows and 3 cardiology NPs) responded for a response rate of 64%. One of several residents who rotated through the CCU and PCCU during the intervention also completed the survey, for a total of 19 participants. When asked if the protocol was easy to use, 79% agreed or strongly agreed. Eighteen of the 19 participants (95%) agreed or strongly agreed that the protocol was useful in making referral decisions. Sixty-eight percent agreed or strongly agreed that the AMI READMITS risk assessment score improves referral process. All participants agreed or strongly agreed that there should be an option to incorporate the AMI READMITS risk assessment score into electronic clinical notes. When asked whether the AMI READMITS risk score should be implemented in clinical practice, responses were mixed (Figure 3). A common theme among the 4 participants who responded with comments was the need for additional data to validate the usefulness of the AMI READMITS to reduce readmissions. In addition, 1 participant commented that “manual calculation [of the risk score] is not ideal.”

Provider perceptions related to implementing the AMI READMITS score in clinical practice

 

 

Discussion

This project demonstrated that implementing an evidence-based referral protocol integrating the AMI-READMITS score can increase timely postdischarge referrals among patients with type I MI. The percentage of appropriately scheduled appointments increased during the intervention phase; however, a relatively high number of appointments were scheduled outside of the recommended timeframe, similar to preintervention. Thus, while the new protocol increased referrals and provider documentation of these referrals, it appears that challenges in scheduling timely referral appointments remained. This project did not examine the reasons for delayed appointments.

The survey findings indicated that providers were generally satisfied with the usability and usefulness of the new risk assessment protocol. A large majority agreed or strongly agreed that it was easy to use and useful in making referral decisions, and most agreed or strongly agreed that it improves the referral process. Mixed opinions regarding implementing the AMI READMITS score in clinical practice, combined with qualitative findings, suggest that a lack of external validation of the AMI READMITS presents a barrier to its long-term adoption. All providers who participated in the survey agreed or strongly agreed that the risk assessment should be incorporated into electronic clinical notes. We have begun the process of working with the EHR vendor to automate the AMI risk-assessment within the referral work-flow, which will provide an opportunity for a follow-up quality improvement study.

This quality improvement project has several limitations. First, it implemented a small change in 2 inpatient units at 1 hospital using a simple pre- posttest design. Therefore, the findings are not generalizable to other settings. Prior to the intervention, some referrals may have been made without documentation. While the authors were able to trace undocumented referrals for patients who were referred to the post-MI clinic or to a cardiologist affiliated with the hospital, some patients may have been referred to cardiologists who were not affiliated with the hospital. Another limitation was that the self-created provider survey used was not tested in other clinical settings; thus, it cannot be determined whether the sensitivity and specificity of the survey questions are high. In addition, the clinical providers who participated in the study knew the study team, which may have influenced their behavior during the study period. Furthermore, the identified improvement in clinicians’ referral practices may not be sustainable due to the complexity and effort required to manually calculate the risk score. This limitation could be eliminated by integrating the risk score calculation into the EHR.

Conclusion

Early follow-up after discharge plays an important role in supporting patients’ self-management of some risk factors (ie, diet, weight, and smoking) and identifying gaps in postdischarge care which may lead to readmission. This project provides evidence that integrating the AMI READMITS risk assessment score into the referral process can help to guide discharge decision-making and increase timely, appropriate referrals for patients with MI. Integration of a specific risk assessment, such as the AMI READMITS, within the post-MI referral protocol may help clinicians make more efficient, educated referral decisions. Future studies should explore more specifically how and why the new protocol impacts clinicians’ decision-making and behavior related to post-MI referrals. In addition, future studies should investigate challenges associated with scheduling postdischarge appointments. It will be important to investigate how integration of the new protocol within the EHR may increase efficiency, consistency, and provider satisfaction with the new referral process. Additional research investigating the effects of the AMI READMITS score on readmissions reduction will be important to promote long-term adoption of the improved referral protocol in clinical practice.

Acknowledgments: The authors thank Shelly Conaway, ANP-BC, MSN, Angela Street, ANP-BC, MSN, Andrew Geis, ACNP-BC, MSN, Richard P. Jones II, MD, Eunice Young, MD, Joy Rothwell, MSN, RN-BC, Allison Olazo, MBA, MSN, RN-BC, Elizabeth Heck, RN-BC, and Matthew Trojanowski, MHA, MS, RRT, CSSBB for their support of this study.

Corresponding author: Nailya Muganlinskaya, DNP, MPH, ACNP-BC, MSN, The Johns Hopkins Hospital, 1800 Orleans St, Baltimore, MD 21287; nmuganl1@jhmi.edu.

Financial disclosures: None.

From The Johns Hopkins Hospital, Baltimore, MD (Dr. Muganlinskaya and Dr. Skojec, retired); The George Washington University, Washington, DC (Dr. Posey); and Johns Hopkins University, Baltimore, MD (Dr. Resar).

Abstract

Objective: Assessing the risk characteristics of patients with acute myocardial infarction (MI) can help providers make appropriate referral decisions. This quality improvement project sought to improve timely, appropriate referrals among patients with type I MI by adding a risk assessment, the AMI READMITS score, to the existing referral protocol.

Methods: Patients’ chart data were analyzed to assess changes in referrals and timely follow-up appointments from pre-intervention to intervention. A survey assessed providers’ satisfaction with the new referral protocol.

Results: Among 57 patients (n = 29 preintervention; n = 28 intervention), documented referrals increased significantly from 66% to 89% (χ2 = 4.571, df = 1, P = 0.033); and timely appointments increased by 10%, which was not significant (χ2 = 3.550, df = 2, P = 0.169). Most providers agreed that the new protocol was easy to use, useful in making referral decisions, and improved the referral process. All agreed the risk score should be incorporated into electronic clinical notes. Provider opinions related to implementing the risk score in clinical practice were mixed. Qualitative feedback suggests this was due to limited validation of the AMI READMITS score in reducing readmissions.

Conclusions: Our risk-based referral protocol helped to increase appropriate referrals among patients with type I MI. Provider adoption may be enhanced by incorporating the protocol into electronic clinical notes. Research to further validate the accuracy of the AMI READMITS score in predicting readmissions may support adoption of the protocol in clinical practice.

Keywords: quality improvement; type I myocardial infarction; referral process; readmission risk; risk assessment; chart review.

Early follow-up after discharge is an important strategy to reduce the risk of unplanned hospital readmissions among patients with various conditions.1-3 While patient confounding factors, such as chronic health problems, environment, socioeconomic status, and literacy, make it difficult to avoid all unplanned readmissions, early follow-up may help providers identify and appropriately manage some health-related issues, and as such is a pivotal element of a readmission prevention strategy.4 There is evidence that patients with non-ST elevation myocardial infarction (NSTEMI) who have an outpatient appointment with a physician within 7 days after discharge have a lower risk of 30-day readmission.5

 

 

Our hospital’s postmyocardial infarction clinic was created to prevent unplanned readmissions within 30 days after discharge among patients with type I myocardial infarction (MI). Since inception, the number of referrals has been much lower than expected. In 2018, the total number of patients discharged from the hospital with type I MI and any troponin I level above 0.40 ng/mL was 313. Most of these patients were discharged from the hospital’s cardiac units; however, only 91 referrals were made. To increase referrals, the cardiology nurse practitioners (NPs) developed a post-MI referral protocol (Figure 1). However, this protocol was not consistently used and referrals to the clinic remained low.

Current referral protocol used to guide the hospital’s clinicians to make a referral decision prior to discharge

Evidence-based risk assessment tools have the potential to increase effective patient management. For example, cardiology providers at the hospital utilize various scores, such as CHA2DS2-VASc6 and the Society of Thoracic Surgery risk score,7 to plan patient management. Among the scores used to predict unplanned readmissions for MI patients, the most promising is the AMI READMITS score.8 Unlike other nonspecific prediction models, the AMI READMITS score was developed based on variables extracted from the electronic health records (EHRs) of patients who were hospitalized for MI and readmitted within 30 days after discharge. Recognizing the potential to increase referrals by integrating an MI-specific risk assessment, this quality improvement study modified the existing referral protocol to include the patients’ AMI READMITS score and recommendations for follow-up.

Currently, there are no clear recommendations on how soon after discharge patients with MI should undergo follow-up. As research data vary, we selected 7 days follow-up for patients from high risk groups based on the “See you in 7” initiative for patients with heart failure (HF) and MI,9,10 as well as evidence that patients with NSTEMI have a lower risk of 30-day readmission if they have follow-up within 7 days after discharge5; and we selected 14 days follow-up for patients from low-risk groups based on evidence that postdischarge follow-up within 14 days reduces risk of 30-day readmission in patients with acute myocardial infarction (AMI) and/or acutely decompensated HF.11

Methods

This project was designed to answer the following question: For adult patients with type I MI, does implementation of a readmission risk assessment referral protocol increase the percentage of referrals and appointments scheduled within a recommended time? Anticipated outcomes included: (1) increased referrals to a cardiologist or the post-MI clinic; (2) increased scheduled follow-up appointments within 7 to 14 days; (3) provider satisfaction with the usability and usefulness of the new protocol; and (4) consistent provider adoption of the new risk assessment referral protocol.

To evaluate the degree to which these outcomes were achieved, we reviewed patient charts for 2 months prior and 2 months during implementation of the new referral protocol. As shown in Figure 2, the new protocol added the following process steps to the existing protocol: calculation of the AMI READMITS score, recommendations for follow-up based on patients’ risk score, and guidance to refer patients to the post-MI clinic if patients did not have an appointment with a cardiologist within 7 to 14 days after discharge. Patients’ risk assessment scores were obtained from forms completed by clinicians during the intervention. Clinician’s perceptions related to the usability and usefulness of the new protocol and feedback related to its long-term adoption were assessed using a descriptive survey.

Post-myocardial infarction referral protocol to guide postdischarge referrals process implemented during the study

 

 

The institutional review board classified this project as a quality improvement project. To avoid potential loss of patient privacy, no identifiable data were collected, a unique identifier unrelated to patients’ records was generated for each patient, and data were saved on a password-protected cardiology office computer.

Population

The project population included all adult patients (≥ 18 years old) with type I MI who were admitted or transferred to the hospital, had a percutaneous coronary intervention (PCI), or were managed without PCI and discharged from the hospital’s cardiac care unit (CCU) and progressive cardiac care unit (PCCU). The criteria for type I MI included the “detection of a rise and/or fall of cardiac troponin with at least 1 value above the 99th percentile and with at least 1 of the following: symptoms of acute myocardial ischemia; new ischemic electrocardiographic (ECG) changes; development of new pathological Q waves; imaging evidence of new loss of viable myocardium or new regional wall motion abnormality in a pattern consistent with an ischemic etiology; identification of a coronary thrombus by angiography including intracoronary imaging or by autopsy.”12 The study excluded patients with type I MI who were referred for coronary bypass surgery.

Intervention

The revised risk assessment protocol was implemented within the CCU and PCCU. The lead investigator met with each provider to discuss the role of the post-MI clinic, current referral rates, the purpose of the project, and the new referral process to be completed during the project for each patient discharged with type I MI. Cardiology NPs, fellows, and residents were asked to use the risk-assessment form to calculate patients’ risk for readmission, and refer patients to the post-MI clinic if an appointment with a cardiologist was not available within 7 to 14 days after discharge. Every week during the intervention phase, the investigator sent reminder emails to ensure form completion. Providers were asked to calculate and write the score, the discharge and referral dates, where referrals were made (a cardiologist or the post-MI clinic), date of appointment, and reason for not scheduling an appointment or not referring on the risk assessment form, and to drop the completed forms in specific labeled boxes located at the CCU and PCCU work stations. The investigator collected the completed forms weekly. When the number of discharged patients did not match the number of completed forms, the investigator followed up with discharging providers to understand why.

Data and Data Collection

Data to determine whether the use of the new protocol increased discharge referrals among patients with type I MI within the recommended timeframes were collected by electronic chart review. Data included discharging unit, patients’ age, gender, admission and discharge date, diagnosis, referral to a cardiologist and the post-MI clinic, and appointment date. Clinical data needed to calculate the AMI READMITS score was also collected: PCI within 24 hours, serum creatinine, systolic blood pressure (SBP), brain natriuretic peptide (BNP), and diabetes status.

Data to assess provider satisfaction with the usability and usefulness of the new protocol were gathered through an online survey. The survey included 1 question related to the providers’ role, 1 question asking whether they used the risk assessment for each patient, and 5 Likert-items assessing the ease of usage. An additional open-ended question asked providers to share feedback related to integrating the AMI READMITS risk assessment score to the post-MI referral protocol long term.

To evaluate how consistently providers utilized the new referral protocol when discharging patients with type I MI, the number of completed forms was compared with the number of those patients who were discharged.

 

 

Statistical Analysis

Descriptive statistics were used to summarize patient demographics and to calculate the frequency of referrals before and during the intervention. Chi-square statistics were calculated to determine whether the change in percentage of referrals and timely referrals was significant. Descriptive statistics were used to determine the level of provider satisfaction related to each survey item. A content analysis method was used to synthesize themes from the open-ended question asking clinicians to share their feedback related to the new protocol.

Results

Fifty-seven patients met the study inclusion criteria: 29 patients during the preintervention phase and 28 patients during the intervention phase. There were 35 male (61.4%) and 22 female (38.6%) patients. Twenty-five patients (43.9%) were from age groups 41 through 60 years and 61 through 80 years, respectively, representing the majority of included patients. Seven patients (12.3%) were from the 81 years and older age group. There were no patients in the age group 18 through 40 years. Based on the AMI READMITS score calculation, 57.9% (n = 33) patients were from a low-risk group (includes extremely low and low risk for readmission) and 42.1% (n = 24) were from a high-risk group (includes moderate, high, and extremely high risk for readmission).

Provider adoption of the new protocol during the intervention was high. Referral forms were completed for 82% (n = 23) of the 28 patients during the intervention. Analysis findings showed a statistically significant increase in documented referrals after implementing the new referral protocol. During the preintervention phase, 66% (n = 19) of patients with type I MI were referred to see a cardiologist or an NP at a post-MI clinic and there was no documented referral for 34% (n = 10) of patients. During the intervention phase, 89% (n = 25) of patients were referred and there was no documented referral for 11% (n = 3) of patients. Chi-square results indicated that the increase in referrals was significant (χ2 = 4.571, df = 1, P = 0.033).

Data analysis examined whether patient referrals fell within the recommended timeframe of 7 days for the high-risk group (included moderate-to-extremely high risk) and 14 days for the low-risk group (included low-to-extremely low risk). During the preintervention phase, 31% (n = 9) of patient referrals were scheduled as recommended; 28% (n = 8) of patient referrals were scheduled but delayed; and there was no referral date documented for 41% (n = 12) of patients. During the intervention phase, referrals scheduled as recommended increased to 53% (n = 15); 25% (n = 7) of referrals were scheduled but delayed; and there was no referral date documented for 21.4% (n = 6) of patients. The change in appointments scheduled as recommended was not significant (χ2 = 3.550, df = 2, P = 0.169).

Surveys were emailed to 25 cardiology fellows and 3 cardiology NPs who participated in this study. Eighteen of the 28 clinicians (15 cardiology fellows and 3 cardiology NPs) responded for a response rate of 64%. One of several residents who rotated through the CCU and PCCU during the intervention also completed the survey, for a total of 19 participants. When asked if the protocol was easy to use, 79% agreed or strongly agreed. Eighteen of the 19 participants (95%) agreed or strongly agreed that the protocol was useful in making referral decisions. Sixty-eight percent agreed or strongly agreed that the AMI READMITS risk assessment score improves referral process. All participants agreed or strongly agreed that there should be an option to incorporate the AMI READMITS risk assessment score into electronic clinical notes. When asked whether the AMI READMITS risk score should be implemented in clinical practice, responses were mixed (Figure 3). A common theme among the 4 participants who responded with comments was the need for additional data to validate the usefulness of the AMI READMITS to reduce readmissions. In addition, 1 participant commented that “manual calculation [of the risk score] is not ideal.”

Provider perceptions related to implementing the AMI READMITS score in clinical practice

 

 

Discussion

This project demonstrated that implementing an evidence-based referral protocol integrating the AMI-READMITS score can increase timely postdischarge referrals among patients with type I MI. The percentage of appropriately scheduled appointments increased during the intervention phase; however, a relatively high number of appointments were scheduled outside of the recommended timeframe, similar to preintervention. Thus, while the new protocol increased referrals and provider documentation of these referrals, it appears that challenges in scheduling timely referral appointments remained. This project did not examine the reasons for delayed appointments.

The survey findings indicated that providers were generally satisfied with the usability and usefulness of the new risk assessment protocol. A large majority agreed or strongly agreed that it was easy to use and useful in making referral decisions, and most agreed or strongly agreed that it improves the referral process. Mixed opinions regarding implementing the AMI READMITS score in clinical practice, combined with qualitative findings, suggest that a lack of external validation of the AMI READMITS presents a barrier to its long-term adoption. All providers who participated in the survey agreed or strongly agreed that the risk assessment should be incorporated into electronic clinical notes. We have begun the process of working with the EHR vendor to automate the AMI risk-assessment within the referral work-flow, which will provide an opportunity for a follow-up quality improvement study.

This quality improvement project has several limitations. First, it implemented a small change in 2 inpatient units at 1 hospital using a simple pre- posttest design. Therefore, the findings are not generalizable to other settings. Prior to the intervention, some referrals may have been made without documentation. While the authors were able to trace undocumented referrals for patients who were referred to the post-MI clinic or to a cardiologist affiliated with the hospital, some patients may have been referred to cardiologists who were not affiliated with the hospital. Another limitation was that the self-created provider survey used was not tested in other clinical settings; thus, it cannot be determined whether the sensitivity and specificity of the survey questions are high. In addition, the clinical providers who participated in the study knew the study team, which may have influenced their behavior during the study period. Furthermore, the identified improvement in clinicians’ referral practices may not be sustainable due to the complexity and effort required to manually calculate the risk score. This limitation could be eliminated by integrating the risk score calculation into the EHR.

Conclusion

Early follow-up after discharge plays an important role in supporting patients’ self-management of some risk factors (ie, diet, weight, and smoking) and identifying gaps in postdischarge care which may lead to readmission. This project provides evidence that integrating the AMI READMITS risk assessment score into the referral process can help to guide discharge decision-making and increase timely, appropriate referrals for patients with MI. Integration of a specific risk assessment, such as the AMI READMITS, within the post-MI referral protocol may help clinicians make more efficient, educated referral decisions. Future studies should explore more specifically how and why the new protocol impacts clinicians’ decision-making and behavior related to post-MI referrals. In addition, future studies should investigate challenges associated with scheduling postdischarge appointments. It will be important to investigate how integration of the new protocol within the EHR may increase efficiency, consistency, and provider satisfaction with the new referral process. Additional research investigating the effects of the AMI READMITS score on readmissions reduction will be important to promote long-term adoption of the improved referral protocol in clinical practice.

Acknowledgments: The authors thank Shelly Conaway, ANP-BC, MSN, Angela Street, ANP-BC, MSN, Andrew Geis, ACNP-BC, MSN, Richard P. Jones II, MD, Eunice Young, MD, Joy Rothwell, MSN, RN-BC, Allison Olazo, MBA, MSN, RN-BC, Elizabeth Heck, RN-BC, and Matthew Trojanowski, MHA, MS, RRT, CSSBB for their support of this study.

Corresponding author: Nailya Muganlinskaya, DNP, MPH, ACNP-BC, MSN, The Johns Hopkins Hospital, 1800 Orleans St, Baltimore, MD 21287; nmuganl1@jhmi.edu.

Financial disclosures: None.

References

1. Why it is important to improve care transitions? Society of Hospital Medicine. Accessed June 15, 2020. https://www.hospitalmedicine.org/clinical-topics/care-transitions/

2. Tong L, Arnold T, Yang J, et al. The association between outpatient follow-up visits and all-cause non-elective 30-day readmissions: a retrospective observational cohort study. PloS One. 2018;13(7):e0200691.

3. Jackson C, Shahsahebi M, Wedlake T, DuBard CA. Timeliness of outpatient follow-up: an evidence-based approach for planning after hospital discharge. Ann Fam Med. 2015;13(2):115-22.

4. Health Research & Educational Trust. Preventable Readmissions Change Package. American Hospital Association. Updated December 2015. Accessed June 10, 2020. https://www.aha.org/sites/default/files/hiin/HRETHEN_ChangePackage_Readmissions.pd

5. Tung Y-C, Chang G-M, Chang H-Y, Yu T-H. Relationship between early physician follow-up and 30-day readmission after acute myocardial infarction and heart failure. Plos One. 2017;12(1):e0170061.

6. Kaplan RM, Koehler J, Zieger PD, et al. Stroke risk as a function of atrial fibrillation duration and CHA2DS2-VASc score. Circulation. 2019;140(20):1639-46.

7. Balan P, Zhao Y, Johnson S, et al. The Society of Thoracic Surgery Risk Score as a predictor of 30-day mortality in transcatheter vs surgical aortic valve replacement: a single-center experience and its implications for the development of a TAVR risk-prediction model. J Invasive Cardiol. 2017;29(3):109-14.

8. Smith LN, Makam AN, Darden D, et al. Acute myocardial infarction readmission risk prediction models: A systematic review of model performance. Circ Cardiovasc Qual Outcomes9.9. 2018;11(1):e003885.

9. Baker H, Oliver-McNeil S, Deng L, Hummel SL. See you in 7: regional hospital collaboration and outcomes in Medicare heart failure patients. JACC Heart Fail. 2015;3(10):765-73.

10. Batten A, Jaeger C, Griffen D, et al. See you in 7: improving acute myocardial infarction follow-up care. BMJ Open Qual. 2018;7(2):e000296.

11. Lee DW, Armistead L, Coleman H, et al. Abstract 15387: Post-discharge follow-up within 14 days reduces 30-day hospital readmission rates in patients with acute myocardial infarction and/or acutely decompensated heart failure. Circulation. 2018;134 (1):A 15387.

12. Thygesen K, Alpert JS, Jaffe AS, et al. Fourth universal definition of myocardial infarction. Circulation. 2018;138 (20):e:618-51.

References

1. Why it is important to improve care transitions? Society of Hospital Medicine. Accessed June 15, 2020. https://www.hospitalmedicine.org/clinical-topics/care-transitions/

2. Tong L, Arnold T, Yang J, et al. The association between outpatient follow-up visits and all-cause non-elective 30-day readmissions: a retrospective observational cohort study. PloS One. 2018;13(7):e0200691.

3. Jackson C, Shahsahebi M, Wedlake T, DuBard CA. Timeliness of outpatient follow-up: an evidence-based approach for planning after hospital discharge. Ann Fam Med. 2015;13(2):115-22.

4. Health Research & Educational Trust. Preventable Readmissions Change Package. American Hospital Association. Updated December 2015. Accessed June 10, 2020. https://www.aha.org/sites/default/files/hiin/HRETHEN_ChangePackage_Readmissions.pd

5. Tung Y-C, Chang G-M, Chang H-Y, Yu T-H. Relationship between early physician follow-up and 30-day readmission after acute myocardial infarction and heart failure. Plos One. 2017;12(1):e0170061.

6. Kaplan RM, Koehler J, Zieger PD, et al. Stroke risk as a function of atrial fibrillation duration and CHA2DS2-VASc score. Circulation. 2019;140(20):1639-46.

7. Balan P, Zhao Y, Johnson S, et al. The Society of Thoracic Surgery Risk Score as a predictor of 30-day mortality in transcatheter vs surgical aortic valve replacement: a single-center experience and its implications for the development of a TAVR risk-prediction model. J Invasive Cardiol. 2017;29(3):109-14.

8. Smith LN, Makam AN, Darden D, et al. Acute myocardial infarction readmission risk prediction models: A systematic review of model performance. Circ Cardiovasc Qual Outcomes9.9. 2018;11(1):e003885.

9. Baker H, Oliver-McNeil S, Deng L, Hummel SL. See you in 7: regional hospital collaboration and outcomes in Medicare heart failure patients. JACC Heart Fail. 2015;3(10):765-73.

10. Batten A, Jaeger C, Griffen D, et al. See you in 7: improving acute myocardial infarction follow-up care. BMJ Open Qual. 2018;7(2):e000296.

11. Lee DW, Armistead L, Coleman H, et al. Abstract 15387: Post-discharge follow-up within 14 days reduces 30-day hospital readmission rates in patients with acute myocardial infarction and/or acutely decompensated heart failure. Circulation. 2018;134 (1):A 15387.

12. Thygesen K, Alpert JS, Jaffe AS, et al. Fourth universal definition of myocardial infarction. Circulation. 2018;138 (20):e:618-51.

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Healthcare Encounter and Financial Impact of COVID-19 on Children’s Hospitals

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Healthcare Encounter and Financial Impact of COVID-19 on Children’s Hospitals

To benefit patients and the public health of their communities, children’s hospitals across the United States prepared for and responded to COVID-19 by conserving personal protective equipment, suspending noncritical in-person healthcare encounters (including outpatient visits and elective surgeries), and implementing socially distanced essential care.1,2 These measures were promptly instituted during a time of both substantial uncertainty about the pandemic’s behavior in children—including its severity and duration—and extreme variation in local and state governments’ responses to the pandemic.

Congruent with other healthcare institutions, children’s hospitals calibrated their clinical operations to the evolving nature of the pandemic, prioritizing the safety of patients and staff while striving to maintain financial viability in the setting of increased costs and decreased revenue. In some cases, children’s hospitals aided adult hospitals and health systems by admitting young and middle-aged adult patients and by centralizing all pediatric patients requiring intensive care within a region. These efforts occurred while many children’s hospitals remained the sole source of specialized pediatric care, including care for rare complex health problems.

As the COVID-19 pandemic continues, there is a critical need to assess how the initial phase of the pandemic affected healthcare encounters and related finances in children’s hospitals. Understanding these trends will position children’s hospitals to project and prepare for subsequent COVID-19 surges, as well as future related public health crises that necessitate widespread social distancing. Therefore, we compared year-over-year trends in healthcare encounters and hospital charges across US children’s hospitals before and during the COVID-19 pandemic, focusing on the beginning of COVID-19 in the United States, which was defined as February through June 2020.

METHODS

This is a retrospective analysis of 26 children’s hospitals (22 freestanding, 4 nonfreestanding) from all US regions (12 South, 7 Midwest, 5 West, 2 Northeast) contributing encounter and financial data to the PROSPECT database (Children’s Hospital Association, Lenexa, Kansas) from February 1 to June 30 in both 2019 (before COVID-19) and 2020 (during COVID-19). In response to COVID-19, hospitals participating in PROSPECT increased the efficiency of data centralization and reporting in 2020 during the period February 1 to June 30 to expedite analysis and dissemination of findings.

The main outcome measures were the percentage of change in weekly encounters (inpatient bed-days, emergency department [ED] visits, and surgeries) and inflation-adjusted charges (categorized as inpatient care and outpatient care, such as ambulatory surgery, clinics, and ED visits) before vs during COVID-19. Number of encounters and charges were compared using the Wilcoxon signed-rank test. The distribution of weekly change in outcome measures from 2019 vs 2020 across hospitals was reported with medians and interquartile ranges (IQRs). The threshold of statistical significance was set at P < .05. All analyses were performed with SAS version 9.4 (SAS Institute). This study was considered exempt from human subjects research by the Institutional Review Board of Children’s Mercy Hospital (Kansas City, Missouri).

RESULTS

All 26 children’s hospitals experienced similar trends in healthcare encounters and charges during the study period (Figure and Table). From February 1 to March 10, 2020, the volume of healthcare encounters in the children’s hospitals remained the same as that for the same period in 2019 (P > .1) (Figure).

February Through June Trends in 2019 vs 2020 for Inpatient Bed-Days, Emergency Department Visits, and Surgeries in 26 US Children’s Hospitals
Compared with 2019, a significant decrease in healthcare encounters began around the week of March 18, 2020, with a nadir observed around April 15. Although the timing of the nadir was similar across health services, its magnitude varied. Inpatient bed-days, ED visits, and surgeries were lower than in 2019 by a median of 36%, 65%, and 77%, respectively, per hospital during the week of the nadir. Following the nadir, inpatient bed-days and ED encounters increased modestly, returning to –12% and –25% of 2019 volumes by June 30. Surgery encounters increased more intensely, returning to –13% of 2019 volumes by June 30. Compared with 2019, a median 2,091 (IQR, 1,306-3,564) fewer surgeries were performed during the study period in 2020.

Trends in Charges of Health Services in 26 US Children’s Hospitals: February Through June in 2019 vs 2020

Charges that accrued from February 1 to June 30 were lower in 2020 by a median 23.6% (IQR, –28.7% to –19.1%) per children’s hospital than they were in 2019, corresponding to a median decrease of $276.3 million (IQR, $404.0-$126.0 million) in charges per hospital (Table). Forty percent of this decrease was attributable to decreased charges resulting from fewer inpatient healthcare encounters.

DISCUSSION

During the initial phase of the COVID-19 pandemic in the United States, children’s hospitals experienced a substantial decrease in healthcare encounters and charges. Greater decreases were observed for ED visits and surgery encounters than for inpatient bed-days. Nonetheless, inpatient bed-days decreased by more than one-third, consistent with the decrease in inpatient resource use reported for adult hospitals.3 Remarkably, these trends were consistent across children’s hospitals, despite variation in the content and installation of and adherence with social distancing policies in their surrounding local areas.

These findings beg the question of how well children’s hospitals are positioned to weather a recurrent surge in COVID-19. Because the severity of illness of COVID-19 has been lower to date in the pediatric vs adult populations, an increase in COVID-19-related visits to EDs and admissions to offset the decreased resource use of other pediatric healthcare problems is not anticipated. Existing hospital financial reserves as well as federal aid from the Coronavirus Aid, Relief, and Economic Security Act that helped mitigate the initial encounter and financial losses during the beginning of COVID-19 may not be readily available over time.4,5 Certainly, the findings from the current study support continued lobbying for additional state and federal funds allocated through future relief packages to children’s hospitals.

Additional approaches to financial solvency in children’s hospitals during the sustained COVID-19 pandemic include addressing surgical backlogs and sharing best practices for safe and sustained reopening of clinical operations and financial practices across institutions. Although the PROSPECT database does not contain information on the types of surgeries present within this backlog, our experiences suggest that both same-day and inpatient elective surgeries have been affected, especially lengthy procedures (eg, spinal fusion for neuromuscular scoliosis). Spread and scale of feasible and efficient solutions to reengineer and expand patient capacities and throughput for operating rooms, postanesthesia recovery areas, and intensive care and floor units are needed. Enhanced analytics that accurately predict postoperative length of hospital stay, coupled with early recovery after surgery clinical protocols, could help optimize hospital bed management. Effective ways to convert hospital rooms from single to double occupancy, to manage family visitation, and to proactively test asymptomatic patients, family, and hospital staff will mitigate continued COVID-19 penetration through children’s hospitals.

One important limitation of the current study is the measurement of hospitals’ charges. The charge data were not positioned to comprehensively measure each hospital’s financial state during the COVID-19 pandemic. However, the decrease in hospital charges reported by the children’s hospitals in the current study is comparable with the financial losses reported for many adult hospitals during the pandemic.6,7 It is important to recognize that the amount of the charges may not be equivalent to the cost of care or revenue collected by the hospitals. PROSPECT does not contain information on cost, and current cost-to-charge ratios are based on historical (ie, pre-COVID-19) data; therefore, they do not account for increased cost of personal protective equipment and other related costs that occurred during the pandemic, which makes use of these ratios challenging. Nevertheless, it is possible that the relative difference in costs incurred and revenue collected before and during COVID-19 may have been similar to the differences observed in hospital charges.

CONCLUSION

Children’s hospitals’ ability to serve the nation’s pediatric patients depends on the success of the hospitals’ plans to manage current and future COVID-19 surges and to reopen and recover from the surges that have passed. Additional investigation is needed to identify best operational and financial practices among children’s hospitals that have enabled them to endure the COVID-19 pandemic.

References

1. COVID-19: ways to prepare your children’s hospital now. Children’s Hospital Association. March 12, 2020. Accessed June 30, 2020. https://www.childrenshospitals.org/Newsroom/Childrens-Hospitals-Today/Articles/2020/03/COVID-19-11-Ways-to-Prepare-Your-Hospital-Now
2. Chopra V, Toner E, Waldhorn R, Washer L. How should U.S. hospitals prepare for coronavirus disease 2019 (COVID-19)? Ann Intern Med. 2020;172(9):621-622. https://doi.org/10.7326/m20-0907
3. Oseran AS, Nash D, Kim C, et al. Changes in hospital admissions for urgent conditions during COVID-19 pandemic. Am J Manag Care. 2020;26(8):327-328. https://doi.org/10.37765/ajmc.2020.43837
4. Coronavirus Aid, Relief, and Economic Security Act or the CARES Act. 15 USC Chapter 116 (2020). Pub L No. 116-36, 134 Stat 281. https://www.congress.gov/bill/116th-congress/house-bill/748
5. The Coronavirus Aid, Relief, and Economic Security (CARES) Act Provider Relief Fund: general information. US Department of Health & Human Services. June 25, 2020. Accessed June 30, 2020. https://www.hhs.gov/coronavirus/cares-act-provider-relief-fund/general-information/index.html
6. Hospitals and health systems face unprecedented financial pressures due to COVID-19. American Hospital Association. May 2020. Accessed July 13, 2020. https://www.aha.org/system/files/media/file/2020/05/aha-covid19-financial-impact-0520-FINAL.pdf
7. Birkmeyer J, Barnato A, Birkmeyer N, Bessler R, Skinner J. The impact of the COVID-19 pandemic on hospital admissions in the United States. Health Aff (Millwood). 2020;39(11):2010-2017. https://doi.org/10.1377/hlthaff.2020.00980

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1Children’s Mercy Kansas City, Kansas City, Missouri; 2Children’s Hospital Association, Lenexa, Kansas; 3Division of Hospital Medicine, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio; 4University of Cincinnati College of Medicine, Cincinnati, Ohio; 5Division of Hospital Medicine, Department of Pediatrics, Vanderbilt University School of Medicine, Nashville, Tennessee; 6Division of Hospital Medicine, Department of Pediatrics, Monroe Carell Jr Children’s Hospital, Nashville, Tennessee; 7Nationwide Children’s Hospital, Columbus, Ohio; 8Complex Care, Division of General Pediatrics, Boston Children’s Hospital, Boston, Massachusetts; 9Department of Pediatrics, Harvard Medical School, Boston, Massachusetts.

Disclosures

Dr Williams is the recipient of grants from the Centers for Disease Control and Prevention, National Institutes of Health, and Agency for Healthcare Research and Quality, payable to his institution, and nonfinancial support to the institution from Biomerieux, all outside the submitted work. Dr Auger is the recipient of a K08 grant from the National Institutes of Health Agency for Healthcare Research and Quality, payable to her institution. The other authors have nothing to disclose.

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1Children’s Mercy Kansas City, Kansas City, Missouri; 2Children’s Hospital Association, Lenexa, Kansas; 3Division of Hospital Medicine, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio; 4University of Cincinnati College of Medicine, Cincinnati, Ohio; 5Division of Hospital Medicine, Department of Pediatrics, Vanderbilt University School of Medicine, Nashville, Tennessee; 6Division of Hospital Medicine, Department of Pediatrics, Monroe Carell Jr Children’s Hospital, Nashville, Tennessee; 7Nationwide Children’s Hospital, Columbus, Ohio; 8Complex Care, Division of General Pediatrics, Boston Children’s Hospital, Boston, Massachusetts; 9Department of Pediatrics, Harvard Medical School, Boston, Massachusetts.

Disclosures

Dr Williams is the recipient of grants from the Centers for Disease Control and Prevention, National Institutes of Health, and Agency for Healthcare Research and Quality, payable to his institution, and nonfinancial support to the institution from Biomerieux, all outside the submitted work. Dr Auger is the recipient of a K08 grant from the National Institutes of Health Agency for Healthcare Research and Quality, payable to her institution. The other authors have nothing to disclose.

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1Children’s Mercy Kansas City, Kansas City, Missouri; 2Children’s Hospital Association, Lenexa, Kansas; 3Division of Hospital Medicine, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio; 4University of Cincinnati College of Medicine, Cincinnati, Ohio; 5Division of Hospital Medicine, Department of Pediatrics, Vanderbilt University School of Medicine, Nashville, Tennessee; 6Division of Hospital Medicine, Department of Pediatrics, Monroe Carell Jr Children’s Hospital, Nashville, Tennessee; 7Nationwide Children’s Hospital, Columbus, Ohio; 8Complex Care, Division of General Pediatrics, Boston Children’s Hospital, Boston, Massachusetts; 9Department of Pediatrics, Harvard Medical School, Boston, Massachusetts.

Disclosures

Dr Williams is the recipient of grants from the Centers for Disease Control and Prevention, National Institutes of Health, and Agency for Healthcare Research and Quality, payable to his institution, and nonfinancial support to the institution from Biomerieux, all outside the submitted work. Dr Auger is the recipient of a K08 grant from the National Institutes of Health Agency for Healthcare Research and Quality, payable to her institution. The other authors have nothing to disclose.

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To benefit patients and the public health of their communities, children’s hospitals across the United States prepared for and responded to COVID-19 by conserving personal protective equipment, suspending noncritical in-person healthcare encounters (including outpatient visits and elective surgeries), and implementing socially distanced essential care.1,2 These measures were promptly instituted during a time of both substantial uncertainty about the pandemic’s behavior in children—including its severity and duration—and extreme variation in local and state governments’ responses to the pandemic.

Congruent with other healthcare institutions, children’s hospitals calibrated their clinical operations to the evolving nature of the pandemic, prioritizing the safety of patients and staff while striving to maintain financial viability in the setting of increased costs and decreased revenue. In some cases, children’s hospitals aided adult hospitals and health systems by admitting young and middle-aged adult patients and by centralizing all pediatric patients requiring intensive care within a region. These efforts occurred while many children’s hospitals remained the sole source of specialized pediatric care, including care for rare complex health problems.

As the COVID-19 pandemic continues, there is a critical need to assess how the initial phase of the pandemic affected healthcare encounters and related finances in children’s hospitals. Understanding these trends will position children’s hospitals to project and prepare for subsequent COVID-19 surges, as well as future related public health crises that necessitate widespread social distancing. Therefore, we compared year-over-year trends in healthcare encounters and hospital charges across US children’s hospitals before and during the COVID-19 pandemic, focusing on the beginning of COVID-19 in the United States, which was defined as February through June 2020.

METHODS

This is a retrospective analysis of 26 children’s hospitals (22 freestanding, 4 nonfreestanding) from all US regions (12 South, 7 Midwest, 5 West, 2 Northeast) contributing encounter and financial data to the PROSPECT database (Children’s Hospital Association, Lenexa, Kansas) from February 1 to June 30 in both 2019 (before COVID-19) and 2020 (during COVID-19). In response to COVID-19, hospitals participating in PROSPECT increased the efficiency of data centralization and reporting in 2020 during the period February 1 to June 30 to expedite analysis and dissemination of findings.

The main outcome measures were the percentage of change in weekly encounters (inpatient bed-days, emergency department [ED] visits, and surgeries) and inflation-adjusted charges (categorized as inpatient care and outpatient care, such as ambulatory surgery, clinics, and ED visits) before vs during COVID-19. Number of encounters and charges were compared using the Wilcoxon signed-rank test. The distribution of weekly change in outcome measures from 2019 vs 2020 across hospitals was reported with medians and interquartile ranges (IQRs). The threshold of statistical significance was set at P < .05. All analyses were performed with SAS version 9.4 (SAS Institute). This study was considered exempt from human subjects research by the Institutional Review Board of Children’s Mercy Hospital (Kansas City, Missouri).

RESULTS

All 26 children’s hospitals experienced similar trends in healthcare encounters and charges during the study period (Figure and Table). From February 1 to March 10, 2020, the volume of healthcare encounters in the children’s hospitals remained the same as that for the same period in 2019 (P > .1) (Figure).

February Through June Trends in 2019 vs 2020 for Inpatient Bed-Days, Emergency Department Visits, and Surgeries in 26 US Children’s Hospitals
Compared with 2019, a significant decrease in healthcare encounters began around the week of March 18, 2020, with a nadir observed around April 15. Although the timing of the nadir was similar across health services, its magnitude varied. Inpatient bed-days, ED visits, and surgeries were lower than in 2019 by a median of 36%, 65%, and 77%, respectively, per hospital during the week of the nadir. Following the nadir, inpatient bed-days and ED encounters increased modestly, returning to –12% and –25% of 2019 volumes by June 30. Surgery encounters increased more intensely, returning to –13% of 2019 volumes by June 30. Compared with 2019, a median 2,091 (IQR, 1,306-3,564) fewer surgeries were performed during the study period in 2020.

Trends in Charges of Health Services in 26 US Children’s Hospitals: February Through June in 2019 vs 2020

Charges that accrued from February 1 to June 30 were lower in 2020 by a median 23.6% (IQR, –28.7% to –19.1%) per children’s hospital than they were in 2019, corresponding to a median decrease of $276.3 million (IQR, $404.0-$126.0 million) in charges per hospital (Table). Forty percent of this decrease was attributable to decreased charges resulting from fewer inpatient healthcare encounters.

DISCUSSION

During the initial phase of the COVID-19 pandemic in the United States, children’s hospitals experienced a substantial decrease in healthcare encounters and charges. Greater decreases were observed for ED visits and surgery encounters than for inpatient bed-days. Nonetheless, inpatient bed-days decreased by more than one-third, consistent with the decrease in inpatient resource use reported for adult hospitals.3 Remarkably, these trends were consistent across children’s hospitals, despite variation in the content and installation of and adherence with social distancing policies in their surrounding local areas.

These findings beg the question of how well children’s hospitals are positioned to weather a recurrent surge in COVID-19. Because the severity of illness of COVID-19 has been lower to date in the pediatric vs adult populations, an increase in COVID-19-related visits to EDs and admissions to offset the decreased resource use of other pediatric healthcare problems is not anticipated. Existing hospital financial reserves as well as federal aid from the Coronavirus Aid, Relief, and Economic Security Act that helped mitigate the initial encounter and financial losses during the beginning of COVID-19 may not be readily available over time.4,5 Certainly, the findings from the current study support continued lobbying for additional state and federal funds allocated through future relief packages to children’s hospitals.

Additional approaches to financial solvency in children’s hospitals during the sustained COVID-19 pandemic include addressing surgical backlogs and sharing best practices for safe and sustained reopening of clinical operations and financial practices across institutions. Although the PROSPECT database does not contain information on the types of surgeries present within this backlog, our experiences suggest that both same-day and inpatient elective surgeries have been affected, especially lengthy procedures (eg, spinal fusion for neuromuscular scoliosis). Spread and scale of feasible and efficient solutions to reengineer and expand patient capacities and throughput for operating rooms, postanesthesia recovery areas, and intensive care and floor units are needed. Enhanced analytics that accurately predict postoperative length of hospital stay, coupled with early recovery after surgery clinical protocols, could help optimize hospital bed management. Effective ways to convert hospital rooms from single to double occupancy, to manage family visitation, and to proactively test asymptomatic patients, family, and hospital staff will mitigate continued COVID-19 penetration through children’s hospitals.

One important limitation of the current study is the measurement of hospitals’ charges. The charge data were not positioned to comprehensively measure each hospital’s financial state during the COVID-19 pandemic. However, the decrease in hospital charges reported by the children’s hospitals in the current study is comparable with the financial losses reported for many adult hospitals during the pandemic.6,7 It is important to recognize that the amount of the charges may not be equivalent to the cost of care or revenue collected by the hospitals. PROSPECT does not contain information on cost, and current cost-to-charge ratios are based on historical (ie, pre-COVID-19) data; therefore, they do not account for increased cost of personal protective equipment and other related costs that occurred during the pandemic, which makes use of these ratios challenging. Nevertheless, it is possible that the relative difference in costs incurred and revenue collected before and during COVID-19 may have been similar to the differences observed in hospital charges.

CONCLUSION

Children’s hospitals’ ability to serve the nation’s pediatric patients depends on the success of the hospitals’ plans to manage current and future COVID-19 surges and to reopen and recover from the surges that have passed. Additional investigation is needed to identify best operational and financial practices among children’s hospitals that have enabled them to endure the COVID-19 pandemic.

To benefit patients and the public health of their communities, children’s hospitals across the United States prepared for and responded to COVID-19 by conserving personal protective equipment, suspending noncritical in-person healthcare encounters (including outpatient visits and elective surgeries), and implementing socially distanced essential care.1,2 These measures were promptly instituted during a time of both substantial uncertainty about the pandemic’s behavior in children—including its severity and duration—and extreme variation in local and state governments’ responses to the pandemic.

Congruent with other healthcare institutions, children’s hospitals calibrated their clinical operations to the evolving nature of the pandemic, prioritizing the safety of patients and staff while striving to maintain financial viability in the setting of increased costs and decreased revenue. In some cases, children’s hospitals aided adult hospitals and health systems by admitting young and middle-aged adult patients and by centralizing all pediatric patients requiring intensive care within a region. These efforts occurred while many children’s hospitals remained the sole source of specialized pediatric care, including care for rare complex health problems.

As the COVID-19 pandemic continues, there is a critical need to assess how the initial phase of the pandemic affected healthcare encounters and related finances in children’s hospitals. Understanding these trends will position children’s hospitals to project and prepare for subsequent COVID-19 surges, as well as future related public health crises that necessitate widespread social distancing. Therefore, we compared year-over-year trends in healthcare encounters and hospital charges across US children’s hospitals before and during the COVID-19 pandemic, focusing on the beginning of COVID-19 in the United States, which was defined as February through June 2020.

METHODS

This is a retrospective analysis of 26 children’s hospitals (22 freestanding, 4 nonfreestanding) from all US regions (12 South, 7 Midwest, 5 West, 2 Northeast) contributing encounter and financial data to the PROSPECT database (Children’s Hospital Association, Lenexa, Kansas) from February 1 to June 30 in both 2019 (before COVID-19) and 2020 (during COVID-19). In response to COVID-19, hospitals participating in PROSPECT increased the efficiency of data centralization and reporting in 2020 during the period February 1 to June 30 to expedite analysis and dissemination of findings.

The main outcome measures were the percentage of change in weekly encounters (inpatient bed-days, emergency department [ED] visits, and surgeries) and inflation-adjusted charges (categorized as inpatient care and outpatient care, such as ambulatory surgery, clinics, and ED visits) before vs during COVID-19. Number of encounters and charges were compared using the Wilcoxon signed-rank test. The distribution of weekly change in outcome measures from 2019 vs 2020 across hospitals was reported with medians and interquartile ranges (IQRs). The threshold of statistical significance was set at P < .05. All analyses were performed with SAS version 9.4 (SAS Institute). This study was considered exempt from human subjects research by the Institutional Review Board of Children’s Mercy Hospital (Kansas City, Missouri).

RESULTS

All 26 children’s hospitals experienced similar trends in healthcare encounters and charges during the study period (Figure and Table). From February 1 to March 10, 2020, the volume of healthcare encounters in the children’s hospitals remained the same as that for the same period in 2019 (P > .1) (Figure).

February Through June Trends in 2019 vs 2020 for Inpatient Bed-Days, Emergency Department Visits, and Surgeries in 26 US Children’s Hospitals
Compared with 2019, a significant decrease in healthcare encounters began around the week of March 18, 2020, with a nadir observed around April 15. Although the timing of the nadir was similar across health services, its magnitude varied. Inpatient bed-days, ED visits, and surgeries were lower than in 2019 by a median of 36%, 65%, and 77%, respectively, per hospital during the week of the nadir. Following the nadir, inpatient bed-days and ED encounters increased modestly, returning to –12% and –25% of 2019 volumes by June 30. Surgery encounters increased more intensely, returning to –13% of 2019 volumes by June 30. Compared with 2019, a median 2,091 (IQR, 1,306-3,564) fewer surgeries were performed during the study period in 2020.

Trends in Charges of Health Services in 26 US Children’s Hospitals: February Through June in 2019 vs 2020

Charges that accrued from February 1 to June 30 were lower in 2020 by a median 23.6% (IQR, –28.7% to –19.1%) per children’s hospital than they were in 2019, corresponding to a median decrease of $276.3 million (IQR, $404.0-$126.0 million) in charges per hospital (Table). Forty percent of this decrease was attributable to decreased charges resulting from fewer inpatient healthcare encounters.

DISCUSSION

During the initial phase of the COVID-19 pandemic in the United States, children’s hospitals experienced a substantial decrease in healthcare encounters and charges. Greater decreases were observed for ED visits and surgery encounters than for inpatient bed-days. Nonetheless, inpatient bed-days decreased by more than one-third, consistent with the decrease in inpatient resource use reported for adult hospitals.3 Remarkably, these trends were consistent across children’s hospitals, despite variation in the content and installation of and adherence with social distancing policies in their surrounding local areas.

These findings beg the question of how well children’s hospitals are positioned to weather a recurrent surge in COVID-19. Because the severity of illness of COVID-19 has been lower to date in the pediatric vs adult populations, an increase in COVID-19-related visits to EDs and admissions to offset the decreased resource use of other pediatric healthcare problems is not anticipated. Existing hospital financial reserves as well as federal aid from the Coronavirus Aid, Relief, and Economic Security Act that helped mitigate the initial encounter and financial losses during the beginning of COVID-19 may not be readily available over time.4,5 Certainly, the findings from the current study support continued lobbying for additional state and federal funds allocated through future relief packages to children’s hospitals.

Additional approaches to financial solvency in children’s hospitals during the sustained COVID-19 pandemic include addressing surgical backlogs and sharing best practices for safe and sustained reopening of clinical operations and financial practices across institutions. Although the PROSPECT database does not contain information on the types of surgeries present within this backlog, our experiences suggest that both same-day and inpatient elective surgeries have been affected, especially lengthy procedures (eg, spinal fusion for neuromuscular scoliosis). Spread and scale of feasible and efficient solutions to reengineer and expand patient capacities and throughput for operating rooms, postanesthesia recovery areas, and intensive care and floor units are needed. Enhanced analytics that accurately predict postoperative length of hospital stay, coupled with early recovery after surgery clinical protocols, could help optimize hospital bed management. Effective ways to convert hospital rooms from single to double occupancy, to manage family visitation, and to proactively test asymptomatic patients, family, and hospital staff will mitigate continued COVID-19 penetration through children’s hospitals.

One important limitation of the current study is the measurement of hospitals’ charges. The charge data were not positioned to comprehensively measure each hospital’s financial state during the COVID-19 pandemic. However, the decrease in hospital charges reported by the children’s hospitals in the current study is comparable with the financial losses reported for many adult hospitals during the pandemic.6,7 It is important to recognize that the amount of the charges may not be equivalent to the cost of care or revenue collected by the hospitals. PROSPECT does not contain information on cost, and current cost-to-charge ratios are based on historical (ie, pre-COVID-19) data; therefore, they do not account for increased cost of personal protective equipment and other related costs that occurred during the pandemic, which makes use of these ratios challenging. Nevertheless, it is possible that the relative difference in costs incurred and revenue collected before and during COVID-19 may have been similar to the differences observed in hospital charges.

CONCLUSION

Children’s hospitals’ ability to serve the nation’s pediatric patients depends on the success of the hospitals’ plans to manage current and future COVID-19 surges and to reopen and recover from the surges that have passed. Additional investigation is needed to identify best operational and financial practices among children’s hospitals that have enabled them to endure the COVID-19 pandemic.

References

1. COVID-19: ways to prepare your children’s hospital now. Children’s Hospital Association. March 12, 2020. Accessed June 30, 2020. https://www.childrenshospitals.org/Newsroom/Childrens-Hospitals-Today/Articles/2020/03/COVID-19-11-Ways-to-Prepare-Your-Hospital-Now
2. Chopra V, Toner E, Waldhorn R, Washer L. How should U.S. hospitals prepare for coronavirus disease 2019 (COVID-19)? Ann Intern Med. 2020;172(9):621-622. https://doi.org/10.7326/m20-0907
3. Oseran AS, Nash D, Kim C, et al. Changes in hospital admissions for urgent conditions during COVID-19 pandemic. Am J Manag Care. 2020;26(8):327-328. https://doi.org/10.37765/ajmc.2020.43837
4. Coronavirus Aid, Relief, and Economic Security Act or the CARES Act. 15 USC Chapter 116 (2020). Pub L No. 116-36, 134 Stat 281. https://www.congress.gov/bill/116th-congress/house-bill/748
5. The Coronavirus Aid, Relief, and Economic Security (CARES) Act Provider Relief Fund: general information. US Department of Health & Human Services. June 25, 2020. Accessed June 30, 2020. https://www.hhs.gov/coronavirus/cares-act-provider-relief-fund/general-information/index.html
6. Hospitals and health systems face unprecedented financial pressures due to COVID-19. American Hospital Association. May 2020. Accessed July 13, 2020. https://www.aha.org/system/files/media/file/2020/05/aha-covid19-financial-impact-0520-FINAL.pdf
7. Birkmeyer J, Barnato A, Birkmeyer N, Bessler R, Skinner J. The impact of the COVID-19 pandemic on hospital admissions in the United States. Health Aff (Millwood). 2020;39(11):2010-2017. https://doi.org/10.1377/hlthaff.2020.00980

References

1. COVID-19: ways to prepare your children’s hospital now. Children’s Hospital Association. March 12, 2020. Accessed June 30, 2020. https://www.childrenshospitals.org/Newsroom/Childrens-Hospitals-Today/Articles/2020/03/COVID-19-11-Ways-to-Prepare-Your-Hospital-Now
2. Chopra V, Toner E, Waldhorn R, Washer L. How should U.S. hospitals prepare for coronavirus disease 2019 (COVID-19)? Ann Intern Med. 2020;172(9):621-622. https://doi.org/10.7326/m20-0907
3. Oseran AS, Nash D, Kim C, et al. Changes in hospital admissions for urgent conditions during COVID-19 pandemic. Am J Manag Care. 2020;26(8):327-328. https://doi.org/10.37765/ajmc.2020.43837
4. Coronavirus Aid, Relief, and Economic Security Act or the CARES Act. 15 USC Chapter 116 (2020). Pub L No. 116-36, 134 Stat 281. https://www.congress.gov/bill/116th-congress/house-bill/748
5. The Coronavirus Aid, Relief, and Economic Security (CARES) Act Provider Relief Fund: general information. US Department of Health & Human Services. June 25, 2020. Accessed June 30, 2020. https://www.hhs.gov/coronavirus/cares-act-provider-relief-fund/general-information/index.html
6. Hospitals and health systems face unprecedented financial pressures due to COVID-19. American Hospital Association. May 2020. Accessed July 13, 2020. https://www.aha.org/system/files/media/file/2020/05/aha-covid19-financial-impact-0520-FINAL.pdf
7. Birkmeyer J, Barnato A, Birkmeyer N, Bessler R, Skinner J. The impact of the COVID-19 pandemic on hospital admissions in the United States. Health Aff (Millwood). 2020;39(11):2010-2017. https://doi.org/10.1377/hlthaff.2020.00980

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Variation in COVID-19 Mortality Across 117 US Hospitals in High- and Low-Burden Settings

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It is clear that certain patient-level factors, such as age, sex, and comorbidities, predict outcomes of SARS-CoV-2 infection.1,2 Less is known about whether hospital-level factors, including surges of patients with COVID-19, are associated with patient outcomes.

In a multicenter cohort study of 2,215 patients with COVID-19 in 65 intensive care units (ICU) across the United States, mortality rates varied widely (6.6%-80.8%), with improved survival for patients admitted to a hospital with more (>100) rather than fewer (<50) ICU beds.3 A different study found that at the state level, COVID-19 mortality increased with increasing COVID-19 admissions.4 Together, these studies suggest that surges in COVID-19 patient volume may be associated with excess mortality. However, the first study was restricted to the ICU population, limiting generalizability, and did not consider admission volume, only ICU bed count. Meanwhile, the second study considered both hospital capacity and patient volume, but it describes a relatively small sample, did not adjust for patient-level predictors of mortality, and does not report outcomes at the hospital level.

Here, we used a large dataset to compare in-hospital mortality rates for patients with COVID-19 across US hospitals, hypothesizing that mortality would be higher in hospitals with the highest burden of COVID-19 admissions. By adjusting for patient-level predictors of mortality and normalizing admission volume for hospital size, we are able to describe residual variability in mortality that may be attributable to differences in COVID-19 patient volume.

METHODS

We included patients with an International Statistical Classification of Diseases, Tenth Revision (ICD)-10 diagnosis of COVID-19 (U07.1) who were admitted to a US hospital that contracts with CarePort Health.5 CarePort is a platform for discharge planning and care coordination that contracts with hospitals in all US regions and auto-extracts data using interface feeds.

We restricted the population to patients admitted between April 1 and April 30, 2020, after a new ICD-10 code for confirmed COVID-19 infection became available, and to hospitals that provided real-time ICD-10 data and pertinent demographic information and could be linked to Centers for Medicare & Medicaid Services (CMS) data by National Provider Identifier. We assumed that the 145 patients (1.0%) who remained hospitalized at 5 weeks all survived. For the 5.9% of patients with multiple admissions during the study period, we included only the first admission with a diagnosis code for COVID-19.

We adjusted for patient age, sex, and the 31 comorbidities in the Elixhauser index, defined by ICD-10 codes. This set of comorbidities includes those previously associated with COVID-19 survival.1,2,6 Unfortunately, inconsistent reporting of vital signs and laboratory data precluded adjusting for acute illness severity. For those patients whose residence zip code was known, we report the racial breakdown (White vs non-White) and adjusted gross income (AGI), based on linked information from the 2018 American Community Survey.7

We defined COVID-19 burden as the quotient of COVID-19 admissions in April 2020 and each hospital’s certified bed count, as reported to the CMS.8 This allowed us to normalize COVID-19 patient volume for variation in hospital size, acknowledging that admitting 10 patients with COVID-19 to a 1,000-bed hospital is different from admitting 10 patients with COVID-19 to a 20-bed hospital. Certified bed count seemed the ideal denominator because it excludes beds not readily deployable to care for patients with COVID-19 (eg, radiology suites, labor and delivery rooms).

We computed hospital-specific adjusted mortality proportions and 95% confidence intervals based on hierarchical multivariable logistic regression, adjusting for age, sex, and comorbidities, and a random effect for each hospital.9,10 Hypothesizing that there may be a threshold of burden beyond which mortality begins to rise, we compared the in-hospital mortality rate at hospitals in the highest quintile of COVID-19 burden to all other hospitals.

We conducted eight post-hoc sensitivity analyses: (1) restricting the study population to patients aged 75 years and older; (2) restricting study hospitals to those with at least 100 beds and 20 COVID-19 admissions; (3) assuming that all patients who remained hospitalized at 5 weeks had died; (4) using each patient’s last admission during the month of April rather than the first; sequentially incorporating (5) zip code–level information on race (limited to White, non-White) and (6) AGI (treated as a continuous variable) into our model; (7) computing two burdens for each hospital (one for each half of April) and using whichever was higher; and (8) treating COVID-19 burden as a continuous predictor. Analyses were performed using SAS statistical software, version 9.4 (SAS Institute Inc) using the GLIMMIX procedure. This study was deemed exempt by the University of California, San Francisco Institutional Review Board.

RESULTS

The study population included 14,226 patients with COVID-19 (median age, 66 years [range, 0-110 years]; 45.2% women) at 117 US hospitals. Based on patients’ zip code of residence, we estimate that 47.0% of patients were White and 29.1% Black, and that the mean household AGI was $61,956. Most hospitals were nonprofit (56%) or private (39%), with approximately one quarter coming from each US census region (range, 25 hospitals [21%] in Midwest to 33 hospitals [28%] in Northeast). Nine hospitals (8%) had more than 700 beds, 40 (34%) had 300 to 700 beds, and 68 (58%) had fewer than 300 beds. Thirty-six hospitals (30.8%) admitted fewer than 20 patients with COVID-19, while six hospitals (5.1%) admitted more than 500 such patients. COVID burden ranged from 0.004 to 2.03 admissions per bed.

As of June 5, 2020, 78.1% of patients had been discharged alive, 20.9% had died, and 1.0% remained hospitalized. At the hospital level, the observed mortality ranged from 0% to 44.4%, was 17.1% among hospitals in COVID-19 burden quintiles one through four, and was 22.7% in the highest burden quintile (Table).

Characteristics and Outcomes of 14,226 Patients Admitted to US Hospitals With COVID-19
The 22 hospitals reporting zero deaths admitted a median of six patients with COVID-19 (maximum, 17). After adjustment for age, sex, and comorbidities, the adjusted odds ratio for in-hospital death in the most burdened hospitals was 1.46 (95% CI, 1.07-2.00) compared to hospitals in the bottom four quintiles of burden. The adjusted in-hospital mortality rate for each study hospital is shown in the Figure.

In-Hospital Mortality Rates for Patients With COVID-19 at 117 US Hospitals

Results were similar across multiple sensitivity analyses (see Appendix Table), although the relationship between COVID-19 burden and in-hospital mortality was attenuated and not significant when the sample was restricted to hospitals with at least 100 beds and 20 COVID-19 admissions, or in analyses adjusted for race and AGI.

DISCUSSION

In this study of 14,226 patients with COVID-19 across 117 US hospitals, those patients admitted to the most burdened hospitals had a higher odds of death. This relationship, which persisted after adjusting for age, sex, and comorbid conditions, suggests that a threshold exists at which patient surges may cause excess mortality.

Notably, in sensitivity analyses adjusting for race and AGI, COVID-19 burden was no longer associated with in-hospital mortality and the point estimate was attenuated. This raises the possibility that our primary results are confounded by these factors. However, prior studies of hospitalized patients have not found race to be predictive of mortality, after adjusting for other factors.11,12

We also note that the relationship between COVID-19 burden and mortality was not significant (P = .07) when the sample was restricted to larger hospitals with more than 20 COVID-19 admissions; again, the point estimate was attenuated. This suggests that larger hospitals may be more resilient in the face of patient surges. Whether this is due to increased availability of staff who can be redeployed to patient care (as with researchers at academic centers), increased experience managing severe respiratory failure, or other factors is uncertain.

Interestingly, in-hospital mortality varied widely across study hospitals, even among the most-burdened hospitals. The reasons for this residual variability—after adjusting for age, sex, and comorbidities and stratifying by COVID-19 burden—are uncertain. To the extent that this variability reflects differences in patient management, hospital staffing, or use of investigational or advanced therapies, it will be critical to identify and disseminate any replicable best practices from high-burden hospitals with low mortality rates.

Whereas other reports have often described single-center or regional experiences,13-15 leaving open the possibility that their results were highly influenced by the local nature of the pandemic in their respective settings, our report from a large sample of hospitals across the United States in high- and low-burden settings provides a more generalizable description of mortality rates for hospitalized patients. Additional study strengths include our adjustment for comorbidities known to be associated with COVID-19 survival, the reporting of definitive outcomes for 99% of patients, and the inclusion of multiple sensitivity analyses to assess the stability of findings.

Our principal limitation is the inability to adjust for severity of acute illness due to inconsistent reporting of laboratory and vital signs data from study hospitals and missing information on interhospital transfers. While our adjusted analyses clearly suggest an association between COVID-19 burden and patient outcomes, our results may still be confounded by differences in illness severity at study hospitals. Thus, our findings should be considered hypothesis-generating and will require confirmation in future studies that include adjustment for acute illness severity.

Other limitations of our study include overrepresentation of large urban hospitals in the Northeast, although this represents the geography of the US pandemic during the study period. Our adjustment for race/ethnicity and socioeconomic status was limited in that we only had zip code-of-residence level information, did not know the zip code of residence for one quarter of study patients, and had to bifurcate the population into White/non-White categories. Finally, our definition of burden does not account for hospital resources, including staffing, ICU capacity, and the availability of advanced or investigational therapies.

CONCLUSION

In this study of 14,226 patients with COVID-19 admitted to 1 of 117 US hospitals, we found that the odds of in-hospital mortality were higher in hospitals that had the highest burden of COVID-19 admissions. This relationship, which persisted after adjustment for age, sex, and comorbid conditions, suggests that patient surges may be an independent risk factor for in-hospital death among patients with COVID-19.

ACKNOWLEGMENTS

The authors thank Bocheng Jing, MS, Senior Statistician at the UCSF Pepper Center, for providing code to identify Elixhauser conditions from ICD-10 data; and Scott Kerber, BS, and Scott Magnoni, MS, both of CarePort Health, for assistance with data extraction. They were not compensated for this work beyond their regular salaries.

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References

1. Evidence used to update the list of underlying medical conditions that increase a person’s risk of severe illness from COVID-19. Centers for Disease Control and Prevention. Updated November 2, 2020. Accessed December 29, 2020. https://www.cdc.gov/coronavirus/2019-ncov/need-extra-precautions/evidence-table.html
2. Cummings MJ, Baldwin MR, Abrams D, et al. Epidemiology, clinical course, and outcomes of critically ill adults with COVID-19 in New York City: a prospective cohort study. Lancet. 2020;395(10239):1763-1770. https://doi.org/10.1016/S0140-6736(20)31189-2
3. Gupta S, Hayek SS, Wang W, et al. Factors associated with death in critically ill patients with coronavirus disease 2019 in the US. JAMA Intern Med. 2020;180(11):1-12. https://doi.org/10.1001/jamainternmed.2020.4568
4. Karaca-Mandic P, Sen S, Georgiou A, Zhu Y, Basu A. Association of COVID-19-related hospital use and overall covid-19 mortality in the USA. J Gen Intern Med. 2020:1-3. https://doi.org/10.1007/s11606-020-06084-7
5. ICD-10-CM official coding and reporting guidelines April 1, 2020 through September 30, 2020. Centers for Disease Control and Prevention. Accessed June 2, 2020. https://www.cdc.gov/nchs/data/icd/COVID-19-guidelines-final.pdf
6. Quan H, Sundararajan V, Halfon P, et al. Coding algorithms for defining comorbidities in ICD-9-CM and ICD-10 administrative data. Med Care. 2005;43(11):1130-1139. https://doi.org/10.1097/01.mlr.0000182534.19832.83
7. About the American Community Survey. United States Census Bureau. Updated January 4, 2021. Accessed March 2, 2021. https://www.census.gov/programs-surveys/acs/about.html
8. Provider of service files. Centers for Medicare & Medicaid Services. Revised January 15, 2020. Accessed March 2, 2021. https://www.cms.gov/research-statistics-data-systems/provider-services-current-files/2019-pos-file
9. Ash AS, Fienberg SE, Louis TA, et al. Statistical issues in assessing hospital performance. Committee of Presidents of Statistical Societies white paper. January 2012. Accessed March 1, 2021. https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HospitalQualityInits/Downloads/Statistical-Issues-in-Assessing-Hospital-Performance.pdf
10. Bratzler DW, Normand SL, Wang Y, et al. An administrative claims model for profiling hospital 30-day mortality rates for pneumonia patients. PLoS One. 2011;12;6(4):e17401. https://doi.org/10.1371/journal.pone.0017401
11. Garibaldi BT, Fiksel J, Muschelli J, et al. Patient trajectories among persons hospitalized for COVID-19: a cohort study. Ann Intern Med. 2021;174(1):33-41. https://doi.org/10.7326/M20-3905
12. Price-Haywood EG, Burton J, Fort D, Seoane L. Hospitalization and mortality among Black patients and White patients with Covid-19. N Engl J Med. 2020;382(26):2534-2543. https://doi.org/10.1056/NEJMsa2011686
13. Bhatraju PK, Ghassemieh BJ, Nichols M, et al. Covid-19 in critically ill patients in the Seattle region - case series. N Engl J Med. 2020;382(21):2012-2022. https://doi.org/10.1056/NEJMoa2004500
14. Yang X, Yu Y, Xu J, et al. Clinical course and outcomes of critically ill patients with SARS-CoV-2 pneumonia in Wuhan, China: a single-centered, retrospective, observational study. Lancet Respir Med. 2020;8(5):475-481. https://doi.org/10.1016/S2213-2600(20)30079-5
15. Richardson S, Hirsch JS, Narasimhan M, et al. Presenting characteristics, comorbidities, and outcomes among 5700 patients hospitalized with COVID-19 in the New York City area. JAMA. 2020;323(20):2052-2059. https://doi.org/10.1001/jama.2020.6775

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Author and Disclosure Information

1Division of Pulmonary Allergy, Critical Care and Sleep Medicine, University of California, San Francisco, San Francisco, California; 2CarePort Health, Boston, MA; 3Division of Geriatrics, University of California, San Francisco, San Francisco, California; 4Division of Hospital Medicine, University of California, San Francisco, San Francisco, California.

Disclosures

Dr Hu is the chief executive officer of CarePort Health. Mr. Martin is the director of Post-Acute Care Analytics at CarePort Health. No other disclosures were reported.

Funding

Drs Boscardin, Covinsky, and Smith are supported by the UCSF Pepper Center grant P30AG044281. The funder had no role in the design, conduct, or interpretation of the study, or the decision to publish. Dr Covinsky was supported by grants from the National Institute on Aging during the conduct of the study.

Access to Data: Mr Martin had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. The authors would be happy to share statistical code used to generate results.

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1Division of Pulmonary Allergy, Critical Care and Sleep Medicine, University of California, San Francisco, San Francisco, California; 2CarePort Health, Boston, MA; 3Division of Geriatrics, University of California, San Francisco, San Francisco, California; 4Division of Hospital Medicine, University of California, San Francisco, San Francisco, California.

Disclosures

Dr Hu is the chief executive officer of CarePort Health. Mr. Martin is the director of Post-Acute Care Analytics at CarePort Health. No other disclosures were reported.

Funding

Drs Boscardin, Covinsky, and Smith are supported by the UCSF Pepper Center grant P30AG044281. The funder had no role in the design, conduct, or interpretation of the study, or the decision to publish. Dr Covinsky was supported by grants from the National Institute on Aging during the conduct of the study.

Access to Data: Mr Martin had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. The authors would be happy to share statistical code used to generate results.

Author and Disclosure Information

1Division of Pulmonary Allergy, Critical Care and Sleep Medicine, University of California, San Francisco, San Francisco, California; 2CarePort Health, Boston, MA; 3Division of Geriatrics, University of California, San Francisco, San Francisco, California; 4Division of Hospital Medicine, University of California, San Francisco, San Francisco, California.

Disclosures

Dr Hu is the chief executive officer of CarePort Health. Mr. Martin is the director of Post-Acute Care Analytics at CarePort Health. No other disclosures were reported.

Funding

Drs Boscardin, Covinsky, and Smith are supported by the UCSF Pepper Center grant P30AG044281. The funder had no role in the design, conduct, or interpretation of the study, or the decision to publish. Dr Covinsky was supported by grants from the National Institute on Aging during the conduct of the study.

Access to Data: Mr Martin had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. The authors would be happy to share statistical code used to generate results.

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It is clear that certain patient-level factors, such as age, sex, and comorbidities, predict outcomes of SARS-CoV-2 infection.1,2 Less is known about whether hospital-level factors, including surges of patients with COVID-19, are associated with patient outcomes.

In a multicenter cohort study of 2,215 patients with COVID-19 in 65 intensive care units (ICU) across the United States, mortality rates varied widely (6.6%-80.8%), with improved survival for patients admitted to a hospital with more (>100) rather than fewer (<50) ICU beds.3 A different study found that at the state level, COVID-19 mortality increased with increasing COVID-19 admissions.4 Together, these studies suggest that surges in COVID-19 patient volume may be associated with excess mortality. However, the first study was restricted to the ICU population, limiting generalizability, and did not consider admission volume, only ICU bed count. Meanwhile, the second study considered both hospital capacity and patient volume, but it describes a relatively small sample, did not adjust for patient-level predictors of mortality, and does not report outcomes at the hospital level.

Here, we used a large dataset to compare in-hospital mortality rates for patients with COVID-19 across US hospitals, hypothesizing that mortality would be higher in hospitals with the highest burden of COVID-19 admissions. By adjusting for patient-level predictors of mortality and normalizing admission volume for hospital size, we are able to describe residual variability in mortality that may be attributable to differences in COVID-19 patient volume.

METHODS

We included patients with an International Statistical Classification of Diseases, Tenth Revision (ICD)-10 diagnosis of COVID-19 (U07.1) who were admitted to a US hospital that contracts with CarePort Health.5 CarePort is a platform for discharge planning and care coordination that contracts with hospitals in all US regions and auto-extracts data using interface feeds.

We restricted the population to patients admitted between April 1 and April 30, 2020, after a new ICD-10 code for confirmed COVID-19 infection became available, and to hospitals that provided real-time ICD-10 data and pertinent demographic information and could be linked to Centers for Medicare & Medicaid Services (CMS) data by National Provider Identifier. We assumed that the 145 patients (1.0%) who remained hospitalized at 5 weeks all survived. For the 5.9% of patients with multiple admissions during the study period, we included only the first admission with a diagnosis code for COVID-19.

We adjusted for patient age, sex, and the 31 comorbidities in the Elixhauser index, defined by ICD-10 codes. This set of comorbidities includes those previously associated with COVID-19 survival.1,2,6 Unfortunately, inconsistent reporting of vital signs and laboratory data precluded adjusting for acute illness severity. For those patients whose residence zip code was known, we report the racial breakdown (White vs non-White) and adjusted gross income (AGI), based on linked information from the 2018 American Community Survey.7

We defined COVID-19 burden as the quotient of COVID-19 admissions in April 2020 and each hospital’s certified bed count, as reported to the CMS.8 This allowed us to normalize COVID-19 patient volume for variation in hospital size, acknowledging that admitting 10 patients with COVID-19 to a 1,000-bed hospital is different from admitting 10 patients with COVID-19 to a 20-bed hospital. Certified bed count seemed the ideal denominator because it excludes beds not readily deployable to care for patients with COVID-19 (eg, radiology suites, labor and delivery rooms).

We computed hospital-specific adjusted mortality proportions and 95% confidence intervals based on hierarchical multivariable logistic regression, adjusting for age, sex, and comorbidities, and a random effect for each hospital.9,10 Hypothesizing that there may be a threshold of burden beyond which mortality begins to rise, we compared the in-hospital mortality rate at hospitals in the highest quintile of COVID-19 burden to all other hospitals.

We conducted eight post-hoc sensitivity analyses: (1) restricting the study population to patients aged 75 years and older; (2) restricting study hospitals to those with at least 100 beds and 20 COVID-19 admissions; (3) assuming that all patients who remained hospitalized at 5 weeks had died; (4) using each patient’s last admission during the month of April rather than the first; sequentially incorporating (5) zip code–level information on race (limited to White, non-White) and (6) AGI (treated as a continuous variable) into our model; (7) computing two burdens for each hospital (one for each half of April) and using whichever was higher; and (8) treating COVID-19 burden as a continuous predictor. Analyses were performed using SAS statistical software, version 9.4 (SAS Institute Inc) using the GLIMMIX procedure. This study was deemed exempt by the University of California, San Francisco Institutional Review Board.

RESULTS

The study population included 14,226 patients with COVID-19 (median age, 66 years [range, 0-110 years]; 45.2% women) at 117 US hospitals. Based on patients’ zip code of residence, we estimate that 47.0% of patients were White and 29.1% Black, and that the mean household AGI was $61,956. Most hospitals were nonprofit (56%) or private (39%), with approximately one quarter coming from each US census region (range, 25 hospitals [21%] in Midwest to 33 hospitals [28%] in Northeast). Nine hospitals (8%) had more than 700 beds, 40 (34%) had 300 to 700 beds, and 68 (58%) had fewer than 300 beds. Thirty-six hospitals (30.8%) admitted fewer than 20 patients with COVID-19, while six hospitals (5.1%) admitted more than 500 such patients. COVID burden ranged from 0.004 to 2.03 admissions per bed.

As of June 5, 2020, 78.1% of patients had been discharged alive, 20.9% had died, and 1.0% remained hospitalized. At the hospital level, the observed mortality ranged from 0% to 44.4%, was 17.1% among hospitals in COVID-19 burden quintiles one through four, and was 22.7% in the highest burden quintile (Table).

Characteristics and Outcomes of 14,226 Patients Admitted to US Hospitals With COVID-19
The 22 hospitals reporting zero deaths admitted a median of six patients with COVID-19 (maximum, 17). After adjustment for age, sex, and comorbidities, the adjusted odds ratio for in-hospital death in the most burdened hospitals was 1.46 (95% CI, 1.07-2.00) compared to hospitals in the bottom four quintiles of burden. The adjusted in-hospital mortality rate for each study hospital is shown in the Figure.

In-Hospital Mortality Rates for Patients With COVID-19 at 117 US Hospitals

Results were similar across multiple sensitivity analyses (see Appendix Table), although the relationship between COVID-19 burden and in-hospital mortality was attenuated and not significant when the sample was restricted to hospitals with at least 100 beds and 20 COVID-19 admissions, or in analyses adjusted for race and AGI.

DISCUSSION

In this study of 14,226 patients with COVID-19 across 117 US hospitals, those patients admitted to the most burdened hospitals had a higher odds of death. This relationship, which persisted after adjusting for age, sex, and comorbid conditions, suggests that a threshold exists at which patient surges may cause excess mortality.

Notably, in sensitivity analyses adjusting for race and AGI, COVID-19 burden was no longer associated with in-hospital mortality and the point estimate was attenuated. This raises the possibility that our primary results are confounded by these factors. However, prior studies of hospitalized patients have not found race to be predictive of mortality, after adjusting for other factors.11,12

We also note that the relationship between COVID-19 burden and mortality was not significant (P = .07) when the sample was restricted to larger hospitals with more than 20 COVID-19 admissions; again, the point estimate was attenuated. This suggests that larger hospitals may be more resilient in the face of patient surges. Whether this is due to increased availability of staff who can be redeployed to patient care (as with researchers at academic centers), increased experience managing severe respiratory failure, or other factors is uncertain.

Interestingly, in-hospital mortality varied widely across study hospitals, even among the most-burdened hospitals. The reasons for this residual variability—after adjusting for age, sex, and comorbidities and stratifying by COVID-19 burden—are uncertain. To the extent that this variability reflects differences in patient management, hospital staffing, or use of investigational or advanced therapies, it will be critical to identify and disseminate any replicable best practices from high-burden hospitals with low mortality rates.

Whereas other reports have often described single-center or regional experiences,13-15 leaving open the possibility that their results were highly influenced by the local nature of the pandemic in their respective settings, our report from a large sample of hospitals across the United States in high- and low-burden settings provides a more generalizable description of mortality rates for hospitalized patients. Additional study strengths include our adjustment for comorbidities known to be associated with COVID-19 survival, the reporting of definitive outcomes for 99% of patients, and the inclusion of multiple sensitivity analyses to assess the stability of findings.

Our principal limitation is the inability to adjust for severity of acute illness due to inconsistent reporting of laboratory and vital signs data from study hospitals and missing information on interhospital transfers. While our adjusted analyses clearly suggest an association between COVID-19 burden and patient outcomes, our results may still be confounded by differences in illness severity at study hospitals. Thus, our findings should be considered hypothesis-generating and will require confirmation in future studies that include adjustment for acute illness severity.

Other limitations of our study include overrepresentation of large urban hospitals in the Northeast, although this represents the geography of the US pandemic during the study period. Our adjustment for race/ethnicity and socioeconomic status was limited in that we only had zip code-of-residence level information, did not know the zip code of residence for one quarter of study patients, and had to bifurcate the population into White/non-White categories. Finally, our definition of burden does not account for hospital resources, including staffing, ICU capacity, and the availability of advanced or investigational therapies.

CONCLUSION

In this study of 14,226 patients with COVID-19 admitted to 1 of 117 US hospitals, we found that the odds of in-hospital mortality were higher in hospitals that had the highest burden of COVID-19 admissions. This relationship, which persisted after adjustment for age, sex, and comorbid conditions, suggests that patient surges may be an independent risk factor for in-hospital death among patients with COVID-19.

ACKNOWLEGMENTS

The authors thank Bocheng Jing, MS, Senior Statistician at the UCSF Pepper Center, for providing code to identify Elixhauser conditions from ICD-10 data; and Scott Kerber, BS, and Scott Magnoni, MS, both of CarePort Health, for assistance with data extraction. They were not compensated for this work beyond their regular salaries.

It is clear that certain patient-level factors, such as age, sex, and comorbidities, predict outcomes of SARS-CoV-2 infection.1,2 Less is known about whether hospital-level factors, including surges of patients with COVID-19, are associated with patient outcomes.

In a multicenter cohort study of 2,215 patients with COVID-19 in 65 intensive care units (ICU) across the United States, mortality rates varied widely (6.6%-80.8%), with improved survival for patients admitted to a hospital with more (>100) rather than fewer (<50) ICU beds.3 A different study found that at the state level, COVID-19 mortality increased with increasing COVID-19 admissions.4 Together, these studies suggest that surges in COVID-19 patient volume may be associated with excess mortality. However, the first study was restricted to the ICU population, limiting generalizability, and did not consider admission volume, only ICU bed count. Meanwhile, the second study considered both hospital capacity and patient volume, but it describes a relatively small sample, did not adjust for patient-level predictors of mortality, and does not report outcomes at the hospital level.

Here, we used a large dataset to compare in-hospital mortality rates for patients with COVID-19 across US hospitals, hypothesizing that mortality would be higher in hospitals with the highest burden of COVID-19 admissions. By adjusting for patient-level predictors of mortality and normalizing admission volume for hospital size, we are able to describe residual variability in mortality that may be attributable to differences in COVID-19 patient volume.

METHODS

We included patients with an International Statistical Classification of Diseases, Tenth Revision (ICD)-10 diagnosis of COVID-19 (U07.1) who were admitted to a US hospital that contracts with CarePort Health.5 CarePort is a platform for discharge planning and care coordination that contracts with hospitals in all US regions and auto-extracts data using interface feeds.

We restricted the population to patients admitted between April 1 and April 30, 2020, after a new ICD-10 code for confirmed COVID-19 infection became available, and to hospitals that provided real-time ICD-10 data and pertinent demographic information and could be linked to Centers for Medicare & Medicaid Services (CMS) data by National Provider Identifier. We assumed that the 145 patients (1.0%) who remained hospitalized at 5 weeks all survived. For the 5.9% of patients with multiple admissions during the study period, we included only the first admission with a diagnosis code for COVID-19.

We adjusted for patient age, sex, and the 31 comorbidities in the Elixhauser index, defined by ICD-10 codes. This set of comorbidities includes those previously associated with COVID-19 survival.1,2,6 Unfortunately, inconsistent reporting of vital signs and laboratory data precluded adjusting for acute illness severity. For those patients whose residence zip code was known, we report the racial breakdown (White vs non-White) and adjusted gross income (AGI), based on linked information from the 2018 American Community Survey.7

We defined COVID-19 burden as the quotient of COVID-19 admissions in April 2020 and each hospital’s certified bed count, as reported to the CMS.8 This allowed us to normalize COVID-19 patient volume for variation in hospital size, acknowledging that admitting 10 patients with COVID-19 to a 1,000-bed hospital is different from admitting 10 patients with COVID-19 to a 20-bed hospital. Certified bed count seemed the ideal denominator because it excludes beds not readily deployable to care for patients with COVID-19 (eg, radiology suites, labor and delivery rooms).

We computed hospital-specific adjusted mortality proportions and 95% confidence intervals based on hierarchical multivariable logistic regression, adjusting for age, sex, and comorbidities, and a random effect for each hospital.9,10 Hypothesizing that there may be a threshold of burden beyond which mortality begins to rise, we compared the in-hospital mortality rate at hospitals in the highest quintile of COVID-19 burden to all other hospitals.

We conducted eight post-hoc sensitivity analyses: (1) restricting the study population to patients aged 75 years and older; (2) restricting study hospitals to those with at least 100 beds and 20 COVID-19 admissions; (3) assuming that all patients who remained hospitalized at 5 weeks had died; (4) using each patient’s last admission during the month of April rather than the first; sequentially incorporating (5) zip code–level information on race (limited to White, non-White) and (6) AGI (treated as a continuous variable) into our model; (7) computing two burdens for each hospital (one for each half of April) and using whichever was higher; and (8) treating COVID-19 burden as a continuous predictor. Analyses were performed using SAS statistical software, version 9.4 (SAS Institute Inc) using the GLIMMIX procedure. This study was deemed exempt by the University of California, San Francisco Institutional Review Board.

RESULTS

The study population included 14,226 patients with COVID-19 (median age, 66 years [range, 0-110 years]; 45.2% women) at 117 US hospitals. Based on patients’ zip code of residence, we estimate that 47.0% of patients were White and 29.1% Black, and that the mean household AGI was $61,956. Most hospitals were nonprofit (56%) or private (39%), with approximately one quarter coming from each US census region (range, 25 hospitals [21%] in Midwest to 33 hospitals [28%] in Northeast). Nine hospitals (8%) had more than 700 beds, 40 (34%) had 300 to 700 beds, and 68 (58%) had fewer than 300 beds. Thirty-six hospitals (30.8%) admitted fewer than 20 patients with COVID-19, while six hospitals (5.1%) admitted more than 500 such patients. COVID burden ranged from 0.004 to 2.03 admissions per bed.

As of June 5, 2020, 78.1% of patients had been discharged alive, 20.9% had died, and 1.0% remained hospitalized. At the hospital level, the observed mortality ranged from 0% to 44.4%, was 17.1% among hospitals in COVID-19 burden quintiles one through four, and was 22.7% in the highest burden quintile (Table).

Characteristics and Outcomes of 14,226 Patients Admitted to US Hospitals With COVID-19
The 22 hospitals reporting zero deaths admitted a median of six patients with COVID-19 (maximum, 17). After adjustment for age, sex, and comorbidities, the adjusted odds ratio for in-hospital death in the most burdened hospitals was 1.46 (95% CI, 1.07-2.00) compared to hospitals in the bottom four quintiles of burden. The adjusted in-hospital mortality rate for each study hospital is shown in the Figure.

In-Hospital Mortality Rates for Patients With COVID-19 at 117 US Hospitals

Results were similar across multiple sensitivity analyses (see Appendix Table), although the relationship between COVID-19 burden and in-hospital mortality was attenuated and not significant when the sample was restricted to hospitals with at least 100 beds and 20 COVID-19 admissions, or in analyses adjusted for race and AGI.

DISCUSSION

In this study of 14,226 patients with COVID-19 across 117 US hospitals, those patients admitted to the most burdened hospitals had a higher odds of death. This relationship, which persisted after adjusting for age, sex, and comorbid conditions, suggests that a threshold exists at which patient surges may cause excess mortality.

Notably, in sensitivity analyses adjusting for race and AGI, COVID-19 burden was no longer associated with in-hospital mortality and the point estimate was attenuated. This raises the possibility that our primary results are confounded by these factors. However, prior studies of hospitalized patients have not found race to be predictive of mortality, after adjusting for other factors.11,12

We also note that the relationship between COVID-19 burden and mortality was not significant (P = .07) when the sample was restricted to larger hospitals with more than 20 COVID-19 admissions; again, the point estimate was attenuated. This suggests that larger hospitals may be more resilient in the face of patient surges. Whether this is due to increased availability of staff who can be redeployed to patient care (as with researchers at academic centers), increased experience managing severe respiratory failure, or other factors is uncertain.

Interestingly, in-hospital mortality varied widely across study hospitals, even among the most-burdened hospitals. The reasons for this residual variability—after adjusting for age, sex, and comorbidities and stratifying by COVID-19 burden—are uncertain. To the extent that this variability reflects differences in patient management, hospital staffing, or use of investigational or advanced therapies, it will be critical to identify and disseminate any replicable best practices from high-burden hospitals with low mortality rates.

Whereas other reports have often described single-center or regional experiences,13-15 leaving open the possibility that their results were highly influenced by the local nature of the pandemic in their respective settings, our report from a large sample of hospitals across the United States in high- and low-burden settings provides a more generalizable description of mortality rates for hospitalized patients. Additional study strengths include our adjustment for comorbidities known to be associated with COVID-19 survival, the reporting of definitive outcomes for 99% of patients, and the inclusion of multiple sensitivity analyses to assess the stability of findings.

Our principal limitation is the inability to adjust for severity of acute illness due to inconsistent reporting of laboratory and vital signs data from study hospitals and missing information on interhospital transfers. While our adjusted analyses clearly suggest an association between COVID-19 burden and patient outcomes, our results may still be confounded by differences in illness severity at study hospitals. Thus, our findings should be considered hypothesis-generating and will require confirmation in future studies that include adjustment for acute illness severity.

Other limitations of our study include overrepresentation of large urban hospitals in the Northeast, although this represents the geography of the US pandemic during the study period. Our adjustment for race/ethnicity and socioeconomic status was limited in that we only had zip code-of-residence level information, did not know the zip code of residence for one quarter of study patients, and had to bifurcate the population into White/non-White categories. Finally, our definition of burden does not account for hospital resources, including staffing, ICU capacity, and the availability of advanced or investigational therapies.

CONCLUSION

In this study of 14,226 patients with COVID-19 admitted to 1 of 117 US hospitals, we found that the odds of in-hospital mortality were higher in hospitals that had the highest burden of COVID-19 admissions. This relationship, which persisted after adjustment for age, sex, and comorbid conditions, suggests that patient surges may be an independent risk factor for in-hospital death among patients with COVID-19.

ACKNOWLEGMENTS

The authors thank Bocheng Jing, MS, Senior Statistician at the UCSF Pepper Center, for providing code to identify Elixhauser conditions from ICD-10 data; and Scott Kerber, BS, and Scott Magnoni, MS, both of CarePort Health, for assistance with data extraction. They were not compensated for this work beyond their regular salaries.

References

1. Evidence used to update the list of underlying medical conditions that increase a person’s risk of severe illness from COVID-19. Centers for Disease Control and Prevention. Updated November 2, 2020. Accessed December 29, 2020. https://www.cdc.gov/coronavirus/2019-ncov/need-extra-precautions/evidence-table.html
2. Cummings MJ, Baldwin MR, Abrams D, et al. Epidemiology, clinical course, and outcomes of critically ill adults with COVID-19 in New York City: a prospective cohort study. Lancet. 2020;395(10239):1763-1770. https://doi.org/10.1016/S0140-6736(20)31189-2
3. Gupta S, Hayek SS, Wang W, et al. Factors associated with death in critically ill patients with coronavirus disease 2019 in the US. JAMA Intern Med. 2020;180(11):1-12. https://doi.org/10.1001/jamainternmed.2020.4568
4. Karaca-Mandic P, Sen S, Georgiou A, Zhu Y, Basu A. Association of COVID-19-related hospital use and overall covid-19 mortality in the USA. J Gen Intern Med. 2020:1-3. https://doi.org/10.1007/s11606-020-06084-7
5. ICD-10-CM official coding and reporting guidelines April 1, 2020 through September 30, 2020. Centers for Disease Control and Prevention. Accessed June 2, 2020. https://www.cdc.gov/nchs/data/icd/COVID-19-guidelines-final.pdf
6. Quan H, Sundararajan V, Halfon P, et al. Coding algorithms for defining comorbidities in ICD-9-CM and ICD-10 administrative data. Med Care. 2005;43(11):1130-1139. https://doi.org/10.1097/01.mlr.0000182534.19832.83
7. About the American Community Survey. United States Census Bureau. Updated January 4, 2021. Accessed March 2, 2021. https://www.census.gov/programs-surveys/acs/about.html
8. Provider of service files. Centers for Medicare & Medicaid Services. Revised January 15, 2020. Accessed March 2, 2021. https://www.cms.gov/research-statistics-data-systems/provider-services-current-files/2019-pos-file
9. Ash AS, Fienberg SE, Louis TA, et al. Statistical issues in assessing hospital performance. Committee of Presidents of Statistical Societies white paper. January 2012. Accessed March 1, 2021. https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HospitalQualityInits/Downloads/Statistical-Issues-in-Assessing-Hospital-Performance.pdf
10. Bratzler DW, Normand SL, Wang Y, et al. An administrative claims model for profiling hospital 30-day mortality rates for pneumonia patients. PLoS One. 2011;12;6(4):e17401. https://doi.org/10.1371/journal.pone.0017401
11. Garibaldi BT, Fiksel J, Muschelli J, et al. Patient trajectories among persons hospitalized for COVID-19: a cohort study. Ann Intern Med. 2021;174(1):33-41. https://doi.org/10.7326/M20-3905
12. Price-Haywood EG, Burton J, Fort D, Seoane L. Hospitalization and mortality among Black patients and White patients with Covid-19. N Engl J Med. 2020;382(26):2534-2543. https://doi.org/10.1056/NEJMsa2011686
13. Bhatraju PK, Ghassemieh BJ, Nichols M, et al. Covid-19 in critically ill patients in the Seattle region - case series. N Engl J Med. 2020;382(21):2012-2022. https://doi.org/10.1056/NEJMoa2004500
14. Yang X, Yu Y, Xu J, et al. Clinical course and outcomes of critically ill patients with SARS-CoV-2 pneumonia in Wuhan, China: a single-centered, retrospective, observational study. Lancet Respir Med. 2020;8(5):475-481. https://doi.org/10.1016/S2213-2600(20)30079-5
15. Richardson S, Hirsch JS, Narasimhan M, et al. Presenting characteristics, comorbidities, and outcomes among 5700 patients hospitalized with COVID-19 in the New York City area. JAMA. 2020;323(20):2052-2059. https://doi.org/10.1001/jama.2020.6775

References

1. Evidence used to update the list of underlying medical conditions that increase a person’s risk of severe illness from COVID-19. Centers for Disease Control and Prevention. Updated November 2, 2020. Accessed December 29, 2020. https://www.cdc.gov/coronavirus/2019-ncov/need-extra-precautions/evidence-table.html
2. Cummings MJ, Baldwin MR, Abrams D, et al. Epidemiology, clinical course, and outcomes of critically ill adults with COVID-19 in New York City: a prospective cohort study. Lancet. 2020;395(10239):1763-1770. https://doi.org/10.1016/S0140-6736(20)31189-2
3. Gupta S, Hayek SS, Wang W, et al. Factors associated with death in critically ill patients with coronavirus disease 2019 in the US. JAMA Intern Med. 2020;180(11):1-12. https://doi.org/10.1001/jamainternmed.2020.4568
4. Karaca-Mandic P, Sen S, Georgiou A, Zhu Y, Basu A. Association of COVID-19-related hospital use and overall covid-19 mortality in the USA. J Gen Intern Med. 2020:1-3. https://doi.org/10.1007/s11606-020-06084-7
5. ICD-10-CM official coding and reporting guidelines April 1, 2020 through September 30, 2020. Centers for Disease Control and Prevention. Accessed June 2, 2020. https://www.cdc.gov/nchs/data/icd/COVID-19-guidelines-final.pdf
6. Quan H, Sundararajan V, Halfon P, et al. Coding algorithms for defining comorbidities in ICD-9-CM and ICD-10 administrative data. Med Care. 2005;43(11):1130-1139. https://doi.org/10.1097/01.mlr.0000182534.19832.83
7. About the American Community Survey. United States Census Bureau. Updated January 4, 2021. Accessed March 2, 2021. https://www.census.gov/programs-surveys/acs/about.html
8. Provider of service files. Centers for Medicare & Medicaid Services. Revised January 15, 2020. Accessed March 2, 2021. https://www.cms.gov/research-statistics-data-systems/provider-services-current-files/2019-pos-file
9. Ash AS, Fienberg SE, Louis TA, et al. Statistical issues in assessing hospital performance. Committee of Presidents of Statistical Societies white paper. January 2012. Accessed March 1, 2021. https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HospitalQualityInits/Downloads/Statistical-Issues-in-Assessing-Hospital-Performance.pdf
10. Bratzler DW, Normand SL, Wang Y, et al. An administrative claims model for profiling hospital 30-day mortality rates for pneumonia patients. PLoS One. 2011;12;6(4):e17401. https://doi.org/10.1371/journal.pone.0017401
11. Garibaldi BT, Fiksel J, Muschelli J, et al. Patient trajectories among persons hospitalized for COVID-19: a cohort study. Ann Intern Med. 2021;174(1):33-41. https://doi.org/10.7326/M20-3905
12. Price-Haywood EG, Burton J, Fort D, Seoane L. Hospitalization and mortality among Black patients and White patients with Covid-19. N Engl J Med. 2020;382(26):2534-2543. https://doi.org/10.1056/NEJMsa2011686
13. Bhatraju PK, Ghassemieh BJ, Nichols M, et al. Covid-19 in critically ill patients in the Seattle region - case series. N Engl J Med. 2020;382(21):2012-2022. https://doi.org/10.1056/NEJMoa2004500
14. Yang X, Yu Y, Xu J, et al. Clinical course and outcomes of critically ill patients with SARS-CoV-2 pneumonia in Wuhan, China: a single-centered, retrospective, observational study. Lancet Respir Med. 2020;8(5):475-481. https://doi.org/10.1016/S2213-2600(20)30079-5
15. Richardson S, Hirsch JS, Narasimhan M, et al. Presenting characteristics, comorbidities, and outcomes among 5700 patients hospitalized with COVID-19 in the New York City area. JAMA. 2020;323(20):2052-2059. https://doi.org/10.1001/jama.2020.6775

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Supine-Related Pseudoanemia in Hospitalized Patients

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Supine-Related Pseudoanemia in Hospitalized Patients

The World Health Organization (WHO) defines anemia as a hemoglobin value less than 12 g/dL in women and less than 13 g/dL in men.1 Hospital-acquired anemia is loosely defined as normal hemoglobin levels on admission that, at their nadir during hospitalization or on discharge, are less than WHO sex-defined cutoffs. Hospital-acquired anemia or significant decreases in hemoglobin are often identified during hospitalization.2-6 Potential causes include blood loss from phlebotomy, occult gastrointestinal bleeding, hemolysis, anemia of inflammation, and hemodilution due to fluid resuscitation. Of these causes, some are dangerous to patients, some are iatrogenic, and some are due to laboratory error.7 Physicians often evaluate decreases in hemoglobin, which could otherwise be explained by laboratory error, hemodilution, or expected decrease in hemoglobin due to hospitalization, to identify causes that may lead to potential harm.

Jacob et al8 demonstrated the effect of posture on hemoglobin concentrations in healthy volunteers, showing an average 11% relative increase in hemoglobin when going from lying to standing. This increase was attributed to shifts in plasma volume to the vascular space with recumbence. They hypothesized that the initial hemoglobin on admission is measured when patients are upright or recently upright, whereas after admission, patients are more likely to be supine, resulting in lower hemoglobin concentrations. Others have also demonstrated similar effects of patient posture on hemoglobin concentration.9-13 However, these prior results are not readily generalizable to hospitalized patients. These prior studies enrolled healthy volunteers, and most examined postural changes from the supine and standing positions; blood is rarely obtained from hospitalized patients when they are standing.

The aim of this study was to investigate whether postural changes in hemoglobin can be demonstrated in positions that patients routinely encountered during in-hospital phlebotomy: upright in a chair or recumbent in a bed. Patient position, which is not standardized during blood draws, may contribute to lower measured hemoglobin concentrations in some patients, especially sicker individuals who are recumbent more frequently. We hypothesized that going from supine to upright in a chair would result in a relative increase in hemoglobin concentration of 5% to 6%, approximately half the value of going from supine to standing.8 To investigate this, we conducted a quasi-experimental study exploring the effect of position (supine or sitting in chair) on hemoglobin concentrations in medical inpatients.

METHODS

Participants

Patients were enrolled in this single-center study between October 2017 and August 2018. Patients aged 18 years or older who were hospitalized on the general internal medicine wards were screened to determine if they met the following inclusion criteria: hospitalized for <5 days, had blood work scheduled as part of routine care (in order to decrease phlebotomy required by this study), had baseline hemoglobin >8 g/dL, and were able to remain supine without interruption overnight and able to sit in a chair for at least 1 hour the following morning. Patients were excluded from the study if they had a hematologic malignancy, were at risk of >100 mL of blood loss (eg, admitted for gastrointestinal bleeding, planned surgery), had a transfusion requirement, or received intravascular modifiers such as fluid (>100 cc/h) or intravenous diuretics. The Johns Hopkins Institutional Review Board approved this study, and all patients provided written informed consent.

Study Design

Patients enrolled in this quasi-experimental study were asked to remain supine for at least 6 hours overnight. Adherence to the recumbent position was tracked by patient self-report and by corroboration with the patient’s nurse overnight. Any interruptions to supine positioning resulted in exclusion from the study. The following morning, a member of the study team performed phlebotomy while the patient remained supine. Patients were then asked to sit comfortably in a chair for at least 1 hour with their feet on the ground; the blood draw was then repeated. All blood samples were acquired by venipuncture. Prior to each blood draw, a tourniquet was placed over the upper arm below the axilla. An antecubital vein on either arm was visualized under ultrasound guidance, and a 23-G × 3/4” butterfly needle was used for venipuncture. The vials of blood were immediately inverted after blood collection. Hemoglobin assays were processed and analyzed using Sysmex XN-10 analyzer (Sysmex Corporation). The reference range for hemoglobin in our facility was 12.0 to 15.0 g/dL for women and 13.9 to 16.3 g/dL for men. Laboratory technicians were blinded to and uninvolved in the study.

We determined, a priori, that 33 enrolled patients would provide 80% power (alpha 0.05) to detect an average hemoglobin change of 4.1%, assuming that the standard deviation of the hemoglobin change was twice the mean (ie, SD = 8.2%). The Wilcoxon signed-rank test was used to test the significance of postural hemoglobin changes. Analyses were conducted using JMP Pro 13.0 (SAS) and GraphPad Prism 8 (GraphPad Software). Significance was defined at P < .05 for all analyses.

RESULTS

Thirty-nine patients were consented and enrolled in the study; four patients were excluded prior to blood draw (two patients because of interruption of supine time, two patients because of refusal in the morning). Of the 35 patients who completed the study, 13 were women (37%); median age was 49 years (range, 25-83 years). Median supine hemoglobin concentration in our sample was 11.7 g/dL (range, 9.3-18.1 g/dL), and median baseline creatinine level was 0.70 mg/dL (range, 0.5-2.5 mg/dL). Median supine hemoglobin levels were 11.7 g/dL (range, 9.6-13.2 g/dL) in women and 11.8 g/dL (range, 9.3-18.1 g/dL) in men. In aggregate, patients had a median increase in hemoglobin concentration of 0.60 g/dL (range, –0.6 to 1.4 g/dL) with sitting, a 5.2% (range, –4.5% to 15.1%) relative change (P < .001) (Figure 1).

Patient-Level Hemoglobin Changes With Posture Changes
Women had a median increase in hemoglobin concentration of 0.60 g/dL (range, –0.6 to 1.4 g/dL) with sitting, a relative change of 5.3% (range, –4.5% to 12.0%) (P = .02). Men had a median increase in hemoglobin concentration of 0.55 g/dL (range, –0.1 to 1.4 g/dL) with sitting, a 5.0% (range, –0.6% to 15.1%) relative change (P < .001). Ten of 35 participants (29%) exhibited an increase in hemoglobin level of 1.0 g/dL or more (Figure 2).
Absolute and Relative Change in Hemoglobin Concentration With Positional Changes

DISCUSSION

International blood collection guidelines acknowledge postural changes in laboratory values and recommend standardization of patient position to either sitting in a chair or lying flat in a bed, without changes in position for 15 minutes prior to blood draw.14 When these positional accommodations cannot be met, documenting positional disruptions is recommended so that laboratory values can be interpreted accordingly. To the best of our knowledge, no hospital in the United States has standardized patient position as part of phlebotomy procedure such that patient position is documented and can be made available to interpreting providers.

Relative increases in hemoglobin or hematocrit range from 7% to 12% when patients go from supine to standing.8,9,11 The reverse relationship has also been shown, where upright-to-supine position results in decreases in hemoglobin concentrations.10,13 We found that going from supine to a seated position resulted in significant increases in hemoglobin of 0.6 g/dL and in a more than 1 g/dL increase in 29% of the patients. Although four of the 35 patients experienced either no change or a slight decrease in their hemoglobin concentration when going from supine to upright and not all patients saw a uniform effect, providers should be aware that the patient’s position can contribute to changes in hemoglobin concentration in the hospitalized setting. Providers may be able to use this information to avoid an extensive diagnostic workup when anemia is identified in hospitalized patients, although more research is needed to identify patient subsets who are at higher risk for this effect.

Until hospitals implement protocols that require phlebotomists to report patient position during phlebotomy in a standardized fashion, providers should be alert to the fact that supine positioning may result in a hemoglobin level that is significantly lower than that when drawn in a sitting position, and in almost one-third of patients, this difference may be 1.0 g/dL or greater.

Given our study criteria requiring supine positions of at least 6 hours and a baseline hemoglobin concentration >8 g/dL, our sample of patients may have been younger and healthier than the average hospitalized patient on general internal medicine wards. Since greater relative changes in plasma volume shifts and hemoglobin might be seen in patients with lower baseline hemoglobin and lower baseline plasma protein, this selection bias may underestimate the effects of position on hemoglobin changes for the average inpatient population. Additionally, we intentionally sought to obtain sitting hemoglobin levels after the supine samples to avoid the possibility of incorrectly attributing dropping hemoglobin levels to progressive hospital-acquired anemia from phlebotomy or illness. Any concomitant trend of falling hemoglobin levels in our patients would be expected to lead to a systematic underestimation of the positional change in hemoglobin we observed. We did not objectively observe adherence to supine and upright position and instead relied on patient self-reporting, which is one possible contributor to the variable effects of position on hemoglobin concentration, with some patients having no change or decreases in hemoglobin concentrations.

CONCLUSION

Posture can significantly influence hemoglobin levels in hospitalized patients on general medicine wards. Further research can determine whether it would be cost and time effective to standardize patient positions prior to phlebotomy, or at least to report patient positioning with the laboratory testing results.

References

1. DeMaeyer E, Adiels-Tegman M. The prevalence of anaemia in the world. World Health Stat Q. 1985;38(3):302-316.
2. Martin ND, Scantling D. Hospital-acquired anemia. J Infus Nurs. 2015;38(5):330-338. https://doi.org/10.1097/NAN.0000000000000121
3. Thavendiranathan P, Bagai A, Ebidia A, Detsky AS, Choudhry NK. Do blood tests cause anemia in hospitalized patients? The effect of diagnostic phlebotomy on hemoglobin and hematocrit levels. J Gen Intern Med. 2005;20(6):520-524. https://doi.org/10.1111/j.1525-1497.2005.0094.x
4. Salisbury AC, Reid KJ, Alexander KP, et al. Diagnostic blood loss from phlebotomy and hospital-acquired anemia during acute myocardial infarction. Arch Intern Med. 2011;171(18):1646-1653. https://doi.org/10.1001/archinternmed.2011.361
5. Languasco A, Cazap N, Marciano S, et al. Hemoglobin concentration variations over time in general medical inpatients. J Hosp Med. 2010;5(5):283-288. https://doi.org/10.1002/jhm.650
6. van der Bom JG, Cannegieter SC. Hospital-acquired anemia: the contribution of diagnostic blood loss. J Thromb Haemost. 2015;13(6):1157-1159. https://doi.org/10.1111/jth.12886
7. Berkow L. Factors affecting hemoglobin measurement. J Clin Monit Comput. 2013;27(5):499-508. https://doi.org/10.1007/s10877-013-9456-3
8. Jacob G, Raj SR, Ketch T, et al. Postural pseudoanemia: posture-dependent change in hematocrit. Mayo Clin Proc. 2005;80(5):611-614. https://doi.org/10.4065/80.5.611
9. Fawcett JK, Wynn V. Effects of posture on plasma volume and some blood constituents. J Clin Pathol. 1960;13(4):304-310. https://doi.org/10.1136/jcp.13.4.304
10. Tombridge TL. Effect of posture on hematology results. Am J ClinPathol. 1968;49(4):491-493. https://doi.org/10.1093/ajcp/49.4.491
11. Hagan RD, Diaz FJ, Horvath SM. Plasma volume changes with movement to supine and standing positions. J Appl Physiol. 1978;45(3):414-417. https://doi.org/10.1152/jappl.1978.45.3.414
12. Maw GJ, Mackenzie IL, Taylor NA. Redistribution of body fluids during postural manipulations. Acta Physiol Scand. 1995;155(2):157-163. https://doi.org/10.1111/j.1748-1716.1995.tb09960.x
13. Lima-Oliveira G, Guidi GC, Salvagno GL, Danese E, Montagnana M, Lippi G. Patient posture for blood collection by venipuncture: recall for standardization after 28 years. Rev Bras Hematol Hemoter. 2017;39(2):127-132. https://doi.org/10.1016/j.bjhh.2017.01.004
14. Simundic AM, Bölenius K, Cadamuro J, et al. Working Group for Preanalytical Phase (WG-PRE), of the European Federation of Clinical Chemistry and Laboratory Medicine (EFLM) and Latin American Working Group for Preanalytical Phase (WG-PRE-LATAM) of the Latin America Confederation of Clinical Biochemistry (COLABIOCLI). Joint EFLM-COLABIOCLI recommendation for venous blood sampling. Clin Chem Lab Med. 2018;56(12):2015-2038. https://doi.org/10.1515/cclm-2018-0602

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Related Articles

The World Health Organization (WHO) defines anemia as a hemoglobin value less than 12 g/dL in women and less than 13 g/dL in men.1 Hospital-acquired anemia is loosely defined as normal hemoglobin levels on admission that, at their nadir during hospitalization or on discharge, are less than WHO sex-defined cutoffs. Hospital-acquired anemia or significant decreases in hemoglobin are often identified during hospitalization.2-6 Potential causes include blood loss from phlebotomy, occult gastrointestinal bleeding, hemolysis, anemia of inflammation, and hemodilution due to fluid resuscitation. Of these causes, some are dangerous to patients, some are iatrogenic, and some are due to laboratory error.7 Physicians often evaluate decreases in hemoglobin, which could otherwise be explained by laboratory error, hemodilution, or expected decrease in hemoglobin due to hospitalization, to identify causes that may lead to potential harm.

Jacob et al8 demonstrated the effect of posture on hemoglobin concentrations in healthy volunteers, showing an average 11% relative increase in hemoglobin when going from lying to standing. This increase was attributed to shifts in plasma volume to the vascular space with recumbence. They hypothesized that the initial hemoglobin on admission is measured when patients are upright or recently upright, whereas after admission, patients are more likely to be supine, resulting in lower hemoglobin concentrations. Others have also demonstrated similar effects of patient posture on hemoglobin concentration.9-13 However, these prior results are not readily generalizable to hospitalized patients. These prior studies enrolled healthy volunteers, and most examined postural changes from the supine and standing positions; blood is rarely obtained from hospitalized patients when they are standing.

The aim of this study was to investigate whether postural changes in hemoglobin can be demonstrated in positions that patients routinely encountered during in-hospital phlebotomy: upright in a chair or recumbent in a bed. Patient position, which is not standardized during blood draws, may contribute to lower measured hemoglobin concentrations in some patients, especially sicker individuals who are recumbent more frequently. We hypothesized that going from supine to upright in a chair would result in a relative increase in hemoglobin concentration of 5% to 6%, approximately half the value of going from supine to standing.8 To investigate this, we conducted a quasi-experimental study exploring the effect of position (supine or sitting in chair) on hemoglobin concentrations in medical inpatients.

METHODS

Participants

Patients were enrolled in this single-center study between October 2017 and August 2018. Patients aged 18 years or older who were hospitalized on the general internal medicine wards were screened to determine if they met the following inclusion criteria: hospitalized for <5 days, had blood work scheduled as part of routine care (in order to decrease phlebotomy required by this study), had baseline hemoglobin >8 g/dL, and were able to remain supine without interruption overnight and able to sit in a chair for at least 1 hour the following morning. Patients were excluded from the study if they had a hematologic malignancy, were at risk of >100 mL of blood loss (eg, admitted for gastrointestinal bleeding, planned surgery), had a transfusion requirement, or received intravascular modifiers such as fluid (>100 cc/h) or intravenous diuretics. The Johns Hopkins Institutional Review Board approved this study, and all patients provided written informed consent.

Study Design

Patients enrolled in this quasi-experimental study were asked to remain supine for at least 6 hours overnight. Adherence to the recumbent position was tracked by patient self-report and by corroboration with the patient’s nurse overnight. Any interruptions to supine positioning resulted in exclusion from the study. The following morning, a member of the study team performed phlebotomy while the patient remained supine. Patients were then asked to sit comfortably in a chair for at least 1 hour with their feet on the ground; the blood draw was then repeated. All blood samples were acquired by venipuncture. Prior to each blood draw, a tourniquet was placed over the upper arm below the axilla. An antecubital vein on either arm was visualized under ultrasound guidance, and a 23-G × 3/4” butterfly needle was used for venipuncture. The vials of blood were immediately inverted after blood collection. Hemoglobin assays were processed and analyzed using Sysmex XN-10 analyzer (Sysmex Corporation). The reference range for hemoglobin in our facility was 12.0 to 15.0 g/dL for women and 13.9 to 16.3 g/dL for men. Laboratory technicians were blinded to and uninvolved in the study.

We determined, a priori, that 33 enrolled patients would provide 80% power (alpha 0.05) to detect an average hemoglobin change of 4.1%, assuming that the standard deviation of the hemoglobin change was twice the mean (ie, SD = 8.2%). The Wilcoxon signed-rank test was used to test the significance of postural hemoglobin changes. Analyses were conducted using JMP Pro 13.0 (SAS) and GraphPad Prism 8 (GraphPad Software). Significance was defined at P < .05 for all analyses.

RESULTS

Thirty-nine patients were consented and enrolled in the study; four patients were excluded prior to blood draw (two patients because of interruption of supine time, two patients because of refusal in the morning). Of the 35 patients who completed the study, 13 were women (37%); median age was 49 years (range, 25-83 years). Median supine hemoglobin concentration in our sample was 11.7 g/dL (range, 9.3-18.1 g/dL), and median baseline creatinine level was 0.70 mg/dL (range, 0.5-2.5 mg/dL). Median supine hemoglobin levels were 11.7 g/dL (range, 9.6-13.2 g/dL) in women and 11.8 g/dL (range, 9.3-18.1 g/dL) in men. In aggregate, patients had a median increase in hemoglobin concentration of 0.60 g/dL (range, –0.6 to 1.4 g/dL) with sitting, a 5.2% (range, –4.5% to 15.1%) relative change (P < .001) (Figure 1).

Patient-Level Hemoglobin Changes With Posture Changes
Women had a median increase in hemoglobin concentration of 0.60 g/dL (range, –0.6 to 1.4 g/dL) with sitting, a relative change of 5.3% (range, –4.5% to 12.0%) (P = .02). Men had a median increase in hemoglobin concentration of 0.55 g/dL (range, –0.1 to 1.4 g/dL) with sitting, a 5.0% (range, –0.6% to 15.1%) relative change (P < .001). Ten of 35 participants (29%) exhibited an increase in hemoglobin level of 1.0 g/dL or more (Figure 2).
Absolute and Relative Change in Hemoglobin Concentration With Positional Changes

DISCUSSION

International blood collection guidelines acknowledge postural changes in laboratory values and recommend standardization of patient position to either sitting in a chair or lying flat in a bed, without changes in position for 15 minutes prior to blood draw.14 When these positional accommodations cannot be met, documenting positional disruptions is recommended so that laboratory values can be interpreted accordingly. To the best of our knowledge, no hospital in the United States has standardized patient position as part of phlebotomy procedure such that patient position is documented and can be made available to interpreting providers.

Relative increases in hemoglobin or hematocrit range from 7% to 12% when patients go from supine to standing.8,9,11 The reverse relationship has also been shown, where upright-to-supine position results in decreases in hemoglobin concentrations.10,13 We found that going from supine to a seated position resulted in significant increases in hemoglobin of 0.6 g/dL and in a more than 1 g/dL increase in 29% of the patients. Although four of the 35 patients experienced either no change or a slight decrease in their hemoglobin concentration when going from supine to upright and not all patients saw a uniform effect, providers should be aware that the patient’s position can contribute to changes in hemoglobin concentration in the hospitalized setting. Providers may be able to use this information to avoid an extensive diagnostic workup when anemia is identified in hospitalized patients, although more research is needed to identify patient subsets who are at higher risk for this effect.

Until hospitals implement protocols that require phlebotomists to report patient position during phlebotomy in a standardized fashion, providers should be alert to the fact that supine positioning may result in a hemoglobin level that is significantly lower than that when drawn in a sitting position, and in almost one-third of patients, this difference may be 1.0 g/dL or greater.

Given our study criteria requiring supine positions of at least 6 hours and a baseline hemoglobin concentration >8 g/dL, our sample of patients may have been younger and healthier than the average hospitalized patient on general internal medicine wards. Since greater relative changes in plasma volume shifts and hemoglobin might be seen in patients with lower baseline hemoglobin and lower baseline plasma protein, this selection bias may underestimate the effects of position on hemoglobin changes for the average inpatient population. Additionally, we intentionally sought to obtain sitting hemoglobin levels after the supine samples to avoid the possibility of incorrectly attributing dropping hemoglobin levels to progressive hospital-acquired anemia from phlebotomy or illness. Any concomitant trend of falling hemoglobin levels in our patients would be expected to lead to a systematic underestimation of the positional change in hemoglobin we observed. We did not objectively observe adherence to supine and upright position and instead relied on patient self-reporting, which is one possible contributor to the variable effects of position on hemoglobin concentration, with some patients having no change or decreases in hemoglobin concentrations.

CONCLUSION

Posture can significantly influence hemoglobin levels in hospitalized patients on general medicine wards. Further research can determine whether it would be cost and time effective to standardize patient positions prior to phlebotomy, or at least to report patient positioning with the laboratory testing results.

The World Health Organization (WHO) defines anemia as a hemoglobin value less than 12 g/dL in women and less than 13 g/dL in men.1 Hospital-acquired anemia is loosely defined as normal hemoglobin levels on admission that, at their nadir during hospitalization or on discharge, are less than WHO sex-defined cutoffs. Hospital-acquired anemia or significant decreases in hemoglobin are often identified during hospitalization.2-6 Potential causes include blood loss from phlebotomy, occult gastrointestinal bleeding, hemolysis, anemia of inflammation, and hemodilution due to fluid resuscitation. Of these causes, some are dangerous to patients, some are iatrogenic, and some are due to laboratory error.7 Physicians often evaluate decreases in hemoglobin, which could otherwise be explained by laboratory error, hemodilution, or expected decrease in hemoglobin due to hospitalization, to identify causes that may lead to potential harm.

Jacob et al8 demonstrated the effect of posture on hemoglobin concentrations in healthy volunteers, showing an average 11% relative increase in hemoglobin when going from lying to standing. This increase was attributed to shifts in plasma volume to the vascular space with recumbence. They hypothesized that the initial hemoglobin on admission is measured when patients are upright or recently upright, whereas after admission, patients are more likely to be supine, resulting in lower hemoglobin concentrations. Others have also demonstrated similar effects of patient posture on hemoglobin concentration.9-13 However, these prior results are not readily generalizable to hospitalized patients. These prior studies enrolled healthy volunteers, and most examined postural changes from the supine and standing positions; blood is rarely obtained from hospitalized patients when they are standing.

The aim of this study was to investigate whether postural changes in hemoglobin can be demonstrated in positions that patients routinely encountered during in-hospital phlebotomy: upright in a chair or recumbent in a bed. Patient position, which is not standardized during blood draws, may contribute to lower measured hemoglobin concentrations in some patients, especially sicker individuals who are recumbent more frequently. We hypothesized that going from supine to upright in a chair would result in a relative increase in hemoglobin concentration of 5% to 6%, approximately half the value of going from supine to standing.8 To investigate this, we conducted a quasi-experimental study exploring the effect of position (supine or sitting in chair) on hemoglobin concentrations in medical inpatients.

METHODS

Participants

Patients were enrolled in this single-center study between October 2017 and August 2018. Patients aged 18 years or older who were hospitalized on the general internal medicine wards were screened to determine if they met the following inclusion criteria: hospitalized for <5 days, had blood work scheduled as part of routine care (in order to decrease phlebotomy required by this study), had baseline hemoglobin >8 g/dL, and were able to remain supine without interruption overnight and able to sit in a chair for at least 1 hour the following morning. Patients were excluded from the study if they had a hematologic malignancy, were at risk of >100 mL of blood loss (eg, admitted for gastrointestinal bleeding, planned surgery), had a transfusion requirement, or received intravascular modifiers such as fluid (>100 cc/h) or intravenous diuretics. The Johns Hopkins Institutional Review Board approved this study, and all patients provided written informed consent.

Study Design

Patients enrolled in this quasi-experimental study were asked to remain supine for at least 6 hours overnight. Adherence to the recumbent position was tracked by patient self-report and by corroboration with the patient’s nurse overnight. Any interruptions to supine positioning resulted in exclusion from the study. The following morning, a member of the study team performed phlebotomy while the patient remained supine. Patients were then asked to sit comfortably in a chair for at least 1 hour with their feet on the ground; the blood draw was then repeated. All blood samples were acquired by venipuncture. Prior to each blood draw, a tourniquet was placed over the upper arm below the axilla. An antecubital vein on either arm was visualized under ultrasound guidance, and a 23-G × 3/4” butterfly needle was used for venipuncture. The vials of blood were immediately inverted after blood collection. Hemoglobin assays were processed and analyzed using Sysmex XN-10 analyzer (Sysmex Corporation). The reference range for hemoglobin in our facility was 12.0 to 15.0 g/dL for women and 13.9 to 16.3 g/dL for men. Laboratory technicians were blinded to and uninvolved in the study.

We determined, a priori, that 33 enrolled patients would provide 80% power (alpha 0.05) to detect an average hemoglobin change of 4.1%, assuming that the standard deviation of the hemoglobin change was twice the mean (ie, SD = 8.2%). The Wilcoxon signed-rank test was used to test the significance of postural hemoglobin changes. Analyses were conducted using JMP Pro 13.0 (SAS) and GraphPad Prism 8 (GraphPad Software). Significance was defined at P < .05 for all analyses.

RESULTS

Thirty-nine patients were consented and enrolled in the study; four patients were excluded prior to blood draw (two patients because of interruption of supine time, two patients because of refusal in the morning). Of the 35 patients who completed the study, 13 were women (37%); median age was 49 years (range, 25-83 years). Median supine hemoglobin concentration in our sample was 11.7 g/dL (range, 9.3-18.1 g/dL), and median baseline creatinine level was 0.70 mg/dL (range, 0.5-2.5 mg/dL). Median supine hemoglobin levels were 11.7 g/dL (range, 9.6-13.2 g/dL) in women and 11.8 g/dL (range, 9.3-18.1 g/dL) in men. In aggregate, patients had a median increase in hemoglobin concentration of 0.60 g/dL (range, –0.6 to 1.4 g/dL) with sitting, a 5.2% (range, –4.5% to 15.1%) relative change (P < .001) (Figure 1).

Patient-Level Hemoglobin Changes With Posture Changes
Women had a median increase in hemoglobin concentration of 0.60 g/dL (range, –0.6 to 1.4 g/dL) with sitting, a relative change of 5.3% (range, –4.5% to 12.0%) (P = .02). Men had a median increase in hemoglobin concentration of 0.55 g/dL (range, –0.1 to 1.4 g/dL) with sitting, a 5.0% (range, –0.6% to 15.1%) relative change (P < .001). Ten of 35 participants (29%) exhibited an increase in hemoglobin level of 1.0 g/dL or more (Figure 2).
Absolute and Relative Change in Hemoglobin Concentration With Positional Changes

DISCUSSION

International blood collection guidelines acknowledge postural changes in laboratory values and recommend standardization of patient position to either sitting in a chair or lying flat in a bed, without changes in position for 15 minutes prior to blood draw.14 When these positional accommodations cannot be met, documenting positional disruptions is recommended so that laboratory values can be interpreted accordingly. To the best of our knowledge, no hospital in the United States has standardized patient position as part of phlebotomy procedure such that patient position is documented and can be made available to interpreting providers.

Relative increases in hemoglobin or hematocrit range from 7% to 12% when patients go from supine to standing.8,9,11 The reverse relationship has also been shown, where upright-to-supine position results in decreases in hemoglobin concentrations.10,13 We found that going from supine to a seated position resulted in significant increases in hemoglobin of 0.6 g/dL and in a more than 1 g/dL increase in 29% of the patients. Although four of the 35 patients experienced either no change or a slight decrease in their hemoglobin concentration when going from supine to upright and not all patients saw a uniform effect, providers should be aware that the patient’s position can contribute to changes in hemoglobin concentration in the hospitalized setting. Providers may be able to use this information to avoid an extensive diagnostic workup when anemia is identified in hospitalized patients, although more research is needed to identify patient subsets who are at higher risk for this effect.

Until hospitals implement protocols that require phlebotomists to report patient position during phlebotomy in a standardized fashion, providers should be alert to the fact that supine positioning may result in a hemoglobin level that is significantly lower than that when drawn in a sitting position, and in almost one-third of patients, this difference may be 1.0 g/dL or greater.

Given our study criteria requiring supine positions of at least 6 hours and a baseline hemoglobin concentration >8 g/dL, our sample of patients may have been younger and healthier than the average hospitalized patient on general internal medicine wards. Since greater relative changes in plasma volume shifts and hemoglobin might be seen in patients with lower baseline hemoglobin and lower baseline plasma protein, this selection bias may underestimate the effects of position on hemoglobin changes for the average inpatient population. Additionally, we intentionally sought to obtain sitting hemoglobin levels after the supine samples to avoid the possibility of incorrectly attributing dropping hemoglobin levels to progressive hospital-acquired anemia from phlebotomy or illness. Any concomitant trend of falling hemoglobin levels in our patients would be expected to lead to a systematic underestimation of the positional change in hemoglobin we observed. We did not objectively observe adherence to supine and upright position and instead relied on patient self-reporting, which is one possible contributor to the variable effects of position on hemoglobin concentration, with some patients having no change or decreases in hemoglobin concentrations.

CONCLUSION

Posture can significantly influence hemoglobin levels in hospitalized patients on general medicine wards. Further research can determine whether it would be cost and time effective to standardize patient positions prior to phlebotomy, or at least to report patient positioning with the laboratory testing results.

References

1. DeMaeyer E, Adiels-Tegman M. The prevalence of anaemia in the world. World Health Stat Q. 1985;38(3):302-316.
2. Martin ND, Scantling D. Hospital-acquired anemia. J Infus Nurs. 2015;38(5):330-338. https://doi.org/10.1097/NAN.0000000000000121
3. Thavendiranathan P, Bagai A, Ebidia A, Detsky AS, Choudhry NK. Do blood tests cause anemia in hospitalized patients? The effect of diagnostic phlebotomy on hemoglobin and hematocrit levels. J Gen Intern Med. 2005;20(6):520-524. https://doi.org/10.1111/j.1525-1497.2005.0094.x
4. Salisbury AC, Reid KJ, Alexander KP, et al. Diagnostic blood loss from phlebotomy and hospital-acquired anemia during acute myocardial infarction. Arch Intern Med. 2011;171(18):1646-1653. https://doi.org/10.1001/archinternmed.2011.361
5. Languasco A, Cazap N, Marciano S, et al. Hemoglobin concentration variations over time in general medical inpatients. J Hosp Med. 2010;5(5):283-288. https://doi.org/10.1002/jhm.650
6. van der Bom JG, Cannegieter SC. Hospital-acquired anemia: the contribution of diagnostic blood loss. J Thromb Haemost. 2015;13(6):1157-1159. https://doi.org/10.1111/jth.12886
7. Berkow L. Factors affecting hemoglobin measurement. J Clin Monit Comput. 2013;27(5):499-508. https://doi.org/10.1007/s10877-013-9456-3
8. Jacob G, Raj SR, Ketch T, et al. Postural pseudoanemia: posture-dependent change in hematocrit. Mayo Clin Proc. 2005;80(5):611-614. https://doi.org/10.4065/80.5.611
9. Fawcett JK, Wynn V. Effects of posture on plasma volume and some blood constituents. J Clin Pathol. 1960;13(4):304-310. https://doi.org/10.1136/jcp.13.4.304
10. Tombridge TL. Effect of posture on hematology results. Am J ClinPathol. 1968;49(4):491-493. https://doi.org/10.1093/ajcp/49.4.491
11. Hagan RD, Diaz FJ, Horvath SM. Plasma volume changes with movement to supine and standing positions. J Appl Physiol. 1978;45(3):414-417. https://doi.org/10.1152/jappl.1978.45.3.414
12. Maw GJ, Mackenzie IL, Taylor NA. Redistribution of body fluids during postural manipulations. Acta Physiol Scand. 1995;155(2):157-163. https://doi.org/10.1111/j.1748-1716.1995.tb09960.x
13. Lima-Oliveira G, Guidi GC, Salvagno GL, Danese E, Montagnana M, Lippi G. Patient posture for blood collection by venipuncture: recall for standardization after 28 years. Rev Bras Hematol Hemoter. 2017;39(2):127-132. https://doi.org/10.1016/j.bjhh.2017.01.004
14. Simundic AM, Bölenius K, Cadamuro J, et al. Working Group for Preanalytical Phase (WG-PRE), of the European Federation of Clinical Chemistry and Laboratory Medicine (EFLM) and Latin American Working Group for Preanalytical Phase (WG-PRE-LATAM) of the Latin America Confederation of Clinical Biochemistry (COLABIOCLI). Joint EFLM-COLABIOCLI recommendation for venous blood sampling. Clin Chem Lab Med. 2018;56(12):2015-2038. https://doi.org/10.1515/cclm-2018-0602

References

1. DeMaeyer E, Adiels-Tegman M. The prevalence of anaemia in the world. World Health Stat Q. 1985;38(3):302-316.
2. Martin ND, Scantling D. Hospital-acquired anemia. J Infus Nurs. 2015;38(5):330-338. https://doi.org/10.1097/NAN.0000000000000121
3. Thavendiranathan P, Bagai A, Ebidia A, Detsky AS, Choudhry NK. Do blood tests cause anemia in hospitalized patients? The effect of diagnostic phlebotomy on hemoglobin and hematocrit levels. J Gen Intern Med. 2005;20(6):520-524. https://doi.org/10.1111/j.1525-1497.2005.0094.x
4. Salisbury AC, Reid KJ, Alexander KP, et al. Diagnostic blood loss from phlebotomy and hospital-acquired anemia during acute myocardial infarction. Arch Intern Med. 2011;171(18):1646-1653. https://doi.org/10.1001/archinternmed.2011.361
5. Languasco A, Cazap N, Marciano S, et al. Hemoglobin concentration variations over time in general medical inpatients. J Hosp Med. 2010;5(5):283-288. https://doi.org/10.1002/jhm.650
6. van der Bom JG, Cannegieter SC. Hospital-acquired anemia: the contribution of diagnostic blood loss. J Thromb Haemost. 2015;13(6):1157-1159. https://doi.org/10.1111/jth.12886
7. Berkow L. Factors affecting hemoglobin measurement. J Clin Monit Comput. 2013;27(5):499-508. https://doi.org/10.1007/s10877-013-9456-3
8. Jacob G, Raj SR, Ketch T, et al. Postural pseudoanemia: posture-dependent change in hematocrit. Mayo Clin Proc. 2005;80(5):611-614. https://doi.org/10.4065/80.5.611
9. Fawcett JK, Wynn V. Effects of posture on plasma volume and some blood constituents. J Clin Pathol. 1960;13(4):304-310. https://doi.org/10.1136/jcp.13.4.304
10. Tombridge TL. Effect of posture on hematology results. Am J ClinPathol. 1968;49(4):491-493. https://doi.org/10.1093/ajcp/49.4.491
11. Hagan RD, Diaz FJ, Horvath SM. Plasma volume changes with movement to supine and standing positions. J Appl Physiol. 1978;45(3):414-417. https://doi.org/10.1152/jappl.1978.45.3.414
12. Maw GJ, Mackenzie IL, Taylor NA. Redistribution of body fluids during postural manipulations. Acta Physiol Scand. 1995;155(2):157-163. https://doi.org/10.1111/j.1748-1716.1995.tb09960.x
13. Lima-Oliveira G, Guidi GC, Salvagno GL, Danese E, Montagnana M, Lippi G. Patient posture for blood collection by venipuncture: recall for standardization after 28 years. Rev Bras Hematol Hemoter. 2017;39(2):127-132. https://doi.org/10.1016/j.bjhh.2017.01.004
14. Simundic AM, Bölenius K, Cadamuro J, et al. Working Group for Preanalytical Phase (WG-PRE), of the European Federation of Clinical Chemistry and Laboratory Medicine (EFLM) and Latin American Working Group for Preanalytical Phase (WG-PRE-LATAM) of the Latin America Confederation of Clinical Biochemistry (COLABIOCLI). Joint EFLM-COLABIOCLI recommendation for venous blood sampling. Clin Chem Lab Med. 2018;56(12):2015-2038. https://doi.org/10.1515/cclm-2018-0602

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Clinical Guideline Highlights for the Hospitalist: Management of Acute and Chronic Pain in Sickle Cell Disease

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Clinical Guideline Highlights for the Hospitalist: Management of Acute and Chronic Pain in Sickle Cell Disease

Sickle cell disease (SCD) affects an estimated 100,000 people in the United States.1 Pain is the most common complication of SCD and the primary reason patients with SCD seek medical attention.2 In 2016, three-fourths of the approximately 130,000 SCD-related hospitalizations in the United States involved pain crises.3 When managing patients with SCD and chronic pain, an individualized and interdisciplinary approach is crucial. In 2020, the American Society of Hematology (ASH) developed guidelines reflecting the latest evidence in managing acute and chronic pain in adult and pediatric patients with SCD. The ASH guidelines provide 18 recommendations; here, we highlight the 8 recommendations most pertinent to the hospitalist.

KEY RECOMMENDATIONS FOR THE HOSPITALIST

Acute Pain

Acute pain in the guideline is defined as pain that results in an unplanned visit to an acute care center for treatment.

Recommendation 1. For adult and pediatric patients presenting to an acute care setting with SCD-related acute pain, the ASH guideline panel recommends rapid (ie, within 1 hour of arrival at the emergency department [ED]) assessment and administration of analgesia, with reassessments every 30-60 minutes to optimize pain control (Strong recommendation; low certainty in the evidence about effects).

Although the perceived benefits are unclear due to insufficient evidence, the panel agrees that delaying pain management results in undeniable harm to patients. Hence, this recommendation was deemed both acceptable and ethical. Rapid evaluation also allows for earlier identification and treatment of other potential SCD-related complications.

Recommendation 2. For adult and pediatric patients presenting to an acute care setting with SCD-associated pain for whom opioid therapy is indicated, the ASH guideline panel suggests tailored opioid dosing based on consideration of baseline opioid therapy and prior effective therapy. (For adults: conditional recommendation; moderate certainty in the evidence about effects. For children: conditional recommendation; low certainty in the evidence about effects).

One randomized controlled trial examined patient-specific opioid dosing (based on current chronic opioid therapy [COT] and previously known effective acute pain management) vs weight-based dosing in the ED and found that participants randomized into the patient-specific protocol had a greater reduction in pain and decreased rate of hospital admission.4

The panel acknowledges that intravenous patient-controlled opioid analgesia is generally the standard of care at most institutions. However, no clear data address whether continuous opioid infusion in addition to on-demand dosing is beneficial.

Recommendation 3. For adult and pediatric patients with acute pain related to SCD, the ASH guideline panel suggests a short course (5 to 7 days) of nonsteroidal anti-inflammatory drugs (NSAIDs) in addition to opioids (Conditional recommendation; very low certainty in the evidence about effects).

The use of NSAIDs for managing pain in hospitalized patients with SCD has been associated with a reduction in the use of opioids in the inpatient setting and decreased lengths of stay.5 The potential harms of NSAIDs, including renal and gastrointestinal toxicity, however, should be factored into the decision-making as the risks may outweigh the potential benefits.

Recommendation 4. For adult and pediatric patients with SCD hospitalized for acute pain, the ASH guideline panel suggests a subanesthetic (analgesic) infusion of ketamine as adjunctive treatment of pain refractory or not effectively treated with opioids alone (Conditional recommendation; very low certainty in the evidence about effects). The guideline panel also suggests regional anesthesia for localized pain refractory or not effectively treated with opioids alone (Conditional recommendation; very low certainty in the evidence about effects).

Studies have demonstrated reduced pain and opioid utilization in individuals who received adjuvant ketamine infusions6 or regional anesthesia (ie, epidural).7 Feasibility, however, is limited to centers that have the appropriate experience and expertise with these interventions.

Recommendation 5. For adult and pediatric patients who have recurrent acute pain associated with SCD, the ASH guideline panel suggests against chronic monthly transfusion therapy as a first-line strategy to prevent or reduce recurrent acute pain episodes (Conditional recommendation; low certainty in the evidence about effects). The evidence for monthly transfusions in preventing recurrent pain is limited. There is, however, a moderate risk of harm, including iron overload and transfusion reactions, in addition to substantial burden and costs.

Chronic Pain

Chronic pain in the guideline is defined as ongoing pain present on most days over the past 6 months.

Recommendation 6. For adult patients with SCD who have chronic pain from the SCD-related identifiable cause avascular necrosis (AVN) of the bone, the ASH guideline panel suggests the use of serotonin-norepinephrine reuptake inhibitors (SNRIs) or NSAIDs in the context of a comprehensive disease and pain management plan (Conditional recommendation; very low certainty in the evidence about effects). For patients with no identifiable cause beyond SCD, the guideline panel suggests SNRIs, tricyclic antidepressants, or gabapentinoids for pain management (Conditional recommendation; very low certainty in the evidence about effects). Given the lack of direct evidence, indirect evidence was used to formulate these recommendations. For pain associated with AVN, data were extrapolated from literature on osteoarthritis, a form of degenerative arthropathy. For pain without an identifiable cause, evidence was taken from studies on fibromyalgia, a condition the panel felt most closely aligned with chronic pain related to SCD.

No recommendations were made for pediatric patients as the indirect evidence base only addressed adult patients.

Recommendation 7. For adult and pediatric patients with SCD and emerging and/or recently developed chronic pain, the ASH guideline panel does not recommend initiating COT unless pain is refractory to multiple other treatment modalities (Conditional recommendation; very low certainty in the evidence about effects). For patients receiving COT who are functioning well and have perceived benefit, the ASH guideline panel suggests shared decision-making for continuation of COT (Conditional recommendation; very low certainty in the evidence about effects).

High-quality data on the benefit of long-term COT in individuals with chronic noncancer pain are lacking. The panel maintains that the decision to initiate or continue COT should be individualized after weighing appropriate risks and benefits.

Recommendation 8. For adult and pediatric patients with chronic pain related to SCD, the panel suggests cognitive and behavioral pain management strategies in the context of a comprehensive disease and pain management plan (Conditional recommendation; very low certainty in the evidence about effects). Cognitive behavioral therapy may decrease overall pain intensity and improve coping skills.8 The panel agrees that medications alone may not be effective in reducing the burden of chronic pain in adult and pediatric patients with SCD.

CRITIQUE

The guidelines were created by a multidisciplinary panel that included physicians from hematology, pain medicine, psychiatry, and emergency medicine, a doctoral nurse practitioner, and two patient representatives. The Mayo Evidence-Based Practice Research Program supported the guideline-development process. The GRADE (Grading of Recommendations Assessment, Development, and Evaluation) approach was used to assess evidence and make recommendations.

High-quality data in treating acute and chronic pain in both adult and pediatric patients with SCD are limited. As such, the majority of recommendations in these guidelines are conditional. The panel included studies that were indirectly related to SCD based on consensus (eg, inferred data from disease processes thought to be similar to SCD). One panelist disclosed receiving direct payments from a company that could be affected by these guidelines; however, it was deemed that the conflict was unlikely to have influenced any recommendations.

AREAS IN NEED OF FUTURE STUDY

The panel acknowledges that further investigation is needed for both nonpharmacologic and pharmacologic modalities in treating acute and chronic pain related to SCD. Examples include evaluating the comparative-effectiveness of COT vs nonopioid pharmacotherapy, the benefits and harms of continuous opioid infusions in acute pain crises, and the impact of chronic transfusions on acute and chronic pain.

References

1. Data & statistics on sickle cell disease. Centers for Disease Control and Prevention. Accessed August 23, 2020. https://www.cdc.gov/ncbddd/sicklecell/data.html
2. Complications and treatments of sickle cell disease. Centers for Disease Control and Prevention. Accessed August 23, 2020. https://www.cdc.gov/ncbddd/sicklecell/treatments.html
3. Fingar KR, Owens PL, Reid LD, Mistry KB, Barrett ML. Characteristics of Inpatient Hospital Stays Involving Sickle Cell Disease, 2000-2016. Agency for Healthcare Research and Quality. Healthcare Cost and Utilization Project. Statistical Brief 251. September 2019. Accessed August 23, 2020. www.hcup-us.ahrq.gov/reports/statbriefs/sb251-Sickle-Cell-Disease-Stays-2016.pdf
4. Tanabe P, Silva S, Bosworth HB, et al. A randomized controlled trial comparing two vaso-occlusive episode (VOE) protocols in sickle cell disease (SCD). Am J Hematol. 2018;93(2):159-168. https://doi.org/10.1002/ajh.24948
5. Perlin E, Finke H, Castro O, et al. Enhancement of pain control with ketorolac tromethamine in patients with sickle cell vaso-occlusive crisis. Am J Hematol. 1994;46(1):43-47. https://doi.org/10.1002/ajh.2830460108
6. Sheehy KA, Lippold C, Rice AL, et al. Subanesthetic ketamine for pain management in hospitalized children, adolescents, and young adults: a single-center cohort study. J Pain Res. 2017;10:787-795. https://doi.org/10.2147/jpr.s131156
7. New T, Venable C, Fraser L, et al. Management of refractory pain in hospitalized adolescents with sickle cell disease: changing from intravenous opioids to continuous infusion epidural analgesia. J Pediatr Hematol Oncol. 2014;36(6):e398-e402. https://doi.org/10.1097/mph.0000000000000026
8. Schatz J, Schlenz AM, McClellan CB, et al. Changes in coping, pain, and activity after cognitive-behavioral training: a randomized clinical trial for pediatric sickle cell disease using smartphones. Clin J Pain. 2015;31(6):536-547. https://doi.org/10.1097/ajp.0000000000000183

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Related Articles

Sickle cell disease (SCD) affects an estimated 100,000 people in the United States.1 Pain is the most common complication of SCD and the primary reason patients with SCD seek medical attention.2 In 2016, three-fourths of the approximately 130,000 SCD-related hospitalizations in the United States involved pain crises.3 When managing patients with SCD and chronic pain, an individualized and interdisciplinary approach is crucial. In 2020, the American Society of Hematology (ASH) developed guidelines reflecting the latest evidence in managing acute and chronic pain in adult and pediatric patients with SCD. The ASH guidelines provide 18 recommendations; here, we highlight the 8 recommendations most pertinent to the hospitalist.

KEY RECOMMENDATIONS FOR THE HOSPITALIST

Acute Pain

Acute pain in the guideline is defined as pain that results in an unplanned visit to an acute care center for treatment.

Recommendation 1. For adult and pediatric patients presenting to an acute care setting with SCD-related acute pain, the ASH guideline panel recommends rapid (ie, within 1 hour of arrival at the emergency department [ED]) assessment and administration of analgesia, with reassessments every 30-60 minutes to optimize pain control (Strong recommendation; low certainty in the evidence about effects).

Although the perceived benefits are unclear due to insufficient evidence, the panel agrees that delaying pain management results in undeniable harm to patients. Hence, this recommendation was deemed both acceptable and ethical. Rapid evaluation also allows for earlier identification and treatment of other potential SCD-related complications.

Recommendation 2. For adult and pediatric patients presenting to an acute care setting with SCD-associated pain for whom opioid therapy is indicated, the ASH guideline panel suggests tailored opioid dosing based on consideration of baseline opioid therapy and prior effective therapy. (For adults: conditional recommendation; moderate certainty in the evidence about effects. For children: conditional recommendation; low certainty in the evidence about effects).

One randomized controlled trial examined patient-specific opioid dosing (based on current chronic opioid therapy [COT] and previously known effective acute pain management) vs weight-based dosing in the ED and found that participants randomized into the patient-specific protocol had a greater reduction in pain and decreased rate of hospital admission.4

The panel acknowledges that intravenous patient-controlled opioid analgesia is generally the standard of care at most institutions. However, no clear data address whether continuous opioid infusion in addition to on-demand dosing is beneficial.

Recommendation 3. For adult and pediatric patients with acute pain related to SCD, the ASH guideline panel suggests a short course (5 to 7 days) of nonsteroidal anti-inflammatory drugs (NSAIDs) in addition to opioids (Conditional recommendation; very low certainty in the evidence about effects).

The use of NSAIDs for managing pain in hospitalized patients with SCD has been associated with a reduction in the use of opioids in the inpatient setting and decreased lengths of stay.5 The potential harms of NSAIDs, including renal and gastrointestinal toxicity, however, should be factored into the decision-making as the risks may outweigh the potential benefits.

Recommendation 4. For adult and pediatric patients with SCD hospitalized for acute pain, the ASH guideline panel suggests a subanesthetic (analgesic) infusion of ketamine as adjunctive treatment of pain refractory or not effectively treated with opioids alone (Conditional recommendation; very low certainty in the evidence about effects). The guideline panel also suggests regional anesthesia for localized pain refractory or not effectively treated with opioids alone (Conditional recommendation; very low certainty in the evidence about effects).

Studies have demonstrated reduced pain and opioid utilization in individuals who received adjuvant ketamine infusions6 or regional anesthesia (ie, epidural).7 Feasibility, however, is limited to centers that have the appropriate experience and expertise with these interventions.

Recommendation 5. For adult and pediatric patients who have recurrent acute pain associated with SCD, the ASH guideline panel suggests against chronic monthly transfusion therapy as a first-line strategy to prevent or reduce recurrent acute pain episodes (Conditional recommendation; low certainty in the evidence about effects). The evidence for monthly transfusions in preventing recurrent pain is limited. There is, however, a moderate risk of harm, including iron overload and transfusion reactions, in addition to substantial burden and costs.

Chronic Pain

Chronic pain in the guideline is defined as ongoing pain present on most days over the past 6 months.

Recommendation 6. For adult patients with SCD who have chronic pain from the SCD-related identifiable cause avascular necrosis (AVN) of the bone, the ASH guideline panel suggests the use of serotonin-norepinephrine reuptake inhibitors (SNRIs) or NSAIDs in the context of a comprehensive disease and pain management plan (Conditional recommendation; very low certainty in the evidence about effects). For patients with no identifiable cause beyond SCD, the guideline panel suggests SNRIs, tricyclic antidepressants, or gabapentinoids for pain management (Conditional recommendation; very low certainty in the evidence about effects). Given the lack of direct evidence, indirect evidence was used to formulate these recommendations. For pain associated with AVN, data were extrapolated from literature on osteoarthritis, a form of degenerative arthropathy. For pain without an identifiable cause, evidence was taken from studies on fibromyalgia, a condition the panel felt most closely aligned with chronic pain related to SCD.

No recommendations were made for pediatric patients as the indirect evidence base only addressed adult patients.

Recommendation 7. For adult and pediatric patients with SCD and emerging and/or recently developed chronic pain, the ASH guideline panel does not recommend initiating COT unless pain is refractory to multiple other treatment modalities (Conditional recommendation; very low certainty in the evidence about effects). For patients receiving COT who are functioning well and have perceived benefit, the ASH guideline panel suggests shared decision-making for continuation of COT (Conditional recommendation; very low certainty in the evidence about effects).

High-quality data on the benefit of long-term COT in individuals with chronic noncancer pain are lacking. The panel maintains that the decision to initiate or continue COT should be individualized after weighing appropriate risks and benefits.

Recommendation 8. For adult and pediatric patients with chronic pain related to SCD, the panel suggests cognitive and behavioral pain management strategies in the context of a comprehensive disease and pain management plan (Conditional recommendation; very low certainty in the evidence about effects). Cognitive behavioral therapy may decrease overall pain intensity and improve coping skills.8 The panel agrees that medications alone may not be effective in reducing the burden of chronic pain in adult and pediatric patients with SCD.

CRITIQUE

The guidelines were created by a multidisciplinary panel that included physicians from hematology, pain medicine, psychiatry, and emergency medicine, a doctoral nurse practitioner, and two patient representatives. The Mayo Evidence-Based Practice Research Program supported the guideline-development process. The GRADE (Grading of Recommendations Assessment, Development, and Evaluation) approach was used to assess evidence and make recommendations.

High-quality data in treating acute and chronic pain in both adult and pediatric patients with SCD are limited. As such, the majority of recommendations in these guidelines are conditional. The panel included studies that were indirectly related to SCD based on consensus (eg, inferred data from disease processes thought to be similar to SCD). One panelist disclosed receiving direct payments from a company that could be affected by these guidelines; however, it was deemed that the conflict was unlikely to have influenced any recommendations.

AREAS IN NEED OF FUTURE STUDY

The panel acknowledges that further investigation is needed for both nonpharmacologic and pharmacologic modalities in treating acute and chronic pain related to SCD. Examples include evaluating the comparative-effectiveness of COT vs nonopioid pharmacotherapy, the benefits and harms of continuous opioid infusions in acute pain crises, and the impact of chronic transfusions on acute and chronic pain.

Sickle cell disease (SCD) affects an estimated 100,000 people in the United States.1 Pain is the most common complication of SCD and the primary reason patients with SCD seek medical attention.2 In 2016, three-fourths of the approximately 130,000 SCD-related hospitalizations in the United States involved pain crises.3 When managing patients with SCD and chronic pain, an individualized and interdisciplinary approach is crucial. In 2020, the American Society of Hematology (ASH) developed guidelines reflecting the latest evidence in managing acute and chronic pain in adult and pediatric patients with SCD. The ASH guidelines provide 18 recommendations; here, we highlight the 8 recommendations most pertinent to the hospitalist.

KEY RECOMMENDATIONS FOR THE HOSPITALIST

Acute Pain

Acute pain in the guideline is defined as pain that results in an unplanned visit to an acute care center for treatment.

Recommendation 1. For adult and pediatric patients presenting to an acute care setting with SCD-related acute pain, the ASH guideline panel recommends rapid (ie, within 1 hour of arrival at the emergency department [ED]) assessment and administration of analgesia, with reassessments every 30-60 minutes to optimize pain control (Strong recommendation; low certainty in the evidence about effects).

Although the perceived benefits are unclear due to insufficient evidence, the panel agrees that delaying pain management results in undeniable harm to patients. Hence, this recommendation was deemed both acceptable and ethical. Rapid evaluation also allows for earlier identification and treatment of other potential SCD-related complications.

Recommendation 2. For adult and pediatric patients presenting to an acute care setting with SCD-associated pain for whom opioid therapy is indicated, the ASH guideline panel suggests tailored opioid dosing based on consideration of baseline opioid therapy and prior effective therapy. (For adults: conditional recommendation; moderate certainty in the evidence about effects. For children: conditional recommendation; low certainty in the evidence about effects).

One randomized controlled trial examined patient-specific opioid dosing (based on current chronic opioid therapy [COT] and previously known effective acute pain management) vs weight-based dosing in the ED and found that participants randomized into the patient-specific protocol had a greater reduction in pain and decreased rate of hospital admission.4

The panel acknowledges that intravenous patient-controlled opioid analgesia is generally the standard of care at most institutions. However, no clear data address whether continuous opioid infusion in addition to on-demand dosing is beneficial.

Recommendation 3. For adult and pediatric patients with acute pain related to SCD, the ASH guideline panel suggests a short course (5 to 7 days) of nonsteroidal anti-inflammatory drugs (NSAIDs) in addition to opioids (Conditional recommendation; very low certainty in the evidence about effects).

The use of NSAIDs for managing pain in hospitalized patients with SCD has been associated with a reduction in the use of opioids in the inpatient setting and decreased lengths of stay.5 The potential harms of NSAIDs, including renal and gastrointestinal toxicity, however, should be factored into the decision-making as the risks may outweigh the potential benefits.

Recommendation 4. For adult and pediatric patients with SCD hospitalized for acute pain, the ASH guideline panel suggests a subanesthetic (analgesic) infusion of ketamine as adjunctive treatment of pain refractory or not effectively treated with opioids alone (Conditional recommendation; very low certainty in the evidence about effects). The guideline panel also suggests regional anesthesia for localized pain refractory or not effectively treated with opioids alone (Conditional recommendation; very low certainty in the evidence about effects).

Studies have demonstrated reduced pain and opioid utilization in individuals who received adjuvant ketamine infusions6 or regional anesthesia (ie, epidural).7 Feasibility, however, is limited to centers that have the appropriate experience and expertise with these interventions.

Recommendation 5. For adult and pediatric patients who have recurrent acute pain associated with SCD, the ASH guideline panel suggests against chronic monthly transfusion therapy as a first-line strategy to prevent or reduce recurrent acute pain episodes (Conditional recommendation; low certainty in the evidence about effects). The evidence for monthly transfusions in preventing recurrent pain is limited. There is, however, a moderate risk of harm, including iron overload and transfusion reactions, in addition to substantial burden and costs.

Chronic Pain

Chronic pain in the guideline is defined as ongoing pain present on most days over the past 6 months.

Recommendation 6. For adult patients with SCD who have chronic pain from the SCD-related identifiable cause avascular necrosis (AVN) of the bone, the ASH guideline panel suggests the use of serotonin-norepinephrine reuptake inhibitors (SNRIs) or NSAIDs in the context of a comprehensive disease and pain management plan (Conditional recommendation; very low certainty in the evidence about effects). For patients with no identifiable cause beyond SCD, the guideline panel suggests SNRIs, tricyclic antidepressants, or gabapentinoids for pain management (Conditional recommendation; very low certainty in the evidence about effects). Given the lack of direct evidence, indirect evidence was used to formulate these recommendations. For pain associated with AVN, data were extrapolated from literature on osteoarthritis, a form of degenerative arthropathy. For pain without an identifiable cause, evidence was taken from studies on fibromyalgia, a condition the panel felt most closely aligned with chronic pain related to SCD.

No recommendations were made for pediatric patients as the indirect evidence base only addressed adult patients.

Recommendation 7. For adult and pediatric patients with SCD and emerging and/or recently developed chronic pain, the ASH guideline panel does not recommend initiating COT unless pain is refractory to multiple other treatment modalities (Conditional recommendation; very low certainty in the evidence about effects). For patients receiving COT who are functioning well and have perceived benefit, the ASH guideline panel suggests shared decision-making for continuation of COT (Conditional recommendation; very low certainty in the evidence about effects).

High-quality data on the benefit of long-term COT in individuals with chronic noncancer pain are lacking. The panel maintains that the decision to initiate or continue COT should be individualized after weighing appropriate risks and benefits.

Recommendation 8. For adult and pediatric patients with chronic pain related to SCD, the panel suggests cognitive and behavioral pain management strategies in the context of a comprehensive disease and pain management plan (Conditional recommendation; very low certainty in the evidence about effects). Cognitive behavioral therapy may decrease overall pain intensity and improve coping skills.8 The panel agrees that medications alone may not be effective in reducing the burden of chronic pain in adult and pediatric patients with SCD.

CRITIQUE

The guidelines were created by a multidisciplinary panel that included physicians from hematology, pain medicine, psychiatry, and emergency medicine, a doctoral nurse practitioner, and two patient representatives. The Mayo Evidence-Based Practice Research Program supported the guideline-development process. The GRADE (Grading of Recommendations Assessment, Development, and Evaluation) approach was used to assess evidence and make recommendations.

High-quality data in treating acute and chronic pain in both adult and pediatric patients with SCD are limited. As such, the majority of recommendations in these guidelines are conditional. The panel included studies that were indirectly related to SCD based on consensus (eg, inferred data from disease processes thought to be similar to SCD). One panelist disclosed receiving direct payments from a company that could be affected by these guidelines; however, it was deemed that the conflict was unlikely to have influenced any recommendations.

AREAS IN NEED OF FUTURE STUDY

The panel acknowledges that further investigation is needed for both nonpharmacologic and pharmacologic modalities in treating acute and chronic pain related to SCD. Examples include evaluating the comparative-effectiveness of COT vs nonopioid pharmacotherapy, the benefits and harms of continuous opioid infusions in acute pain crises, and the impact of chronic transfusions on acute and chronic pain.

References

1. Data & statistics on sickle cell disease. Centers for Disease Control and Prevention. Accessed August 23, 2020. https://www.cdc.gov/ncbddd/sicklecell/data.html
2. Complications and treatments of sickle cell disease. Centers for Disease Control and Prevention. Accessed August 23, 2020. https://www.cdc.gov/ncbddd/sicklecell/treatments.html
3. Fingar KR, Owens PL, Reid LD, Mistry KB, Barrett ML. Characteristics of Inpatient Hospital Stays Involving Sickle Cell Disease, 2000-2016. Agency for Healthcare Research and Quality. Healthcare Cost and Utilization Project. Statistical Brief 251. September 2019. Accessed August 23, 2020. www.hcup-us.ahrq.gov/reports/statbriefs/sb251-Sickle-Cell-Disease-Stays-2016.pdf
4. Tanabe P, Silva S, Bosworth HB, et al. A randomized controlled trial comparing two vaso-occlusive episode (VOE) protocols in sickle cell disease (SCD). Am J Hematol. 2018;93(2):159-168. https://doi.org/10.1002/ajh.24948
5. Perlin E, Finke H, Castro O, et al. Enhancement of pain control with ketorolac tromethamine in patients with sickle cell vaso-occlusive crisis. Am J Hematol. 1994;46(1):43-47. https://doi.org/10.1002/ajh.2830460108
6. Sheehy KA, Lippold C, Rice AL, et al. Subanesthetic ketamine for pain management in hospitalized children, adolescents, and young adults: a single-center cohort study. J Pain Res. 2017;10:787-795. https://doi.org/10.2147/jpr.s131156
7. New T, Venable C, Fraser L, et al. Management of refractory pain in hospitalized adolescents with sickle cell disease: changing from intravenous opioids to continuous infusion epidural analgesia. J Pediatr Hematol Oncol. 2014;36(6):e398-e402. https://doi.org/10.1097/mph.0000000000000026
8. Schatz J, Schlenz AM, McClellan CB, et al. Changes in coping, pain, and activity after cognitive-behavioral training: a randomized clinical trial for pediatric sickle cell disease using smartphones. Clin J Pain. 2015;31(6):536-547. https://doi.org/10.1097/ajp.0000000000000183

References

1. Data & statistics on sickle cell disease. Centers for Disease Control and Prevention. Accessed August 23, 2020. https://www.cdc.gov/ncbddd/sicklecell/data.html
2. Complications and treatments of sickle cell disease. Centers for Disease Control and Prevention. Accessed August 23, 2020. https://www.cdc.gov/ncbddd/sicklecell/treatments.html
3. Fingar KR, Owens PL, Reid LD, Mistry KB, Barrett ML. Characteristics of Inpatient Hospital Stays Involving Sickle Cell Disease, 2000-2016. Agency for Healthcare Research and Quality. Healthcare Cost and Utilization Project. Statistical Brief 251. September 2019. Accessed August 23, 2020. www.hcup-us.ahrq.gov/reports/statbriefs/sb251-Sickle-Cell-Disease-Stays-2016.pdf
4. Tanabe P, Silva S, Bosworth HB, et al. A randomized controlled trial comparing two vaso-occlusive episode (VOE) protocols in sickle cell disease (SCD). Am J Hematol. 2018;93(2):159-168. https://doi.org/10.1002/ajh.24948
5. Perlin E, Finke H, Castro O, et al. Enhancement of pain control with ketorolac tromethamine in patients with sickle cell vaso-occlusive crisis. Am J Hematol. 1994;46(1):43-47. https://doi.org/10.1002/ajh.2830460108
6. Sheehy KA, Lippold C, Rice AL, et al. Subanesthetic ketamine for pain management in hospitalized children, adolescents, and young adults: a single-center cohort study. J Pain Res. 2017;10:787-795. https://doi.org/10.2147/jpr.s131156
7. New T, Venable C, Fraser L, et al. Management of refractory pain in hospitalized adolescents with sickle cell disease: changing from intravenous opioids to continuous infusion epidural analgesia. J Pediatr Hematol Oncol. 2014;36(6):e398-e402. https://doi.org/10.1097/mph.0000000000000026
8. Schatz J, Schlenz AM, McClellan CB, et al. Changes in coping, pain, and activity after cognitive-behavioral training: a randomized clinical trial for pediatric sickle cell disease using smartphones. Clin J Pain. 2015;31(6):536-547. https://doi.org/10.1097/ajp.0000000000000183

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Procedural Competency Among Hospitalists: A Literature Review and Future Considerations

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Procedural Competency Among Hospitalists: A Literature Review and Future Considerations

Over the past 20 years, hospitalists have served as the primary workforce for the clinical care of medical inpatients in the United States.1,2 Core competencies1 state that hospitalists should be able to perform the following bedside procedures: lumbar puncture, paracentesis, thoracentesis, arthrocentesis, and central venous catheter placement. More recently, standard of care has dictated that these procedures be performed under ultrasound guidance,3-6 and thus hospitalists are also expected to be adept at point-of-care ultrasound (POCUS).7

However, no current national standard exists for ensuring basic competency among hospitalists performing bedside procedures. In addition, hospitalists’ procedural volumes are declining,8,9 and standards for procedural training during internal medicine residency have been reduced.10 As a result, many residents who intend to become hospitalists are no longer prepared to perform these procedures.

The ramifications of the loss of procedural competency for hospitalists are manifold. Technical errors are a significant source of patient morbidity and mortality,11-15 and complications arising specifically from nonoperative procedures range from 0 to 19%,16 although these data do not distinguish technical errors from unpreventable adverse events nor the degree to which hospitalists contributed to these complications. Second, hospitalists in academic medical centers might be ill equipped to function as supervisors of trainees performing procedures, which could perpetuate a cycle of suboptimal technical skills.17 Finally, the discrepancy between consensus guidelines for hospitalists and their scope of practice represents a significant area of risk management for institutions that base their credentialing policies on published competencies.

There are many compelling reasons for why hospitalists should maintain—in fact reclaim—a primary role in bedside procedures.18 Hospitalists in community and rural settings might not have easy access to procedural specialists. In academic institutions, hospitalists are the primary instructors and supervisors of procedures performed by internal medicine residents. The increased availability of POCUS allows formally trained hospitalists to perform procedures more safely under imaging guidance.16

The literature on procedures performed by hospitalists, although limited, has focused on POCUS, systems innovations such as medical procedure services (MPS), and policy recommendations for procedural credentialing. Most studies on effective procedural instructional approaches have been conducted among trainees, who are procedural novices. This research does not sufficiently address the dilemma that hospitalists face as independent physicians for whom procedures are not a significant component of their practice, yet are expected to perform invasive procedures occasionally. The purpose of our literature review is to synthesize the available research to characterize contributors to hospitalists’ procedural competency. We conclude with considerations for hospital medicine practice.

METHODS

We performed a structured literature search for peer-reviewed articles related to hospitalists conducting procedures, being trained in procedures, or related to hospitalist-run MPS. We focused our search on the core hospitalist procedures with the highest potential morbidity (ie, lumbar puncture, abdominal paracentesis, thoracentesis, and central venous catheterization). We searched PubMed and Google Scholar for articles published since 1996 (when the term “hospitalists” was first coined) using keyword searches for [hospitalist OR hospital medicine] AND [procedur* OR medical procedur* OR medical procedure service] OR [(procedur* AND (train* OR educat* OR teach OR instruct*)] OR abdominal paracentes* OR thoracentes* OR lumbar puncture OR central venous catheter* OR ultrasound OR point-of-care. We included original research, brief research reports, perspectives, guidelines, and consensus statements. Exclusion criteria were articles that focused on nonhospitalists and conference abstracts. We used pearling to identify secondary sources from included articles’ bibliographies, without limits on year of publication.

RESULTS

Trends Towards Specialist Referrals

Between 1986 and 2007, the number and variety of procedures performed by internists decreased by half.19 Hospitalists still completed procedures in greater volume and variety than nonhospitalists,8 with approximately 50% of hospitalists performing lumbar punctures (50%), abdominal paracenteses (49%), and thoracenteses (44%) compared with less than 25% for all three procedures for nonhospitalists. Additionally, only 11% of surveyed hospitalists8 performed all nine core procedures, although these included procedures that are largely cognitive in nature (eg, electrocardiogram interpretation, chest X-ray interpretation) or procedures that have been relegated to other specialists (eg, endotracheal intubation, ventilator management, or joint injection/aspiration).

Surveys showed that, especially in larger cities and academic centers, procedural specialists have taken over a disproportionate share of procedures even as the number of procedures performed continued to rise.20 Between 1993 and 2008, the number of paracenteses and thoracenteses increased by 133% and decreased by 14%, respectively, but the share of procedures performed by radiologists increased by 964% and 358%, respectively, as evident in an analysis of Medicare billing data.20 A more recent study of Medicare claims from 2004 to 2016 similarly revealed that the percentage of paracenteses performed by radiologists compared with nonradiologists rose from 70% to 80% and thoracenteses from 47% to 66%, respectively.21 Comparable trends were apparent in claims data for lumbar punctures; between 1991 and 2011, the share of lumbar punctures performed by radiologists rose from 11% to 48%.22

In academic medical centers, hospitalists might have the opportunity to pursue other activities (eg, education, administration, research) as they progress in their careers, resulting in less clinical activity. Although hospitalists who are more clinically active in hospital care tended to perform more procedures,8 those with smaller clinical footprints reported lower levels of comfort with performing procedures8 and might have less available time to maintain procedural competency or train in new technologies such as POCUS.17

Additionally, hospitalists in both academic and community settings cited efficiency as a major reason for procedural referral. Hospitalists tended to perform more procedures if they had fixed salaries or if less than 50% of their income was based on clinical productivity, although this trend was not significant.8 Further, they also might be motivated by competing opportunity costs such as time lost caring for other patients or length of shift, which influences the amount of time spent at work.23

Notably, speculation that hospitalists referred more complex cases to specialists was not borne out by studies examining referral patterns.21,24,25

Procedural Outcomes for Hospitalists vs Nonhospitalists

No convincing data exist that procedures performed by specialists have better outcomes than those completed at the bedside by well-trained generalists, although studies were limited to the inpatient setting, to generalists who have some exposure to procedures, and to internal medicine residents on inpatient rotations. In one retrospective review, interventional radiology (IR) referrals were associated with more platelet or plasma transfusions and intensive care unit transfers than those performed at the bedside by internal medicine residents, findings that remained significant after accounting for complexity (eg, Model for End-stage Liver Disease score, need for dialysis, and platelet count).24 Similarly, a prospective audit of 529 bedside procedures did not show any differences in complication rates between generalists and pulmonologists, once generalists underwent standardized training and used pleural safety checklists and ultrasound guidance.26 An administrative database review of 130,000 inpatient thoracenteses across several university hospitals between 2010 and 2013 found that the risk of iatrogenic pneumothorax was similar among operators from IR, medicine, and pulmonary (2.8%, 2.9%, and 3.1%, respectively)27; these findings have been reproduced in other studies.28 Finally, the increasing adoption of procedural ultrasound permits procedures to be conducted more safely at the bedside, without the need to refer to radiology for imaging guidance.3-5

IR procedures also are associated with increased healthcare costs compared with bedside procedures. One study showed that hospital costs for admissions when paracenteses were performed by radiologists were higher than those in which the procedure was completed at the bedside by gastroenterologists or hepatologists.25 A chart review examining 399 paracenteses, thoracenteses, and lumbar punctures found that the average procedure cost increased by 38% for referred procedures and 56% for radiology-performed procedures, as compared with bedside procedures.29 Needing ancillary staffing in dedicated suites to perform procedures contributed to the excess cost.9 Moreover, referred procedures resulted in increased length of stay, which can incur additional costs. However, the data were conflicting; two studies did not show a statistical difference,25,28 while others found an increased length of stay,24,27,29 which might be due to the unavailability of specialists during off hours, thereby delaying nonemergent procedures.21 Detailed cost analyses have controlled for the use of procedural facilities and blood transfusions among IR specialists and simulation training among generalists, showing that total costs were $663 per patient undergoing IR procedures compared with $134 per patient undergoing bedside procedures.30

Lack of Standardized Procedural Training or Assessment

A robust body of primary studies and systematic reviews supports the use of simulation for procedural training to improve comfort and skill as well as reduce complication rates and costs.31,32 A systematic review that investigated the impact of four paradigms of procedural training found that MPS and quality improvement/patient safety approaches led to the most active learning compared with apprenticeship (ie, “see one, do one”) and approaches based on educational theories.33 Nevertheless, the vast majority of the research has been conducted in trainees,32,34 with sparse evidence among practicing physicians. One cohort study of attending physicians’ central venous catheter insertion skills on simulators found low and variable short-term performance, showing overall poor adherence to checklists.35 One article suggested that hospitalists’ procedural skills were below established thresholds of competency at baseline and that simulation-based training did not result in sustained skills, but the small sample size and high attrition limited meaningful conclusions.36 Although continuing medical education courses are available to hospitalists, there is no published evidence supporting their effectiveness.

Proxies for procedural skill have included comfort and experience, yet these markers have broadly been shown to be inadequate.34,36,37 Additionally, the natural decline of skill over time has invoked the need for periodic reassessment of proficiency.36,38 Credentialing has been equally inconstant; a survey of the Society of Hospital Medicine’s (SHM) POCUS task force revealed that only half of respondents reported their hospitals required a minimum number of procedures for initial credentialing and recredentialing.39 In short, periodic assessment of procedural skills among hospitalists has not been a routine process at many institutions.

Role of Hospitalist-Run Medical Procedure Services

It might not be necessary for all hospitalists to be proficient and credentialed in a given procedure,1 and a trend has emerged in the creation of MPS staffed by hospitalists as proceduralists. The primary aim of these MPS has been to recapture the procedures—and associated revenue—that would otherwise be referred to specialists. Moreover, concentrating procedures among a core group of hospitalists endeavors to support patient safety through several principles: (1) to increase technical proficiency through higher procedural volumes, (2) to facilitate rigorous training and assessment among dedicated individuals, and (3) to systematize best practices of operator performance, communication, and documentation.

MPS have been implemented around the country and have demonstrated several advantages. In one institution, medical firms that were offered the use of an MPS had 48% more procedural attempts by nonspecialists, without significant differences in the proportions of successful attempts or complications compared with the firms who more often referred to specialists.40 A retrospective study analyzed outcomes of 1,707 bedside procedures, of which 548 were performed by an MPS, and found that procedures done by the MPS were more likely to result in lower rates of unsuccessful procedures and to use best-practice safety processes (ie, to involve attending physicians, to use ultrasound guidance, and to avoid femoral sites for catheterization).12 Satisfaction was high among patients who underwent bedside procedures performed by a hospitalist-supervised, intern-based procedure service with a focus on bedside communication.41 From a workforce perspective, MPS have also allowed surgical or radiological subspecialties to focus on more complex cases with higher reimbursement rates,18,42 for proceduralists to expand beyond core procedures (eg, bone marrow biopsies43), and to train advanced practice providers.44 Although studies have not shown that the outcomes of procedures completed by an MPS are better than the outcomes of procedures performed by other specialists,45 one can potentially extrapolate from earlier data that procedures done at the bedside by nonradiologists would have comparable outcomes.

DISCUSSION

A myriad of factors is influencing hospitalists’ scope of practice with respect to bedside procedures. Some evidence suggests that procedures performed by specialists are not superior to those done by generalists and might be associated with increased costs. The most promising developments in the past few decades include simulation-based training, which has demonstrated effectiveness across an array of clinical outcomes but has not been sufficiently evaluated in hospitalists to draw conclusions, and hospitalist-led MPS, which promote safe and productive procedural clinical practices. However, decreasing procedural volume, increasing referrals to specialists, dwindling hospitalist interest and/or confidence, time constraints, limited training opportunities, nonuniform credentialing policies, and lack of standardized assessment are cumulatively contributing to a loss of procedural competency among hospitalists.

Taken together, these forces should compel hospital medicine groups that expect their hospitalists to perform their own procedures to identify necessary steps for ensuring the safety of hospitalized patients under their care. The following considerations derive from the available—albeit modest—evidence on procedural performance in hospital medicine (Table).

Recommendations to Optimize Procedural Competency Among Hospitalists

1. Create MPS to establish a core set of hospitalists to perform procedures and train them using evidence-based practices. Creation of an MPS places the responsibility of core bedside procedures in the hands of a select group of proceduralists. This strategy streamlines training and assessment of individual procedural competency to meet standards set by SHM36,46 and improves educational outcomes.47-49 MPS could improve clinical outcomes,12,42,50-52 including length of stay and cost, while maintaining patient satisfaction,41 as well as recoup lost revenue from referrals by increasing the volume of procedures done by generalists,40,49 although no robust data supporting the latter point exists. Implementing an MPS requires full-time equivalent (FTE) support for proceduralists and administrative support for data collection and tracking complications. Furthermore, a well-functioning MPS will require investment in portable ultrasound machines and training in POCUS, which has been shown to decrease complications and increase success of invasive bedside procedures.3-7 Hospital medicine groups should be aware that staffing an MPS can divert hospitalist labor and resources from other needed clinical areas, especially during the initial, low-volume phases of implementation. Strategies to offset relative value unit (RVU) loss include combining the MPS with existing clinical roles such as medical consults, code triage, and rapid response teams; or with services with lower patient caps, which might work particularly well in community hospitals. In many institutions, hospitalists can bill for procedural consults in addition to the procedures when the consult involves nonmedical patients, which is relevant when the procedure ultimately cannot be performed (eg, too little ascites to safely perform a paracentesis). Further research should establish best practices of MPS to ensure maximum procedural productivity and safety, because there are no rigorous prospective studies that evaluate strategies to create this service. Such strategies include determining the optimal ratio of proceduralists to general hospitalists, hospital characteristics that benefit most from MPS (eg, referral centers, urban-based settings), volume and type of procedures performed, and the proportion and type of referrals that are most cost-effective.

2. Establish policies with procedural specialists to arrange coverage for off-hours procedures and delineate thresholds for procedures that specialists should perform. Expanding hospitalists’ capabilities in performing procedures should trigger reconsideration of the medical center’s approach to procedural safety. A goal would be to have hospital medicine groups work collaboratively with specialists and other disciplines (eg, surgery, emergency medicine, anesthesia, or radiology) to ensure 24-hour, 7-day a week coverage of urgent bedside procedures. The potential to decrease length of stay and improve off-hour procedural quality might be a compelling rationale for hospital administration, whether or not an MPS is used. That said, we recognize that other services might be unable or unwilling to provide such coverage and that specialist off-hour coverage would incur increased costs and could reduce exposure opportunities for internal medicine residents.

A hospital-level procedures committee might be required to support an institutional imperative for procedural safety and to oversee the implementation of approaches that are practical, financially sustainable, and equitable for all service lines, especially because hospitalist groups might bear the early costs of training and retraining.

3. Hospitalist–proceduralists should collaborate with internal medicine residency programs to offer intensive procedural training experiences to residents who want these skills to be part of their future practice. Robust procedural training for trainees promotes better outcomes for the current workforce and helps to populate the future workforce with procedurally competent practitioners. Simulation-based training is a well-established procedural instruction method that is safe, authentic, and effective in terms of clinical outcomes.34 As the primary teachers of residents in many institutions, hospitalists often are the ones who impart procedural skills to residents, despite uneven skill sets. It is in the interest of internal medicine residency program directors to advocate for a core group of hospitalist–proceduralists, as MPS offer an infrastructure for training that has been shown to increase procedural volume and improve skills.47,48,50 Program directors could therefore be incentivized to sponsor some of these procedural roles with teaching and administration funds, as a trade-off for securing higher-quality procedural training and closer supervision for their trainees. The dual necessity of teaching procedural skills to residents and attending physicians alike offers economies of scale for the use of facilities, personnel, and equipment, and gives faculty an opportunity to extend their clinical teaching skills into the domain of procedural supervision.

4. Hospital medicine groups should re-evaluate credentialing and privileging to ensure procedural competency. Given the lack of published data that characterizes how many hospital medicine groups credential hospitalists to perform procedures and what practices they use to assess competency, hospital medicine groups might be signing off on procedures without verifying hospitalists’ proficiency in core procedures. SHM’s position statement on credentialing for ultrasound-guided procedures46 describes standards that could be applied to other procedures. It proposes that credentialing processes should be grounded in simulation- and patient-based assessments of cognitive and psychomotor skills, using published checklists and global ratings for feedback. Simulation training could support provisional certification, but hospitalists should reach minimum thresholds of supervised patient-based experience before initial credentialing, with continuous reassessment of competency to mitigate skill decay. Prospectively tracking procedural metrics, such as procedural volume and complication rates, also will support systematic skill assessment. Finally, similar to any other medical error, near misses and complications should trigger periprocedural safety reviews.

Limitations

The modest body of research on hospitalists and procedures is the central limitation of our synthesis. Much of the literature consisted of consensus statements, retrospective studies, and small prospective educational studies. As a result, we did not adopt all strategies considered standard in a scoping or systematic review. The literature on MPS specifically was insufficient to draw conclusions about their operational and financial impact or effects on procedure quality. Our primary recommendation to implement MPS requires significant fiscal investment and infrastructure. It also entails risks that must be proactively addressed, including the potential for net financial loss and decreased educational opportunities for residents.

CONCLUSIONS

Hospitalists regularly face the predicament of being expected to independently perform procedures, with little access to training, minimal experience, and no ongoing assessment to ensure their proficiency or the safety of their patients. Past assumptions about hospitalists’ responsibility do not reflect realities in practice patterns and have not translated to widespread adoption of procedural training, monitoring, and assessment mechanisms. Our work summarizes a body of literature that, although limited in empiric studies of hospitalists themselves, offers insights with recommendations for hospital medicine groups wishing to uphold procedural skills as part of their providers’ professional identity.

References

1. Dressler DD, Pistoria MJ, Budnitz TL, McKean SCW, Amin AN. Core competencies in hospital medicine: Development and methodology. J Hosp Med. 2006;1(1):48-56. https://doi.org/10.1002/jhm.6
2. Wachter RM, Goldman L. Zero to 50,000 — The 20th anniversary of the hospitalist. N Engl J Med. 2016;375(11):1009-1011. https://doi.org/10.1056/NEJMp1607958
3. Cho J, Jensen TP, Reierson K, et al. Recommendations on the use of ultrasound guidance for adult abdominal paracentesis: a position statement of the Society of Hospital Medicine. J Hosp Med. 2019;14:E7-E15. https://doi.org/10.12788/jhm.3095
4. Soni NJ, Franco-Sadud R, Kobaidze K, et al. Recommendations on the use of ultrasound guidance for adult lumbar puncture: a position statement of the Society of Hospital Medicine. J Hosp Med. 2019;14(10):591-601. https://doi.org/10.12788/jhm.3197
5. Dancel R, Schnobrich D, Puri N, et al. Recommendations on the use of ultrasound guidance for adult thoracentesis: a position statement of the Society of Hospital Medicine. J Hosp Med. 2018;13(2):126-135. https://doi.org/10.12788/jhm.2940
6. Franco-Sadud R, Schnobrich D, Mathews BK, et al. Recommendations on the use of ultrasound guidance for central and peripheral vascular access in adults: a position statement of the Society of Hospital Medicine. J Hosp Med. 2019;14:E1-E22. https://doi.org/10.12788/jhm.3287
7. Soni NJ, Schnobrich D, Mathews BK, et al. Point-of-care ultrasound for hospitalists: a position statement of the Society of Hospital Medicine. J Hosp Med. 2019;14:E1-E6. https://doi.org/10.12788/jhm.3079
8. Thakkar R, Wright SM, Alguire P, Wigton RS, Boonyasai RT. Procedures performed by hospitalist and non-hospitalist general internists. J Gen Intern Med. 2010;25(5):448-452. https://doi.org/10.1007/s11606-010-1284-2
9. Lucas BP, Asbury JK, Franco-Sadud R. Training future hospitalists with simulators: a needed step toward accessible, expertly performed bedside procedures. J Hosp Med. 2009;4(7):395-396. https://doi.org/10.1002/jhm.602
10. American Board of Internal Medicine. Policies and procedures for certification. Accessed December 3, 2020. https://www.abim.org/~/media/ABIM%20Public/Files/pdf/publications/certification-guides/policies-and-procedures.pdf
11. Myers LC. Toward preventing medical malpractice claims related to chest procedures. Ann Am Thorac Soc. 2020;17(6):776-779. https://doi.org/10.1513/AnnalsATS.201912-863RL
12. Tukey MH, Wiener RS. The impact of a medical procedure service on patient safety, procedure quality and resident training opportunities. J Gen Intern Med. 2014;29(3):485-490. https://doi.org/10.1007/s11606-013-2709-5
13. Brennan TA, Leape LL, Laird NM, et al. Incidence of adverse events and negligence in hospitalized patients. N Engl J Med. 1991;324(6):370-376. https://doi.org/10.1056/NEJM199102073240604
14. Leape LL, Brennan TA, Laird N, et al. The nature of adverse events in hospitalized patients. N Engl J Med. 1991;324(6):377-384. https://doi.org/10.1056/NEJM199102073240605
15. Myers LC, Gartland RM, Skillings J, et al. An examination of medical malpractice claims involving physician trainees. Acad Med. 2020;95(8):1215-1222. https://doi.org/10.1097/ACM.0000000000003117
16. Mercaldi CJ, Lanes SF. Ultrasound guidance decreases complications and improves the cost of care among patients undergoing thoracentesis and paracentesis. Chest. 2013;143(2):532-538. https://doi.org/10.1378/chest.12-0447
17. Vaisman A, Cram P. Procedural competence among faculty in academic health centers: challenges and future directions. Acad Med. 2017;92(1):31-34. https://doi.org/10.1097/ACM.0000000000001327
18. Nelson B. Hospitalists try to reclaim lead role in bedside procedures. The Hospitalist. March 2015. Accessed June 27, 2020. https://www.the-hospitalist.org/hospitalist/article/122571/hospitalists-try-reclaim-lead-role-bedside-procedures
19. Wigton RS, Alguire P; American College of Physicians. The declining number and variety of procedures done by general internists: a resurvey of members of the American College of Physicians. Ann Intern Med. 2007;146(5):355-360. https://doi.org/10.7326/0003-4819-146-5-200703060-00007
20. Duszak R Jr, Chatterjee AR, Schneider DA. National fluid shifts: fifteen-year trends in paracentesis and thoracentesis procedures. J Am Coll Radiol. 2010;7(11):859-864. https://doi.org/10.1016/j.jacr.2010.04.013
21. Gottumukkala RV, Prabhakar AM, Hemingway J, Hughes DR, Duszak R Jr. Disparities over time in volume, day of the week, and patient complexity between paracentesis and thoracentesis procedures performed by radiologists versus those performed by nonradiologists. J Vasc Interv Radiol. 2019;30(11):1769-1778.e1. https://doi.org/10.1016/j.jvir.2019.04.015
22. Kroll H, Duszak R Jr, Nsiah E, Hughes DR, Sumer S, Wintermark M. Trends in lumbar puncture over 2 decades: a dramatic shift to radiology. Am J Roentgenol. 2014;204(1):15-19. https://doi.org/10.2214/AJR.14.12622
23. Jensen T, Lai A, Mourad M. Can lessons from systems-based mastery learning for thoracentesis be translated to hospitalists? J Hosp Med. 2016;11(11):811-812. https://doi.org/10.1002/jhm.2655
24. Barsuk JH, Cohen ER, Feinglass J, McGaghie WC, Wayne DB. Clinical outcomes after bedside and interventional radiology paracentesis procedures. Am J Med. 2013;126(4):349-356. https://doi.org/10.1016/j.amjmed.2012.09.016
25. Barsuk JH, Feinglass J, Kozmic SE, Hohmann SF, Ganger D, Wayne DB. Specialties performing paracentesis procedures at university hospitals: implications for training and certification. J Hosp Med. 2014;9(3):162-168. https://doi.org/10.1002/jhm.2153
26. See KC, Ong V, Teoh CM, et al. Bedside pleural procedures by pulmonologists and non-pulmonologists: a 3-year safety audit. Respirology. 2014;19(3):396-402. https://doi.org/10.1111/resp.12244
27. Kozmic SE, Wayne DB, Feinglass J, Hohmann SF, Barsuk JH. Factors associated with inpatient thoracentesis procedure quality at university hospitals. Jt Comm J Qual Patient Saf. 2016;42(1):34-40. https://doi.org/10.1016/S1553-7250(16)42004-0
28. Berger MS, Divilov V, Paredes H, Sun E. Abdominal paracentesis: safety and efficacy comparing medicine resident bedside paracentesis vs. paracentesis performed by interventional radiology. J Clin Gastroenterol Hepatol. 2018;2(4). https://doi.org/10.21767/2575-7733.1000050
29. Kay C, Wozniak EM, Szabo A, Jackson JL. Examining invasive bedside procedure performance at an academic medical center. South Med J. 2016;109(7):402-407. https://doi.org/10.14423/SMJ.0000000000000485
30. Barsuk JH, Cohen ER, Feinglass J, et al. Cost savings of performing paracentesis procedures at the bedside after simulation-based education. Simul Healthc. 2014;9(5):312-318. https://doi.org/10.1097/SIH.0000000000000040
31. Barsuk JH, Cohen ER, Williams MV, et al. Simulation-based mastery learning for thoracentesis skills improves patient outcomes: a randomized trial. Acad Med. 2018;93(5):729-735. https://doi.org/10.1097/ACM.0000000000001965
32. Huang GC, McSparron JI, Balk EM, et al. Procedural instruction in invasive bedside procedures: a systematic review and meta-analysis of effective teaching approaches. BMJ Qual Saf. 2016;25(4):281-294. https://doi.org/10.1136/bmjqs-2014-003518
33. Brydges R, Stroud L, Wong BM, Holmboe ES, Imrie K, Hatala R. Core competencies or a competent core? a scoping review and realist synthesis of invasive bedside procedural skills training in internal medicine. Acad Med. 2017;92(11):1632-1643. https://doi.org/10.1097/ACM.0000000000001726
34. Brydges R, Hatala R, Zendejas B, Erwin PJ, Cook DA. Linking simulation-based educational assessments and patient-related outcomes: a systematic review and meta-analysis. Acad Med. 2015;90(2):246-256. https://doi.org/10.1097/ACM.0000000000000549
35. Barsuk JH, Cohen ER, Nguyen D, et al. Attending physician adherence to a 29-component central venous catheter bundle checklist during simulated procedures. Crit Care Med. 2016;44(10):1871-1881. https://doi.org/10.1097/CCM.0000000000001831
36. Crocker JT, Hale CP, Vanka A, Ricotta DN, McSparron JI, Huang GC. Raising the bar for procedural competency among hospitalists. Ann Intern Med. 2019;170(9):654-655. https://doi.org/10.7326/M18-3007
37. Barsuk JH, Cohen ER, Feinglass J, McGaghie WC, Wayne DB. Residents’ procedural experience does not ensure competence: a research synthesis. J Grad Med Educ. 2017;9(2):201-208. https://doi.org/10.4300/JGME-D-16-00426.1
38. Sawyer T, White M, Zaveri P, et al. Learn, see, practice, prove, do, maintain: an evidence-based pedagogical framework for procedural skill training in medicine. Acad Med. 2015;90(8):1025-1033. https://doi.org/10.1097/ACM.0000000000000734
39. Jensen T, Soni N, Tierney D, Lucas B. Hospital privileging practices for bedside procedures: a survey of hospitalist experts. J Hosp Med. 2017;12(10):836-839. https://doi.org/10.12788/jhm.2837
40. Lucas BP, Asbury JK, Wang Y, et al. Impact of a bedside procedure service on general medicine inpatients: a firm-based trial. J Hosp Med. 2007;2(3):143-149. https://doi.org/10.1002/jhm.159
41. Mourad M, Auerbach AD, Maselli J, Sliwka D. Patient satisfaction with a hospitalist procedure service: Is bedside procedure teaching reassuring to patients? J Hosp Med. 2011;6(4):219-224. https://doi.org/10.1002/jhm.856
42. Ault MJ, Rosen BT. Proceduralists — leading patient-safety initiatives. N Engl J Med. 2007;356(17):1789-1790. https://doi.org/10.1056/NEJMc063239
43. Obasi JU, Umpierrez De Reguero AP. Safety profile of bone marrow aspiration and biopsies performed by the hospitalist procedure service at an academic center: an observational study. Blood. 2019;134(suppl 1): 5848. https://doi.org/10.1182/blood-2019-121444
44. Gisondi MA, Regan L, Branzetti J, Hopson LR. More learners, finite resources, and the changing landscape of procedural training at the bedside. Acad Med. 2018;93(5):699-704. https://doi.org/10.1097/ACM.0000000000002062
45. McCormack J. The new proceduralists: Have they found their niche? American Medical News. September 17, 2007. Accessed August 30, 2020. https://amednews.com/article/20070917/business/309179994/4/
46. Lucas BP, Tierney DM, Jensen TP, et al; Society of Hospital Medicine Point-of-Care Ultrasound Task Force. Credentialing of hospitalists in ultrasound-guided bedside procedures: a position statement of the Society of Hospital Medicine. J Hosp Med. 2018;13(2):117-125. https://doi.org/10.12788/jhm.2917
47. Lenhard A, Moallem M, Marrie RA, Becker J, Garland A. An intervention to improve procedure education for internal medicine residents. J Gen Intern Med. 2008;23(3):288-293. https://doi.org/10.1007/s11606-008-0513-4
48. Mourad M, Ranji S, Sliwka D. A randomized controlled trial of the impact of a teaching procedure service on the training of internal medicine residents. J Grad Med Educ. 2012;4(2):170-175. https://doi.org/10.4300/JGME-D-11-00136.1
49. Montuno A, Hunt BR, Lee MM. Potential impact of a bedside procedure service on training procedurally competent hospitalists in a community-based residency program. J Community Hosp Intern Med Perspect. 2016;6(3):31054. https://doi.org/10.3402/jchimp.v6.31054
50. Smith CC, Gordon CE, Feller‐Kopman D, et al. Creation of an innovative inpatient medical procedure service and a method to evaluate house staff competency. J Gen Intern Med. 2004;19(5p2):510-513. https://doi.org/10.1111/j.1525-1497.2004.30161.x
51. Mourad M. Capsule commentary on Tukey et al., the impact of a medical procedure service on patient safety, procedure quality and resident training opportunities. J Gen Intern Med. 2014;29(3):518. https://doi.org/10.1007/s11606-013-2740-6
52. Halm EA, Lee C, Chassin MR. Is volume related to outcome in health care: a systematic review and methodologic critique of the literature. 2002. Database of Abstracts of Reviews of Effects (DARE): Quality-assessed Reviews . Accessed June 26, 2020. https://www.ncbi.nlm.nih.gov/books/NBK69189/

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Related Articles

Over the past 20 years, hospitalists have served as the primary workforce for the clinical care of medical inpatients in the United States.1,2 Core competencies1 state that hospitalists should be able to perform the following bedside procedures: lumbar puncture, paracentesis, thoracentesis, arthrocentesis, and central venous catheter placement. More recently, standard of care has dictated that these procedures be performed under ultrasound guidance,3-6 and thus hospitalists are also expected to be adept at point-of-care ultrasound (POCUS).7

However, no current national standard exists for ensuring basic competency among hospitalists performing bedside procedures. In addition, hospitalists’ procedural volumes are declining,8,9 and standards for procedural training during internal medicine residency have been reduced.10 As a result, many residents who intend to become hospitalists are no longer prepared to perform these procedures.

The ramifications of the loss of procedural competency for hospitalists are manifold. Technical errors are a significant source of patient morbidity and mortality,11-15 and complications arising specifically from nonoperative procedures range from 0 to 19%,16 although these data do not distinguish technical errors from unpreventable adverse events nor the degree to which hospitalists contributed to these complications. Second, hospitalists in academic medical centers might be ill equipped to function as supervisors of trainees performing procedures, which could perpetuate a cycle of suboptimal technical skills.17 Finally, the discrepancy between consensus guidelines for hospitalists and their scope of practice represents a significant area of risk management for institutions that base their credentialing policies on published competencies.

There are many compelling reasons for why hospitalists should maintain—in fact reclaim—a primary role in bedside procedures.18 Hospitalists in community and rural settings might not have easy access to procedural specialists. In academic institutions, hospitalists are the primary instructors and supervisors of procedures performed by internal medicine residents. The increased availability of POCUS allows formally trained hospitalists to perform procedures more safely under imaging guidance.16

The literature on procedures performed by hospitalists, although limited, has focused on POCUS, systems innovations such as medical procedure services (MPS), and policy recommendations for procedural credentialing. Most studies on effective procedural instructional approaches have been conducted among trainees, who are procedural novices. This research does not sufficiently address the dilemma that hospitalists face as independent physicians for whom procedures are not a significant component of their practice, yet are expected to perform invasive procedures occasionally. The purpose of our literature review is to synthesize the available research to characterize contributors to hospitalists’ procedural competency. We conclude with considerations for hospital medicine practice.

METHODS

We performed a structured literature search for peer-reviewed articles related to hospitalists conducting procedures, being trained in procedures, or related to hospitalist-run MPS. We focused our search on the core hospitalist procedures with the highest potential morbidity (ie, lumbar puncture, abdominal paracentesis, thoracentesis, and central venous catheterization). We searched PubMed and Google Scholar for articles published since 1996 (when the term “hospitalists” was first coined) using keyword searches for [hospitalist OR hospital medicine] AND [procedur* OR medical procedur* OR medical procedure service] OR [(procedur* AND (train* OR educat* OR teach OR instruct*)] OR abdominal paracentes* OR thoracentes* OR lumbar puncture OR central venous catheter* OR ultrasound OR point-of-care. We included original research, brief research reports, perspectives, guidelines, and consensus statements. Exclusion criteria were articles that focused on nonhospitalists and conference abstracts. We used pearling to identify secondary sources from included articles’ bibliographies, without limits on year of publication.

RESULTS

Trends Towards Specialist Referrals

Between 1986 and 2007, the number and variety of procedures performed by internists decreased by half.19 Hospitalists still completed procedures in greater volume and variety than nonhospitalists,8 with approximately 50% of hospitalists performing lumbar punctures (50%), abdominal paracenteses (49%), and thoracenteses (44%) compared with less than 25% for all three procedures for nonhospitalists. Additionally, only 11% of surveyed hospitalists8 performed all nine core procedures, although these included procedures that are largely cognitive in nature (eg, electrocardiogram interpretation, chest X-ray interpretation) or procedures that have been relegated to other specialists (eg, endotracheal intubation, ventilator management, or joint injection/aspiration).

Surveys showed that, especially in larger cities and academic centers, procedural specialists have taken over a disproportionate share of procedures even as the number of procedures performed continued to rise.20 Between 1993 and 2008, the number of paracenteses and thoracenteses increased by 133% and decreased by 14%, respectively, but the share of procedures performed by radiologists increased by 964% and 358%, respectively, as evident in an analysis of Medicare billing data.20 A more recent study of Medicare claims from 2004 to 2016 similarly revealed that the percentage of paracenteses performed by radiologists compared with nonradiologists rose from 70% to 80% and thoracenteses from 47% to 66%, respectively.21 Comparable trends were apparent in claims data for lumbar punctures; between 1991 and 2011, the share of lumbar punctures performed by radiologists rose from 11% to 48%.22

In academic medical centers, hospitalists might have the opportunity to pursue other activities (eg, education, administration, research) as they progress in their careers, resulting in less clinical activity. Although hospitalists who are more clinically active in hospital care tended to perform more procedures,8 those with smaller clinical footprints reported lower levels of comfort with performing procedures8 and might have less available time to maintain procedural competency or train in new technologies such as POCUS.17

Additionally, hospitalists in both academic and community settings cited efficiency as a major reason for procedural referral. Hospitalists tended to perform more procedures if they had fixed salaries or if less than 50% of their income was based on clinical productivity, although this trend was not significant.8 Further, they also might be motivated by competing opportunity costs such as time lost caring for other patients or length of shift, which influences the amount of time spent at work.23

Notably, speculation that hospitalists referred more complex cases to specialists was not borne out by studies examining referral patterns.21,24,25

Procedural Outcomes for Hospitalists vs Nonhospitalists

No convincing data exist that procedures performed by specialists have better outcomes than those completed at the bedside by well-trained generalists, although studies were limited to the inpatient setting, to generalists who have some exposure to procedures, and to internal medicine residents on inpatient rotations. In one retrospective review, interventional radiology (IR) referrals were associated with more platelet or plasma transfusions and intensive care unit transfers than those performed at the bedside by internal medicine residents, findings that remained significant after accounting for complexity (eg, Model for End-stage Liver Disease score, need for dialysis, and platelet count).24 Similarly, a prospective audit of 529 bedside procedures did not show any differences in complication rates between generalists and pulmonologists, once generalists underwent standardized training and used pleural safety checklists and ultrasound guidance.26 An administrative database review of 130,000 inpatient thoracenteses across several university hospitals between 2010 and 2013 found that the risk of iatrogenic pneumothorax was similar among operators from IR, medicine, and pulmonary (2.8%, 2.9%, and 3.1%, respectively)27; these findings have been reproduced in other studies.28 Finally, the increasing adoption of procedural ultrasound permits procedures to be conducted more safely at the bedside, without the need to refer to radiology for imaging guidance.3-5

IR procedures also are associated with increased healthcare costs compared with bedside procedures. One study showed that hospital costs for admissions when paracenteses were performed by radiologists were higher than those in which the procedure was completed at the bedside by gastroenterologists or hepatologists.25 A chart review examining 399 paracenteses, thoracenteses, and lumbar punctures found that the average procedure cost increased by 38% for referred procedures and 56% for radiology-performed procedures, as compared with bedside procedures.29 Needing ancillary staffing in dedicated suites to perform procedures contributed to the excess cost.9 Moreover, referred procedures resulted in increased length of stay, which can incur additional costs. However, the data were conflicting; two studies did not show a statistical difference,25,28 while others found an increased length of stay,24,27,29 which might be due to the unavailability of specialists during off hours, thereby delaying nonemergent procedures.21 Detailed cost analyses have controlled for the use of procedural facilities and blood transfusions among IR specialists and simulation training among generalists, showing that total costs were $663 per patient undergoing IR procedures compared with $134 per patient undergoing bedside procedures.30

Lack of Standardized Procedural Training or Assessment

A robust body of primary studies and systematic reviews supports the use of simulation for procedural training to improve comfort and skill as well as reduce complication rates and costs.31,32 A systematic review that investigated the impact of four paradigms of procedural training found that MPS and quality improvement/patient safety approaches led to the most active learning compared with apprenticeship (ie, “see one, do one”) and approaches based on educational theories.33 Nevertheless, the vast majority of the research has been conducted in trainees,32,34 with sparse evidence among practicing physicians. One cohort study of attending physicians’ central venous catheter insertion skills on simulators found low and variable short-term performance, showing overall poor adherence to checklists.35 One article suggested that hospitalists’ procedural skills were below established thresholds of competency at baseline and that simulation-based training did not result in sustained skills, but the small sample size and high attrition limited meaningful conclusions.36 Although continuing medical education courses are available to hospitalists, there is no published evidence supporting their effectiveness.

Proxies for procedural skill have included comfort and experience, yet these markers have broadly been shown to be inadequate.34,36,37 Additionally, the natural decline of skill over time has invoked the need for periodic reassessment of proficiency.36,38 Credentialing has been equally inconstant; a survey of the Society of Hospital Medicine’s (SHM) POCUS task force revealed that only half of respondents reported their hospitals required a minimum number of procedures for initial credentialing and recredentialing.39 In short, periodic assessment of procedural skills among hospitalists has not been a routine process at many institutions.

Role of Hospitalist-Run Medical Procedure Services

It might not be necessary for all hospitalists to be proficient and credentialed in a given procedure,1 and a trend has emerged in the creation of MPS staffed by hospitalists as proceduralists. The primary aim of these MPS has been to recapture the procedures—and associated revenue—that would otherwise be referred to specialists. Moreover, concentrating procedures among a core group of hospitalists endeavors to support patient safety through several principles: (1) to increase technical proficiency through higher procedural volumes, (2) to facilitate rigorous training and assessment among dedicated individuals, and (3) to systematize best practices of operator performance, communication, and documentation.

MPS have been implemented around the country and have demonstrated several advantages. In one institution, medical firms that were offered the use of an MPS had 48% more procedural attempts by nonspecialists, without significant differences in the proportions of successful attempts or complications compared with the firms who more often referred to specialists.40 A retrospective study analyzed outcomes of 1,707 bedside procedures, of which 548 were performed by an MPS, and found that procedures done by the MPS were more likely to result in lower rates of unsuccessful procedures and to use best-practice safety processes (ie, to involve attending physicians, to use ultrasound guidance, and to avoid femoral sites for catheterization).12 Satisfaction was high among patients who underwent bedside procedures performed by a hospitalist-supervised, intern-based procedure service with a focus on bedside communication.41 From a workforce perspective, MPS have also allowed surgical or radiological subspecialties to focus on more complex cases with higher reimbursement rates,18,42 for proceduralists to expand beyond core procedures (eg, bone marrow biopsies43), and to train advanced practice providers.44 Although studies have not shown that the outcomes of procedures completed by an MPS are better than the outcomes of procedures performed by other specialists,45 one can potentially extrapolate from earlier data that procedures done at the bedside by nonradiologists would have comparable outcomes.

DISCUSSION

A myriad of factors is influencing hospitalists’ scope of practice with respect to bedside procedures. Some evidence suggests that procedures performed by specialists are not superior to those done by generalists and might be associated with increased costs. The most promising developments in the past few decades include simulation-based training, which has demonstrated effectiveness across an array of clinical outcomes but has not been sufficiently evaluated in hospitalists to draw conclusions, and hospitalist-led MPS, which promote safe and productive procedural clinical practices. However, decreasing procedural volume, increasing referrals to specialists, dwindling hospitalist interest and/or confidence, time constraints, limited training opportunities, nonuniform credentialing policies, and lack of standardized assessment are cumulatively contributing to a loss of procedural competency among hospitalists.

Taken together, these forces should compel hospital medicine groups that expect their hospitalists to perform their own procedures to identify necessary steps for ensuring the safety of hospitalized patients under their care. The following considerations derive from the available—albeit modest—evidence on procedural performance in hospital medicine (Table).

Recommendations to Optimize Procedural Competency Among Hospitalists

1. Create MPS to establish a core set of hospitalists to perform procedures and train them using evidence-based practices. Creation of an MPS places the responsibility of core bedside procedures in the hands of a select group of proceduralists. This strategy streamlines training and assessment of individual procedural competency to meet standards set by SHM36,46 and improves educational outcomes.47-49 MPS could improve clinical outcomes,12,42,50-52 including length of stay and cost, while maintaining patient satisfaction,41 as well as recoup lost revenue from referrals by increasing the volume of procedures done by generalists,40,49 although no robust data supporting the latter point exists. Implementing an MPS requires full-time equivalent (FTE) support for proceduralists and administrative support for data collection and tracking complications. Furthermore, a well-functioning MPS will require investment in portable ultrasound machines and training in POCUS, which has been shown to decrease complications and increase success of invasive bedside procedures.3-7 Hospital medicine groups should be aware that staffing an MPS can divert hospitalist labor and resources from other needed clinical areas, especially during the initial, low-volume phases of implementation. Strategies to offset relative value unit (RVU) loss include combining the MPS with existing clinical roles such as medical consults, code triage, and rapid response teams; or with services with lower patient caps, which might work particularly well in community hospitals. In many institutions, hospitalists can bill for procedural consults in addition to the procedures when the consult involves nonmedical patients, which is relevant when the procedure ultimately cannot be performed (eg, too little ascites to safely perform a paracentesis). Further research should establish best practices of MPS to ensure maximum procedural productivity and safety, because there are no rigorous prospective studies that evaluate strategies to create this service. Such strategies include determining the optimal ratio of proceduralists to general hospitalists, hospital characteristics that benefit most from MPS (eg, referral centers, urban-based settings), volume and type of procedures performed, and the proportion and type of referrals that are most cost-effective.

2. Establish policies with procedural specialists to arrange coverage for off-hours procedures and delineate thresholds for procedures that specialists should perform. Expanding hospitalists’ capabilities in performing procedures should trigger reconsideration of the medical center’s approach to procedural safety. A goal would be to have hospital medicine groups work collaboratively with specialists and other disciplines (eg, surgery, emergency medicine, anesthesia, or radiology) to ensure 24-hour, 7-day a week coverage of urgent bedside procedures. The potential to decrease length of stay and improve off-hour procedural quality might be a compelling rationale for hospital administration, whether or not an MPS is used. That said, we recognize that other services might be unable or unwilling to provide such coverage and that specialist off-hour coverage would incur increased costs and could reduce exposure opportunities for internal medicine residents.

A hospital-level procedures committee might be required to support an institutional imperative for procedural safety and to oversee the implementation of approaches that are practical, financially sustainable, and equitable for all service lines, especially because hospitalist groups might bear the early costs of training and retraining.

3. Hospitalist–proceduralists should collaborate with internal medicine residency programs to offer intensive procedural training experiences to residents who want these skills to be part of their future practice. Robust procedural training for trainees promotes better outcomes for the current workforce and helps to populate the future workforce with procedurally competent practitioners. Simulation-based training is a well-established procedural instruction method that is safe, authentic, and effective in terms of clinical outcomes.34 As the primary teachers of residents in many institutions, hospitalists often are the ones who impart procedural skills to residents, despite uneven skill sets. It is in the interest of internal medicine residency program directors to advocate for a core group of hospitalist–proceduralists, as MPS offer an infrastructure for training that has been shown to increase procedural volume and improve skills.47,48,50 Program directors could therefore be incentivized to sponsor some of these procedural roles with teaching and administration funds, as a trade-off for securing higher-quality procedural training and closer supervision for their trainees. The dual necessity of teaching procedural skills to residents and attending physicians alike offers economies of scale for the use of facilities, personnel, and equipment, and gives faculty an opportunity to extend their clinical teaching skills into the domain of procedural supervision.

4. Hospital medicine groups should re-evaluate credentialing and privileging to ensure procedural competency. Given the lack of published data that characterizes how many hospital medicine groups credential hospitalists to perform procedures and what practices they use to assess competency, hospital medicine groups might be signing off on procedures without verifying hospitalists’ proficiency in core procedures. SHM’s position statement on credentialing for ultrasound-guided procedures46 describes standards that could be applied to other procedures. It proposes that credentialing processes should be grounded in simulation- and patient-based assessments of cognitive and psychomotor skills, using published checklists and global ratings for feedback. Simulation training could support provisional certification, but hospitalists should reach minimum thresholds of supervised patient-based experience before initial credentialing, with continuous reassessment of competency to mitigate skill decay. Prospectively tracking procedural metrics, such as procedural volume and complication rates, also will support systematic skill assessment. Finally, similar to any other medical error, near misses and complications should trigger periprocedural safety reviews.

Limitations

The modest body of research on hospitalists and procedures is the central limitation of our synthesis. Much of the literature consisted of consensus statements, retrospective studies, and small prospective educational studies. As a result, we did not adopt all strategies considered standard in a scoping or systematic review. The literature on MPS specifically was insufficient to draw conclusions about their operational and financial impact or effects on procedure quality. Our primary recommendation to implement MPS requires significant fiscal investment and infrastructure. It also entails risks that must be proactively addressed, including the potential for net financial loss and decreased educational opportunities for residents.

CONCLUSIONS

Hospitalists regularly face the predicament of being expected to independently perform procedures, with little access to training, minimal experience, and no ongoing assessment to ensure their proficiency or the safety of their patients. Past assumptions about hospitalists’ responsibility do not reflect realities in practice patterns and have not translated to widespread adoption of procedural training, monitoring, and assessment mechanisms. Our work summarizes a body of literature that, although limited in empiric studies of hospitalists themselves, offers insights with recommendations for hospital medicine groups wishing to uphold procedural skills as part of their providers’ professional identity.

Over the past 20 years, hospitalists have served as the primary workforce for the clinical care of medical inpatients in the United States.1,2 Core competencies1 state that hospitalists should be able to perform the following bedside procedures: lumbar puncture, paracentesis, thoracentesis, arthrocentesis, and central venous catheter placement. More recently, standard of care has dictated that these procedures be performed under ultrasound guidance,3-6 and thus hospitalists are also expected to be adept at point-of-care ultrasound (POCUS).7

However, no current national standard exists for ensuring basic competency among hospitalists performing bedside procedures. In addition, hospitalists’ procedural volumes are declining,8,9 and standards for procedural training during internal medicine residency have been reduced.10 As a result, many residents who intend to become hospitalists are no longer prepared to perform these procedures.

The ramifications of the loss of procedural competency for hospitalists are manifold. Technical errors are a significant source of patient morbidity and mortality,11-15 and complications arising specifically from nonoperative procedures range from 0 to 19%,16 although these data do not distinguish technical errors from unpreventable adverse events nor the degree to which hospitalists contributed to these complications. Second, hospitalists in academic medical centers might be ill equipped to function as supervisors of trainees performing procedures, which could perpetuate a cycle of suboptimal technical skills.17 Finally, the discrepancy between consensus guidelines for hospitalists and their scope of practice represents a significant area of risk management for institutions that base their credentialing policies on published competencies.

There are many compelling reasons for why hospitalists should maintain—in fact reclaim—a primary role in bedside procedures.18 Hospitalists in community and rural settings might not have easy access to procedural specialists. In academic institutions, hospitalists are the primary instructors and supervisors of procedures performed by internal medicine residents. The increased availability of POCUS allows formally trained hospitalists to perform procedures more safely under imaging guidance.16

The literature on procedures performed by hospitalists, although limited, has focused on POCUS, systems innovations such as medical procedure services (MPS), and policy recommendations for procedural credentialing. Most studies on effective procedural instructional approaches have been conducted among trainees, who are procedural novices. This research does not sufficiently address the dilemma that hospitalists face as independent physicians for whom procedures are not a significant component of their practice, yet are expected to perform invasive procedures occasionally. The purpose of our literature review is to synthesize the available research to characterize contributors to hospitalists’ procedural competency. We conclude with considerations for hospital medicine practice.

METHODS

We performed a structured literature search for peer-reviewed articles related to hospitalists conducting procedures, being trained in procedures, or related to hospitalist-run MPS. We focused our search on the core hospitalist procedures with the highest potential morbidity (ie, lumbar puncture, abdominal paracentesis, thoracentesis, and central venous catheterization). We searched PubMed and Google Scholar for articles published since 1996 (when the term “hospitalists” was first coined) using keyword searches for [hospitalist OR hospital medicine] AND [procedur* OR medical procedur* OR medical procedure service] OR [(procedur* AND (train* OR educat* OR teach OR instruct*)] OR abdominal paracentes* OR thoracentes* OR lumbar puncture OR central venous catheter* OR ultrasound OR point-of-care. We included original research, brief research reports, perspectives, guidelines, and consensus statements. Exclusion criteria were articles that focused on nonhospitalists and conference abstracts. We used pearling to identify secondary sources from included articles’ bibliographies, without limits on year of publication.

RESULTS

Trends Towards Specialist Referrals

Between 1986 and 2007, the number and variety of procedures performed by internists decreased by half.19 Hospitalists still completed procedures in greater volume and variety than nonhospitalists,8 with approximately 50% of hospitalists performing lumbar punctures (50%), abdominal paracenteses (49%), and thoracenteses (44%) compared with less than 25% for all three procedures for nonhospitalists. Additionally, only 11% of surveyed hospitalists8 performed all nine core procedures, although these included procedures that are largely cognitive in nature (eg, electrocardiogram interpretation, chest X-ray interpretation) or procedures that have been relegated to other specialists (eg, endotracheal intubation, ventilator management, or joint injection/aspiration).

Surveys showed that, especially in larger cities and academic centers, procedural specialists have taken over a disproportionate share of procedures even as the number of procedures performed continued to rise.20 Between 1993 and 2008, the number of paracenteses and thoracenteses increased by 133% and decreased by 14%, respectively, but the share of procedures performed by radiologists increased by 964% and 358%, respectively, as evident in an analysis of Medicare billing data.20 A more recent study of Medicare claims from 2004 to 2016 similarly revealed that the percentage of paracenteses performed by radiologists compared with nonradiologists rose from 70% to 80% and thoracenteses from 47% to 66%, respectively.21 Comparable trends were apparent in claims data for lumbar punctures; between 1991 and 2011, the share of lumbar punctures performed by radiologists rose from 11% to 48%.22

In academic medical centers, hospitalists might have the opportunity to pursue other activities (eg, education, administration, research) as they progress in their careers, resulting in less clinical activity. Although hospitalists who are more clinically active in hospital care tended to perform more procedures,8 those with smaller clinical footprints reported lower levels of comfort with performing procedures8 and might have less available time to maintain procedural competency or train in new technologies such as POCUS.17

Additionally, hospitalists in both academic and community settings cited efficiency as a major reason for procedural referral. Hospitalists tended to perform more procedures if they had fixed salaries or if less than 50% of their income was based on clinical productivity, although this trend was not significant.8 Further, they also might be motivated by competing opportunity costs such as time lost caring for other patients or length of shift, which influences the amount of time spent at work.23

Notably, speculation that hospitalists referred more complex cases to specialists was not borne out by studies examining referral patterns.21,24,25

Procedural Outcomes for Hospitalists vs Nonhospitalists

No convincing data exist that procedures performed by specialists have better outcomes than those completed at the bedside by well-trained generalists, although studies were limited to the inpatient setting, to generalists who have some exposure to procedures, and to internal medicine residents on inpatient rotations. In one retrospective review, interventional radiology (IR) referrals were associated with more platelet or plasma transfusions and intensive care unit transfers than those performed at the bedside by internal medicine residents, findings that remained significant after accounting for complexity (eg, Model for End-stage Liver Disease score, need for dialysis, and platelet count).24 Similarly, a prospective audit of 529 bedside procedures did not show any differences in complication rates between generalists and pulmonologists, once generalists underwent standardized training and used pleural safety checklists and ultrasound guidance.26 An administrative database review of 130,000 inpatient thoracenteses across several university hospitals between 2010 and 2013 found that the risk of iatrogenic pneumothorax was similar among operators from IR, medicine, and pulmonary (2.8%, 2.9%, and 3.1%, respectively)27; these findings have been reproduced in other studies.28 Finally, the increasing adoption of procedural ultrasound permits procedures to be conducted more safely at the bedside, without the need to refer to radiology for imaging guidance.3-5

IR procedures also are associated with increased healthcare costs compared with bedside procedures. One study showed that hospital costs for admissions when paracenteses were performed by radiologists were higher than those in which the procedure was completed at the bedside by gastroenterologists or hepatologists.25 A chart review examining 399 paracenteses, thoracenteses, and lumbar punctures found that the average procedure cost increased by 38% for referred procedures and 56% for radiology-performed procedures, as compared with bedside procedures.29 Needing ancillary staffing in dedicated suites to perform procedures contributed to the excess cost.9 Moreover, referred procedures resulted in increased length of stay, which can incur additional costs. However, the data were conflicting; two studies did not show a statistical difference,25,28 while others found an increased length of stay,24,27,29 which might be due to the unavailability of specialists during off hours, thereby delaying nonemergent procedures.21 Detailed cost analyses have controlled for the use of procedural facilities and blood transfusions among IR specialists and simulation training among generalists, showing that total costs were $663 per patient undergoing IR procedures compared with $134 per patient undergoing bedside procedures.30

Lack of Standardized Procedural Training or Assessment

A robust body of primary studies and systematic reviews supports the use of simulation for procedural training to improve comfort and skill as well as reduce complication rates and costs.31,32 A systematic review that investigated the impact of four paradigms of procedural training found that MPS and quality improvement/patient safety approaches led to the most active learning compared with apprenticeship (ie, “see one, do one”) and approaches based on educational theories.33 Nevertheless, the vast majority of the research has been conducted in trainees,32,34 with sparse evidence among practicing physicians. One cohort study of attending physicians’ central venous catheter insertion skills on simulators found low and variable short-term performance, showing overall poor adherence to checklists.35 One article suggested that hospitalists’ procedural skills were below established thresholds of competency at baseline and that simulation-based training did not result in sustained skills, but the small sample size and high attrition limited meaningful conclusions.36 Although continuing medical education courses are available to hospitalists, there is no published evidence supporting their effectiveness.

Proxies for procedural skill have included comfort and experience, yet these markers have broadly been shown to be inadequate.34,36,37 Additionally, the natural decline of skill over time has invoked the need for periodic reassessment of proficiency.36,38 Credentialing has been equally inconstant; a survey of the Society of Hospital Medicine’s (SHM) POCUS task force revealed that only half of respondents reported their hospitals required a minimum number of procedures for initial credentialing and recredentialing.39 In short, periodic assessment of procedural skills among hospitalists has not been a routine process at many institutions.

Role of Hospitalist-Run Medical Procedure Services

It might not be necessary for all hospitalists to be proficient and credentialed in a given procedure,1 and a trend has emerged in the creation of MPS staffed by hospitalists as proceduralists. The primary aim of these MPS has been to recapture the procedures—and associated revenue—that would otherwise be referred to specialists. Moreover, concentrating procedures among a core group of hospitalists endeavors to support patient safety through several principles: (1) to increase technical proficiency through higher procedural volumes, (2) to facilitate rigorous training and assessment among dedicated individuals, and (3) to systematize best practices of operator performance, communication, and documentation.

MPS have been implemented around the country and have demonstrated several advantages. In one institution, medical firms that were offered the use of an MPS had 48% more procedural attempts by nonspecialists, without significant differences in the proportions of successful attempts or complications compared with the firms who more often referred to specialists.40 A retrospective study analyzed outcomes of 1,707 bedside procedures, of which 548 were performed by an MPS, and found that procedures done by the MPS were more likely to result in lower rates of unsuccessful procedures and to use best-practice safety processes (ie, to involve attending physicians, to use ultrasound guidance, and to avoid femoral sites for catheterization).12 Satisfaction was high among patients who underwent bedside procedures performed by a hospitalist-supervised, intern-based procedure service with a focus on bedside communication.41 From a workforce perspective, MPS have also allowed surgical or radiological subspecialties to focus on more complex cases with higher reimbursement rates,18,42 for proceduralists to expand beyond core procedures (eg, bone marrow biopsies43), and to train advanced practice providers.44 Although studies have not shown that the outcomes of procedures completed by an MPS are better than the outcomes of procedures performed by other specialists,45 one can potentially extrapolate from earlier data that procedures done at the bedside by nonradiologists would have comparable outcomes.

DISCUSSION

A myriad of factors is influencing hospitalists’ scope of practice with respect to bedside procedures. Some evidence suggests that procedures performed by specialists are not superior to those done by generalists and might be associated with increased costs. The most promising developments in the past few decades include simulation-based training, which has demonstrated effectiveness across an array of clinical outcomes but has not been sufficiently evaluated in hospitalists to draw conclusions, and hospitalist-led MPS, which promote safe and productive procedural clinical practices. However, decreasing procedural volume, increasing referrals to specialists, dwindling hospitalist interest and/or confidence, time constraints, limited training opportunities, nonuniform credentialing policies, and lack of standardized assessment are cumulatively contributing to a loss of procedural competency among hospitalists.

Taken together, these forces should compel hospital medicine groups that expect their hospitalists to perform their own procedures to identify necessary steps for ensuring the safety of hospitalized patients under their care. The following considerations derive from the available—albeit modest—evidence on procedural performance in hospital medicine (Table).

Recommendations to Optimize Procedural Competency Among Hospitalists

1. Create MPS to establish a core set of hospitalists to perform procedures and train them using evidence-based practices. Creation of an MPS places the responsibility of core bedside procedures in the hands of a select group of proceduralists. This strategy streamlines training and assessment of individual procedural competency to meet standards set by SHM36,46 and improves educational outcomes.47-49 MPS could improve clinical outcomes,12,42,50-52 including length of stay and cost, while maintaining patient satisfaction,41 as well as recoup lost revenue from referrals by increasing the volume of procedures done by generalists,40,49 although no robust data supporting the latter point exists. Implementing an MPS requires full-time equivalent (FTE) support for proceduralists and administrative support for data collection and tracking complications. Furthermore, a well-functioning MPS will require investment in portable ultrasound machines and training in POCUS, which has been shown to decrease complications and increase success of invasive bedside procedures.3-7 Hospital medicine groups should be aware that staffing an MPS can divert hospitalist labor and resources from other needed clinical areas, especially during the initial, low-volume phases of implementation. Strategies to offset relative value unit (RVU) loss include combining the MPS with existing clinical roles such as medical consults, code triage, and rapid response teams; or with services with lower patient caps, which might work particularly well in community hospitals. In many institutions, hospitalists can bill for procedural consults in addition to the procedures when the consult involves nonmedical patients, which is relevant when the procedure ultimately cannot be performed (eg, too little ascites to safely perform a paracentesis). Further research should establish best practices of MPS to ensure maximum procedural productivity and safety, because there are no rigorous prospective studies that evaluate strategies to create this service. Such strategies include determining the optimal ratio of proceduralists to general hospitalists, hospital characteristics that benefit most from MPS (eg, referral centers, urban-based settings), volume and type of procedures performed, and the proportion and type of referrals that are most cost-effective.

2. Establish policies with procedural specialists to arrange coverage for off-hours procedures and delineate thresholds for procedures that specialists should perform. Expanding hospitalists’ capabilities in performing procedures should trigger reconsideration of the medical center’s approach to procedural safety. A goal would be to have hospital medicine groups work collaboratively with specialists and other disciplines (eg, surgery, emergency medicine, anesthesia, or radiology) to ensure 24-hour, 7-day a week coverage of urgent bedside procedures. The potential to decrease length of stay and improve off-hour procedural quality might be a compelling rationale for hospital administration, whether or not an MPS is used. That said, we recognize that other services might be unable or unwilling to provide such coverage and that specialist off-hour coverage would incur increased costs and could reduce exposure opportunities for internal medicine residents.

A hospital-level procedures committee might be required to support an institutional imperative for procedural safety and to oversee the implementation of approaches that are practical, financially sustainable, and equitable for all service lines, especially because hospitalist groups might bear the early costs of training and retraining.

3. Hospitalist–proceduralists should collaborate with internal medicine residency programs to offer intensive procedural training experiences to residents who want these skills to be part of their future practice. Robust procedural training for trainees promotes better outcomes for the current workforce and helps to populate the future workforce with procedurally competent practitioners. Simulation-based training is a well-established procedural instruction method that is safe, authentic, and effective in terms of clinical outcomes.34 As the primary teachers of residents in many institutions, hospitalists often are the ones who impart procedural skills to residents, despite uneven skill sets. It is in the interest of internal medicine residency program directors to advocate for a core group of hospitalist–proceduralists, as MPS offer an infrastructure for training that has been shown to increase procedural volume and improve skills.47,48,50 Program directors could therefore be incentivized to sponsor some of these procedural roles with teaching and administration funds, as a trade-off for securing higher-quality procedural training and closer supervision for their trainees. The dual necessity of teaching procedural skills to residents and attending physicians alike offers economies of scale for the use of facilities, personnel, and equipment, and gives faculty an opportunity to extend their clinical teaching skills into the domain of procedural supervision.

4. Hospital medicine groups should re-evaluate credentialing and privileging to ensure procedural competency. Given the lack of published data that characterizes how many hospital medicine groups credential hospitalists to perform procedures and what practices they use to assess competency, hospital medicine groups might be signing off on procedures without verifying hospitalists’ proficiency in core procedures. SHM’s position statement on credentialing for ultrasound-guided procedures46 describes standards that could be applied to other procedures. It proposes that credentialing processes should be grounded in simulation- and patient-based assessments of cognitive and psychomotor skills, using published checklists and global ratings for feedback. Simulation training could support provisional certification, but hospitalists should reach minimum thresholds of supervised patient-based experience before initial credentialing, with continuous reassessment of competency to mitigate skill decay. Prospectively tracking procedural metrics, such as procedural volume and complication rates, also will support systematic skill assessment. Finally, similar to any other medical error, near misses and complications should trigger periprocedural safety reviews.

Limitations

The modest body of research on hospitalists and procedures is the central limitation of our synthesis. Much of the literature consisted of consensus statements, retrospective studies, and small prospective educational studies. As a result, we did not adopt all strategies considered standard in a scoping or systematic review. The literature on MPS specifically was insufficient to draw conclusions about their operational and financial impact or effects on procedure quality. Our primary recommendation to implement MPS requires significant fiscal investment and infrastructure. It also entails risks that must be proactively addressed, including the potential for net financial loss and decreased educational opportunities for residents.

CONCLUSIONS

Hospitalists regularly face the predicament of being expected to independently perform procedures, with little access to training, minimal experience, and no ongoing assessment to ensure their proficiency or the safety of their patients. Past assumptions about hospitalists’ responsibility do not reflect realities in practice patterns and have not translated to widespread adoption of procedural training, monitoring, and assessment mechanisms. Our work summarizes a body of literature that, although limited in empiric studies of hospitalists themselves, offers insights with recommendations for hospital medicine groups wishing to uphold procedural skills as part of their providers’ professional identity.

References

1. Dressler DD, Pistoria MJ, Budnitz TL, McKean SCW, Amin AN. Core competencies in hospital medicine: Development and methodology. J Hosp Med. 2006;1(1):48-56. https://doi.org/10.1002/jhm.6
2. Wachter RM, Goldman L. Zero to 50,000 — The 20th anniversary of the hospitalist. N Engl J Med. 2016;375(11):1009-1011. https://doi.org/10.1056/NEJMp1607958
3. Cho J, Jensen TP, Reierson K, et al. Recommendations on the use of ultrasound guidance for adult abdominal paracentesis: a position statement of the Society of Hospital Medicine. J Hosp Med. 2019;14:E7-E15. https://doi.org/10.12788/jhm.3095
4. Soni NJ, Franco-Sadud R, Kobaidze K, et al. Recommendations on the use of ultrasound guidance for adult lumbar puncture: a position statement of the Society of Hospital Medicine. J Hosp Med. 2019;14(10):591-601. https://doi.org/10.12788/jhm.3197
5. Dancel R, Schnobrich D, Puri N, et al. Recommendations on the use of ultrasound guidance for adult thoracentesis: a position statement of the Society of Hospital Medicine. J Hosp Med. 2018;13(2):126-135. https://doi.org/10.12788/jhm.2940
6. Franco-Sadud R, Schnobrich D, Mathews BK, et al. Recommendations on the use of ultrasound guidance for central and peripheral vascular access in adults: a position statement of the Society of Hospital Medicine. J Hosp Med. 2019;14:E1-E22. https://doi.org/10.12788/jhm.3287
7. Soni NJ, Schnobrich D, Mathews BK, et al. Point-of-care ultrasound for hospitalists: a position statement of the Society of Hospital Medicine. J Hosp Med. 2019;14:E1-E6. https://doi.org/10.12788/jhm.3079
8. Thakkar R, Wright SM, Alguire P, Wigton RS, Boonyasai RT. Procedures performed by hospitalist and non-hospitalist general internists. J Gen Intern Med. 2010;25(5):448-452. https://doi.org/10.1007/s11606-010-1284-2
9. Lucas BP, Asbury JK, Franco-Sadud R. Training future hospitalists with simulators: a needed step toward accessible, expertly performed bedside procedures. J Hosp Med. 2009;4(7):395-396. https://doi.org/10.1002/jhm.602
10. American Board of Internal Medicine. Policies and procedures for certification. Accessed December 3, 2020. https://www.abim.org/~/media/ABIM%20Public/Files/pdf/publications/certification-guides/policies-and-procedures.pdf
11. Myers LC. Toward preventing medical malpractice claims related to chest procedures. Ann Am Thorac Soc. 2020;17(6):776-779. https://doi.org/10.1513/AnnalsATS.201912-863RL
12. Tukey MH, Wiener RS. The impact of a medical procedure service on patient safety, procedure quality and resident training opportunities. J Gen Intern Med. 2014;29(3):485-490. https://doi.org/10.1007/s11606-013-2709-5
13. Brennan TA, Leape LL, Laird NM, et al. Incidence of adverse events and negligence in hospitalized patients. N Engl J Med. 1991;324(6):370-376. https://doi.org/10.1056/NEJM199102073240604
14. Leape LL, Brennan TA, Laird N, et al. The nature of adverse events in hospitalized patients. N Engl J Med. 1991;324(6):377-384. https://doi.org/10.1056/NEJM199102073240605
15. Myers LC, Gartland RM, Skillings J, et al. An examination of medical malpractice claims involving physician trainees. Acad Med. 2020;95(8):1215-1222. https://doi.org/10.1097/ACM.0000000000003117
16. Mercaldi CJ, Lanes SF. Ultrasound guidance decreases complications and improves the cost of care among patients undergoing thoracentesis and paracentesis. Chest. 2013;143(2):532-538. https://doi.org/10.1378/chest.12-0447
17. Vaisman A, Cram P. Procedural competence among faculty in academic health centers: challenges and future directions. Acad Med. 2017;92(1):31-34. https://doi.org/10.1097/ACM.0000000000001327
18. Nelson B. Hospitalists try to reclaim lead role in bedside procedures. The Hospitalist. March 2015. Accessed June 27, 2020. https://www.the-hospitalist.org/hospitalist/article/122571/hospitalists-try-reclaim-lead-role-bedside-procedures
19. Wigton RS, Alguire P; American College of Physicians. The declining number and variety of procedures done by general internists: a resurvey of members of the American College of Physicians. Ann Intern Med. 2007;146(5):355-360. https://doi.org/10.7326/0003-4819-146-5-200703060-00007
20. Duszak R Jr, Chatterjee AR, Schneider DA. National fluid shifts: fifteen-year trends in paracentesis and thoracentesis procedures. J Am Coll Radiol. 2010;7(11):859-864. https://doi.org/10.1016/j.jacr.2010.04.013
21. Gottumukkala RV, Prabhakar AM, Hemingway J, Hughes DR, Duszak R Jr. Disparities over time in volume, day of the week, and patient complexity between paracentesis and thoracentesis procedures performed by radiologists versus those performed by nonradiologists. J Vasc Interv Radiol. 2019;30(11):1769-1778.e1. https://doi.org/10.1016/j.jvir.2019.04.015
22. Kroll H, Duszak R Jr, Nsiah E, Hughes DR, Sumer S, Wintermark M. Trends in lumbar puncture over 2 decades: a dramatic shift to radiology. Am J Roentgenol. 2014;204(1):15-19. https://doi.org/10.2214/AJR.14.12622
23. Jensen T, Lai A, Mourad M. Can lessons from systems-based mastery learning for thoracentesis be translated to hospitalists? J Hosp Med. 2016;11(11):811-812. https://doi.org/10.1002/jhm.2655
24. Barsuk JH, Cohen ER, Feinglass J, McGaghie WC, Wayne DB. Clinical outcomes after bedside and interventional radiology paracentesis procedures. Am J Med. 2013;126(4):349-356. https://doi.org/10.1016/j.amjmed.2012.09.016
25. Barsuk JH, Feinglass J, Kozmic SE, Hohmann SF, Ganger D, Wayne DB. Specialties performing paracentesis procedures at university hospitals: implications for training and certification. J Hosp Med. 2014;9(3):162-168. https://doi.org/10.1002/jhm.2153
26. See KC, Ong V, Teoh CM, et al. Bedside pleural procedures by pulmonologists and non-pulmonologists: a 3-year safety audit. Respirology. 2014;19(3):396-402. https://doi.org/10.1111/resp.12244
27. Kozmic SE, Wayne DB, Feinglass J, Hohmann SF, Barsuk JH. Factors associated with inpatient thoracentesis procedure quality at university hospitals. Jt Comm J Qual Patient Saf. 2016;42(1):34-40. https://doi.org/10.1016/S1553-7250(16)42004-0
28. Berger MS, Divilov V, Paredes H, Sun E. Abdominal paracentesis: safety and efficacy comparing medicine resident bedside paracentesis vs. paracentesis performed by interventional radiology. J Clin Gastroenterol Hepatol. 2018;2(4). https://doi.org/10.21767/2575-7733.1000050
29. Kay C, Wozniak EM, Szabo A, Jackson JL. Examining invasive bedside procedure performance at an academic medical center. South Med J. 2016;109(7):402-407. https://doi.org/10.14423/SMJ.0000000000000485
30. Barsuk JH, Cohen ER, Feinglass J, et al. Cost savings of performing paracentesis procedures at the bedside after simulation-based education. Simul Healthc. 2014;9(5):312-318. https://doi.org/10.1097/SIH.0000000000000040
31. Barsuk JH, Cohen ER, Williams MV, et al. Simulation-based mastery learning for thoracentesis skills improves patient outcomes: a randomized trial. Acad Med. 2018;93(5):729-735. https://doi.org/10.1097/ACM.0000000000001965
32. Huang GC, McSparron JI, Balk EM, et al. Procedural instruction in invasive bedside procedures: a systematic review and meta-analysis of effective teaching approaches. BMJ Qual Saf. 2016;25(4):281-294. https://doi.org/10.1136/bmjqs-2014-003518
33. Brydges R, Stroud L, Wong BM, Holmboe ES, Imrie K, Hatala R. Core competencies or a competent core? a scoping review and realist synthesis of invasive bedside procedural skills training in internal medicine. Acad Med. 2017;92(11):1632-1643. https://doi.org/10.1097/ACM.0000000000001726
34. Brydges R, Hatala R, Zendejas B, Erwin PJ, Cook DA. Linking simulation-based educational assessments and patient-related outcomes: a systematic review and meta-analysis. Acad Med. 2015;90(2):246-256. https://doi.org/10.1097/ACM.0000000000000549
35. Barsuk JH, Cohen ER, Nguyen D, et al. Attending physician adherence to a 29-component central venous catheter bundle checklist during simulated procedures. Crit Care Med. 2016;44(10):1871-1881. https://doi.org/10.1097/CCM.0000000000001831
36. Crocker JT, Hale CP, Vanka A, Ricotta DN, McSparron JI, Huang GC. Raising the bar for procedural competency among hospitalists. Ann Intern Med. 2019;170(9):654-655. https://doi.org/10.7326/M18-3007
37. Barsuk JH, Cohen ER, Feinglass J, McGaghie WC, Wayne DB. Residents’ procedural experience does not ensure competence: a research synthesis. J Grad Med Educ. 2017;9(2):201-208. https://doi.org/10.4300/JGME-D-16-00426.1
38. Sawyer T, White M, Zaveri P, et al. Learn, see, practice, prove, do, maintain: an evidence-based pedagogical framework for procedural skill training in medicine. Acad Med. 2015;90(8):1025-1033. https://doi.org/10.1097/ACM.0000000000000734
39. Jensen T, Soni N, Tierney D, Lucas B. Hospital privileging practices for bedside procedures: a survey of hospitalist experts. J Hosp Med. 2017;12(10):836-839. https://doi.org/10.12788/jhm.2837
40. Lucas BP, Asbury JK, Wang Y, et al. Impact of a bedside procedure service on general medicine inpatients: a firm-based trial. J Hosp Med. 2007;2(3):143-149. https://doi.org/10.1002/jhm.159
41. Mourad M, Auerbach AD, Maselli J, Sliwka D. Patient satisfaction with a hospitalist procedure service: Is bedside procedure teaching reassuring to patients? J Hosp Med. 2011;6(4):219-224. https://doi.org/10.1002/jhm.856
42. Ault MJ, Rosen BT. Proceduralists — leading patient-safety initiatives. N Engl J Med. 2007;356(17):1789-1790. https://doi.org/10.1056/NEJMc063239
43. Obasi JU, Umpierrez De Reguero AP. Safety profile of bone marrow aspiration and biopsies performed by the hospitalist procedure service at an academic center: an observational study. Blood. 2019;134(suppl 1): 5848. https://doi.org/10.1182/blood-2019-121444
44. Gisondi MA, Regan L, Branzetti J, Hopson LR. More learners, finite resources, and the changing landscape of procedural training at the bedside. Acad Med. 2018;93(5):699-704. https://doi.org/10.1097/ACM.0000000000002062
45. McCormack J. The new proceduralists: Have they found their niche? American Medical News. September 17, 2007. Accessed August 30, 2020. https://amednews.com/article/20070917/business/309179994/4/
46. Lucas BP, Tierney DM, Jensen TP, et al; Society of Hospital Medicine Point-of-Care Ultrasound Task Force. Credentialing of hospitalists in ultrasound-guided bedside procedures: a position statement of the Society of Hospital Medicine. J Hosp Med. 2018;13(2):117-125. https://doi.org/10.12788/jhm.2917
47. Lenhard A, Moallem M, Marrie RA, Becker J, Garland A. An intervention to improve procedure education for internal medicine residents. J Gen Intern Med. 2008;23(3):288-293. https://doi.org/10.1007/s11606-008-0513-4
48. Mourad M, Ranji S, Sliwka D. A randomized controlled trial of the impact of a teaching procedure service on the training of internal medicine residents. J Grad Med Educ. 2012;4(2):170-175. https://doi.org/10.4300/JGME-D-11-00136.1
49. Montuno A, Hunt BR, Lee MM. Potential impact of a bedside procedure service on training procedurally competent hospitalists in a community-based residency program. J Community Hosp Intern Med Perspect. 2016;6(3):31054. https://doi.org/10.3402/jchimp.v6.31054
50. Smith CC, Gordon CE, Feller‐Kopman D, et al. Creation of an innovative inpatient medical procedure service and a method to evaluate house staff competency. J Gen Intern Med. 2004;19(5p2):510-513. https://doi.org/10.1111/j.1525-1497.2004.30161.x
51. Mourad M. Capsule commentary on Tukey et al., the impact of a medical procedure service on patient safety, procedure quality and resident training opportunities. J Gen Intern Med. 2014;29(3):518. https://doi.org/10.1007/s11606-013-2740-6
52. Halm EA, Lee C, Chassin MR. Is volume related to outcome in health care: a systematic review and methodologic critique of the literature. 2002. Database of Abstracts of Reviews of Effects (DARE): Quality-assessed Reviews . Accessed June 26, 2020. https://www.ncbi.nlm.nih.gov/books/NBK69189/

References

1. Dressler DD, Pistoria MJ, Budnitz TL, McKean SCW, Amin AN. Core competencies in hospital medicine: Development and methodology. J Hosp Med. 2006;1(1):48-56. https://doi.org/10.1002/jhm.6
2. Wachter RM, Goldman L. Zero to 50,000 — The 20th anniversary of the hospitalist. N Engl J Med. 2016;375(11):1009-1011. https://doi.org/10.1056/NEJMp1607958
3. Cho J, Jensen TP, Reierson K, et al. Recommendations on the use of ultrasound guidance for adult abdominal paracentesis: a position statement of the Society of Hospital Medicine. J Hosp Med. 2019;14:E7-E15. https://doi.org/10.12788/jhm.3095
4. Soni NJ, Franco-Sadud R, Kobaidze K, et al. Recommendations on the use of ultrasound guidance for adult lumbar puncture: a position statement of the Society of Hospital Medicine. J Hosp Med. 2019;14(10):591-601. https://doi.org/10.12788/jhm.3197
5. Dancel R, Schnobrich D, Puri N, et al. Recommendations on the use of ultrasound guidance for adult thoracentesis: a position statement of the Society of Hospital Medicine. J Hosp Med. 2018;13(2):126-135. https://doi.org/10.12788/jhm.2940
6. Franco-Sadud R, Schnobrich D, Mathews BK, et al. Recommendations on the use of ultrasound guidance for central and peripheral vascular access in adults: a position statement of the Society of Hospital Medicine. J Hosp Med. 2019;14:E1-E22. https://doi.org/10.12788/jhm.3287
7. Soni NJ, Schnobrich D, Mathews BK, et al. Point-of-care ultrasound for hospitalists: a position statement of the Society of Hospital Medicine. J Hosp Med. 2019;14:E1-E6. https://doi.org/10.12788/jhm.3079
8. Thakkar R, Wright SM, Alguire P, Wigton RS, Boonyasai RT. Procedures performed by hospitalist and non-hospitalist general internists. J Gen Intern Med. 2010;25(5):448-452. https://doi.org/10.1007/s11606-010-1284-2
9. Lucas BP, Asbury JK, Franco-Sadud R. Training future hospitalists with simulators: a needed step toward accessible, expertly performed bedside procedures. J Hosp Med. 2009;4(7):395-396. https://doi.org/10.1002/jhm.602
10. American Board of Internal Medicine. Policies and procedures for certification. Accessed December 3, 2020. https://www.abim.org/~/media/ABIM%20Public/Files/pdf/publications/certification-guides/policies-and-procedures.pdf
11. Myers LC. Toward preventing medical malpractice claims related to chest procedures. Ann Am Thorac Soc. 2020;17(6):776-779. https://doi.org/10.1513/AnnalsATS.201912-863RL
12. Tukey MH, Wiener RS. The impact of a medical procedure service on patient safety, procedure quality and resident training opportunities. J Gen Intern Med. 2014;29(3):485-490. https://doi.org/10.1007/s11606-013-2709-5
13. Brennan TA, Leape LL, Laird NM, et al. Incidence of adverse events and negligence in hospitalized patients. N Engl J Med. 1991;324(6):370-376. https://doi.org/10.1056/NEJM199102073240604
14. Leape LL, Brennan TA, Laird N, et al. The nature of adverse events in hospitalized patients. N Engl J Med. 1991;324(6):377-384. https://doi.org/10.1056/NEJM199102073240605
15. Myers LC, Gartland RM, Skillings J, et al. An examination of medical malpractice claims involving physician trainees. Acad Med. 2020;95(8):1215-1222. https://doi.org/10.1097/ACM.0000000000003117
16. Mercaldi CJ, Lanes SF. Ultrasound guidance decreases complications and improves the cost of care among patients undergoing thoracentesis and paracentesis. Chest. 2013;143(2):532-538. https://doi.org/10.1378/chest.12-0447
17. Vaisman A, Cram P. Procedural competence among faculty in academic health centers: challenges and future directions. Acad Med. 2017;92(1):31-34. https://doi.org/10.1097/ACM.0000000000001327
18. Nelson B. Hospitalists try to reclaim lead role in bedside procedures. The Hospitalist. March 2015. Accessed June 27, 2020. https://www.the-hospitalist.org/hospitalist/article/122571/hospitalists-try-reclaim-lead-role-bedside-procedures
19. Wigton RS, Alguire P; American College of Physicians. The declining number and variety of procedures done by general internists: a resurvey of members of the American College of Physicians. Ann Intern Med. 2007;146(5):355-360. https://doi.org/10.7326/0003-4819-146-5-200703060-00007
20. Duszak R Jr, Chatterjee AR, Schneider DA. National fluid shifts: fifteen-year trends in paracentesis and thoracentesis procedures. J Am Coll Radiol. 2010;7(11):859-864. https://doi.org/10.1016/j.jacr.2010.04.013
21. Gottumukkala RV, Prabhakar AM, Hemingway J, Hughes DR, Duszak R Jr. Disparities over time in volume, day of the week, and patient complexity between paracentesis and thoracentesis procedures performed by radiologists versus those performed by nonradiologists. J Vasc Interv Radiol. 2019;30(11):1769-1778.e1. https://doi.org/10.1016/j.jvir.2019.04.015
22. Kroll H, Duszak R Jr, Nsiah E, Hughes DR, Sumer S, Wintermark M. Trends in lumbar puncture over 2 decades: a dramatic shift to radiology. Am J Roentgenol. 2014;204(1):15-19. https://doi.org/10.2214/AJR.14.12622
23. Jensen T, Lai A, Mourad M. Can lessons from systems-based mastery learning for thoracentesis be translated to hospitalists? J Hosp Med. 2016;11(11):811-812. https://doi.org/10.1002/jhm.2655
24. Barsuk JH, Cohen ER, Feinglass J, McGaghie WC, Wayne DB. Clinical outcomes after bedside and interventional radiology paracentesis procedures. Am J Med. 2013;126(4):349-356. https://doi.org/10.1016/j.amjmed.2012.09.016
25. Barsuk JH, Feinglass J, Kozmic SE, Hohmann SF, Ganger D, Wayne DB. Specialties performing paracentesis procedures at university hospitals: implications for training and certification. J Hosp Med. 2014;9(3):162-168. https://doi.org/10.1002/jhm.2153
26. See KC, Ong V, Teoh CM, et al. Bedside pleural procedures by pulmonologists and non-pulmonologists: a 3-year safety audit. Respirology. 2014;19(3):396-402. https://doi.org/10.1111/resp.12244
27. Kozmic SE, Wayne DB, Feinglass J, Hohmann SF, Barsuk JH. Factors associated with inpatient thoracentesis procedure quality at university hospitals. Jt Comm J Qual Patient Saf. 2016;42(1):34-40. https://doi.org/10.1016/S1553-7250(16)42004-0
28. Berger MS, Divilov V, Paredes H, Sun E. Abdominal paracentesis: safety and efficacy comparing medicine resident bedside paracentesis vs. paracentesis performed by interventional radiology. J Clin Gastroenterol Hepatol. 2018;2(4). https://doi.org/10.21767/2575-7733.1000050
29. Kay C, Wozniak EM, Szabo A, Jackson JL. Examining invasive bedside procedure performance at an academic medical center. South Med J. 2016;109(7):402-407. https://doi.org/10.14423/SMJ.0000000000000485
30. Barsuk JH, Cohen ER, Feinglass J, et al. Cost savings of performing paracentesis procedures at the bedside after simulation-based education. Simul Healthc. 2014;9(5):312-318. https://doi.org/10.1097/SIH.0000000000000040
31. Barsuk JH, Cohen ER, Williams MV, et al. Simulation-based mastery learning for thoracentesis skills improves patient outcomes: a randomized trial. Acad Med. 2018;93(5):729-735. https://doi.org/10.1097/ACM.0000000000001965
32. Huang GC, McSparron JI, Balk EM, et al. Procedural instruction in invasive bedside procedures: a systematic review and meta-analysis of effective teaching approaches. BMJ Qual Saf. 2016;25(4):281-294. https://doi.org/10.1136/bmjqs-2014-003518
33. Brydges R, Stroud L, Wong BM, Holmboe ES, Imrie K, Hatala R. Core competencies or a competent core? a scoping review and realist synthesis of invasive bedside procedural skills training in internal medicine. Acad Med. 2017;92(11):1632-1643. https://doi.org/10.1097/ACM.0000000000001726
34. Brydges R, Hatala R, Zendejas B, Erwin PJ, Cook DA. Linking simulation-based educational assessments and patient-related outcomes: a systematic review and meta-analysis. Acad Med. 2015;90(2):246-256. https://doi.org/10.1097/ACM.0000000000000549
35. Barsuk JH, Cohen ER, Nguyen D, et al. Attending physician adherence to a 29-component central venous catheter bundle checklist during simulated procedures. Crit Care Med. 2016;44(10):1871-1881. https://doi.org/10.1097/CCM.0000000000001831
36. Crocker JT, Hale CP, Vanka A, Ricotta DN, McSparron JI, Huang GC. Raising the bar for procedural competency among hospitalists. Ann Intern Med. 2019;170(9):654-655. https://doi.org/10.7326/M18-3007
37. Barsuk JH, Cohen ER, Feinglass J, McGaghie WC, Wayne DB. Residents’ procedural experience does not ensure competence: a research synthesis. J Grad Med Educ. 2017;9(2):201-208. https://doi.org/10.4300/JGME-D-16-00426.1
38. Sawyer T, White M, Zaveri P, et al. Learn, see, practice, prove, do, maintain: an evidence-based pedagogical framework for procedural skill training in medicine. Acad Med. 2015;90(8):1025-1033. https://doi.org/10.1097/ACM.0000000000000734
39. Jensen T, Soni N, Tierney D, Lucas B. Hospital privileging practices for bedside procedures: a survey of hospitalist experts. J Hosp Med. 2017;12(10):836-839. https://doi.org/10.12788/jhm.2837
40. Lucas BP, Asbury JK, Wang Y, et al. Impact of a bedside procedure service on general medicine inpatients: a firm-based trial. J Hosp Med. 2007;2(3):143-149. https://doi.org/10.1002/jhm.159
41. Mourad M, Auerbach AD, Maselli J, Sliwka D. Patient satisfaction with a hospitalist procedure service: Is bedside procedure teaching reassuring to patients? J Hosp Med. 2011;6(4):219-224. https://doi.org/10.1002/jhm.856
42. Ault MJ, Rosen BT. Proceduralists — leading patient-safety initiatives. N Engl J Med. 2007;356(17):1789-1790. https://doi.org/10.1056/NEJMc063239
43. Obasi JU, Umpierrez De Reguero AP. Safety profile of bone marrow aspiration and biopsies performed by the hospitalist procedure service at an academic center: an observational study. Blood. 2019;134(suppl 1): 5848. https://doi.org/10.1182/blood-2019-121444
44. Gisondi MA, Regan L, Branzetti J, Hopson LR. More learners, finite resources, and the changing landscape of procedural training at the bedside. Acad Med. 2018;93(5):699-704. https://doi.org/10.1097/ACM.0000000000002062
45. McCormack J. The new proceduralists: Have they found their niche? American Medical News. September 17, 2007. Accessed August 30, 2020. https://amednews.com/article/20070917/business/309179994/4/
46. Lucas BP, Tierney DM, Jensen TP, et al; Society of Hospital Medicine Point-of-Care Ultrasound Task Force. Credentialing of hospitalists in ultrasound-guided bedside procedures: a position statement of the Society of Hospital Medicine. J Hosp Med. 2018;13(2):117-125. https://doi.org/10.12788/jhm.2917
47. Lenhard A, Moallem M, Marrie RA, Becker J, Garland A. An intervention to improve procedure education for internal medicine residents. J Gen Intern Med. 2008;23(3):288-293. https://doi.org/10.1007/s11606-008-0513-4
48. Mourad M, Ranji S, Sliwka D. A randomized controlled trial of the impact of a teaching procedure service on the training of internal medicine residents. J Grad Med Educ. 2012;4(2):170-175. https://doi.org/10.4300/JGME-D-11-00136.1
49. Montuno A, Hunt BR, Lee MM. Potential impact of a bedside procedure service on training procedurally competent hospitalists in a community-based residency program. J Community Hosp Intern Med Perspect. 2016;6(3):31054. https://doi.org/10.3402/jchimp.v6.31054
50. Smith CC, Gordon CE, Feller‐Kopman D, et al. Creation of an innovative inpatient medical procedure service and a method to evaluate house staff competency. J Gen Intern Med. 2004;19(5p2):510-513. https://doi.org/10.1111/j.1525-1497.2004.30161.x
51. Mourad M. Capsule commentary on Tukey et al., the impact of a medical procedure service on patient safety, procedure quality and resident training opportunities. J Gen Intern Med. 2014;29(3):518. https://doi.org/10.1007/s11606-013-2740-6
52. Halm EA, Lee C, Chassin MR. Is volume related to outcome in health care: a systematic review and methodologic critique of the literature. 2002. Database of Abstracts of Reviews of Effects (DARE): Quality-assessed Reviews . Accessed June 26, 2020. https://www.ncbi.nlm.nih.gov/books/NBK69189/

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Things We Do for No Reason™: Ova and Parasite Testing in Patients With Acute Diarrhea Arising During Hospitalization

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Things We Do for No Reason™: Ova and Parasite Testing in Patients With Acute Diarrhea Arising During Hospitalization

Inspired by the ABIM Foundation’s Choosing Wisely® campaign, the “Things We Do for No Reason” (TWDFNR) series reviews practices that have become common parts of hospital care but may provide little value to our patients. Practices reviewed in the TWDFNR series do not represent clear-cut conclusions or clinical practice standards but are meant as a starting place for research and active discussions among hospitalists and patients. We invite you to be part of that discussion.

CLINICAL SCENARIO

A 54-year-old immunocompetent man admitted to the hospital for non–ST-segment elevation myocardial infarction develops profuse watery diarrhea after his third day of admission. He denies prior episodes of diarrhea. He does not have any fevers, blood in the stool, recent travel, or antibiotic use. Vital signs include a blood pressure of 128/82 mm Hg, heart rate of 120 beats per minute, respiratory rate of 16 breaths per min, oxygen saturation of 100% on room air, and temperature of 36.9 °C. His physical examination is normal, without signs of abdominal tenderness, rebound, or guarding. Complete blood count is normal, without eosinophilia. The comprehensive metabolic panel shows mild hypokalemia of 3.3 mmol/L. The hospitalist resuscitates him with normal saline, provides oral potassium repletion, and orders a stool culture, Clostridioides difficile test, and an ova and parasite (O&P) test. Loperamide and time resolve his symptoms in 2 days. Results of his stool culture, C difficile, and O&P tests return negative in 3 days.

BACKGROUND

Acute diarrhea is a common complaint in both inpatient and outpatient settings. It is defined as the passage of three or more liquid or poorly formed stools in a 24-hour period lasting less than 14 days. Persistent diarrhea lasts from 14 to 29 days, while chronic diarrhea lasts longer than 30 days. There are 47.8 million cases of acute diarrhea per year in the United States, costing $150 million in US health expenditures.1 Viral pathogens remain the most common cause of acute diarrhea in the United States.1,2 Standard O&P testing consists of applying a stool sample to a slide with either saline or iodine (wet mount) and evaluating the specimen with a microscope.

WHY YOU MIGHT THINK O&P TESTING IS HELPFUL

Giardia and Cryptosporidium remain the most commonly implicated parasitic pathogens in acute diarrheal episodes in the United States.3 Cryptosporidium cases in the United States range from 2.2 to 3.9 per 100,000 persons,4 and Giardia cases in the United States range from 5.8 to 6.4 per 100,000 persons.5 To avoid missing potentially treatable causes, providers often order O&P tests reflexively as part of a standard workup for acute diarrhea. From 2001 to 2007, Associated Regional and University Pathologists Laboratories experienced a 379% increase in O&P testing.6 Many providers ordering these tests assume that standard O&P testing covers most, if not all, parasites and that a negative test will rule out a parasitic cause of disease. Furthermore, providers are unaware that more sensitive tests to detect certain parasites have replaced standard O&P microscopy.3

WHY O&P TESTING IS USUALLY UNNECESSARY

Most hospitalized patients do not have a parasitic infection

In a review of 5,681 completed O&P tests from a tertiary care medical center in Canada over a 5-year period, only 1.4% of tests were positive.7 In a 3-year retrospective analysis of stool samples obtained after 3 days of hospitalization, positive results were found in only 1 of 191 stool cultures and in 0 of 90 O&P samples.8 Current practice guidelines suggest not testing patients with stool studies in cases of acute diarrhea lasting less than 7 days in the absence of significant risk factors for parasitic disease because it has been shown to be a rare event and most cases will self-resolve with supportive care only.1,9

The stool O&P test has low sensitivity

Classically ordered stool O&P tests have low sensitivity for the detection of Giardia and Cryptosporidium, the two most common parasites in the United States.6,10,11 O&P studies detect Giardia in only 66% to 79% of specimen samples and Cryptosporidium in less than 5% of specimens. Diagnostic yields can be improved with the use of special stains such as modified acid-fast stain (MAF).6 Despite use of MAF staining, though, sensitivity for Cryptosporidium detection has remained at only 55%.12 Additionally, several studies have shown that physicians are generally unaware of the test characteristics of stool O&P tests and they do not know to order the newer more sensitive enzyme immunoassays (EIA) or direct fluorescent antibody (DFA) tests even in situations when testing for a parasitic infection is appropriate.10,11,13,14 As stated earlier, a parasitic infection without significant risk factors is a rare event. A negative test with low or moderate sensitivity is not additive to such a low clinical suspicion because it does not significantly change posttest probability.

Testing can have adverse consequences

In addition to the low yield, O&P testing is technically complex, is time intensive, and requires an experienced technician’s interpretation. Inappropriate testing increases the cost of care and staff workload without much benefit.6 As such, some institutions have opted to send the O&P tests to labs with experienced technicians. Other institutions have adopted a restrictive stool O&P testing approach that reduces healthcare time and costs and improves the rate of positive tests.13,15 A study at a single tertiary care medical center demonstrated an estimated cost savings of $21,931 annually by implementing a computer-based algorithm to restrict testing for stool cultures and O&P tests to patients with higher probabilities of infection.15 The algorithm directed clinicians to provide further information when attempting to order stool culture, O&P, or other specific stool tests. For patients hospitalized for more than 3 days, the system did not allow certain testing. For patients with worrisome features like severe symptoms or an immunocompromised state, the algorithm directed the clinician to place an infectious disease or gastroenterology consult rather than order stool tests. Decreased laboratory costs of all stool studies (including O&P) in adult inpatient locations led to the cost savings. Additionally, the study authors felt that they likely underestimated the cost savings because they did not account for other expenses in the analysis, such as nursing workload and supplies.15

WHAT YOU SHOULD DO INSTEAD

Clinicians should evaluate patients on a case-by-case basis and determine the need to test based on the presence of high-risk features (Table).

High-Risk Features Warranting Further Stool Testing
Perform O&P testing only in patients with a high pretest probability of having a parasitic disease that will not resolve on its own.1,16 For example, if a patient recently returned from South America with acute diarrhea, EIA testing should be performed for Entamoeba histolytica. If you order O&P tests, you should order at least three spaced over 10 days to increase sensitivity. The yield with one test is 50% to 60%, but with three tests, it is >95%.17 Additionally, it is important to send a fresh stool sample that has not been contaminated with water or urine, both of which may lead to false positives. Most cases of acute diarrheal illnesses, however, do not require O&P evaluation and resolve with supportive treatment alone.

When performing parasitic testing in patients without a recent travel history but with other high-risk features, test for the most prevalent parasites in the United States (ie, Giardia, Cryptosporidium, and Entamoeba histolytica) with DFA or EIA tests.3 DFA testing for Giardia is 99% sensitive.12 In patients with symptoms lasting more than 7 days and recent travel, in addition to the above DFA/EIA tests, perform O&P testing with wet mount, modified acid-fast bacilli stain to detect rare parasites such as helminths, Strongyloides, Cyclospora, and Cystoisospora.3 In patients who live or travel to endemic areas (about 10% of traveler’s diarrhea is caused by parasitic infections), have unexplained eosinophilia, or are part of a community outbreak (eg, childcare institutions or drinking water/food outbreaks), test for Giardia, Cryptosporidium, Cyclospora, Cystoisospora, Entamoeba histolytica, and Isospora belli.9 In addition, among patients with AIDS or immunosuppression, testing should include assays for Microsporidia, Strongyloides, and Mycobacterium avium complex (Figure).9,16 Newer tests, such as the multiplex real-time polymerase chain reaction assay, can also simultaneously detect Entamoeba histolytica, Giardia lamblia, and Cryptosporidium parvum. For more information on parasitic testing, we suggest reading the review article “Beyond O&P times three.”3 It is important to familiarize yourself with the parasitic tests available at your respective clinics/hospital so the optimal test can be used.

Flow Chart for Parasite Testing

RECOMMENDATIONS

  • Prescribe a trial of “wait and see” for patients without high-risk features for parasitic disease.
  • Test patients with high-risk features for parasitic disease by utilizing targeted testing.
  • For patients with high-risk features but no travel history, first perform DFA, EIA, or multiplex real-time polymerase chain reaction testing to evaluate for Giardia, Cryptosporidium, and Entamoeba histolytica.
  • If DFA/EIA testing is negative, obtain O&P tests with and without stains, such as acid-fast bacilli, for detection of other rare parasites.

CONCLUSION

Hospitalists should risk-stratify patients to determine when O&P testing is appropriate. Employ more targeted testing, especially use of DFA/EIA tests when evaluating for parasites. Avoid parasitic testing if symptoms have lasted less than 7 days and the patient has no other high-risk features. Become familiar with the tests available at your institution and their sensitivities. As in our clinical scenario, most acute cases of diarrhea resolve without intervention and should be managed and treated conservatively.

Do you think this is a low-value practice? Is this truly a “Thing We Do for No Reason”? Share what you do in your practice and join in the conversation online by retweeting it on Twitter (#TWDFNR) and liking it on Facebook. We invite you to propose ideas for other “Things We Do for No Reason ” topics by emailing TWDFNR@hospitalmedicine.org .

Acknowledgments

The authors thank Dr Lenny Feldman for his assistance with editing the manuscript.

References

1. Riddle MS, DuPont HL, Connor BA. ACG clinical guideline: diagnosis, treatment, and prevention of acute diarrheal infections in adults. Am J Gastroenterol. 2016;111(5):602-622. https://doi.org/10.1038/ajg.2016.126
2. DuPont HL. Acute infectious diarrhea in immunocompetent adults. N Engl J Med. 2014;370(16):1532-1540. https://doi.org/10.1056/nejmra1301069
3. Mohapatra S, Singh DP, Alcid D, Pitchumoni CS. Beyond O&P times three. Am J Gastroenterol. 2018;113(6):805-818. https://doi.org/10.1038/s41395-018-0083-y
4. Painter JE, Hlavsa MC, Collier SA, Xiao L, Yoder JS. Cryptosporidiosis surveillance -- United States, 2011-2012. MMWR Suppl. 2015;64(3):1-14.
5. Painter JE, Gargano JW, Collier SA, Yoder JS. Giardiasis surveillance -- United States, 2011-2012. MMWR Suppl. 2015;64(3):15-25.
6. Polage CR, Stoddard GJ, Rolfs RT, Petti CA. Physician use of parasite tests in the United States from 1997 to 2006 and in a Utah Cryptosporidium outbreak in 2007. J Clin Microbiol. 2011;49(2):591-596. https://doi.org/10.1128/jcm.01806-10
7. Mosli M, Gregor J, Chande N, Lannigan R. Nonutility of routine testing of stool for ova and parasites in a tertiary care Canadian centre. Can J Microbiol. 2012;58(5):653-659. https://doi.org/10.1139/w2012-039
8. Siegel DL, Edelstein PH, Nachamkin I. Inappropriate testing for diarrheal diseases in the hospital. JAMA. 1990;263(7):979-982.
9. Shane AL, Mody RK, Crump JA, et al. 2017 Infectious Diseases Society of America clinical practice guidelines for the diagnosis and management of infectious diarrhea. Clin Infect Dis. 2017;65(12):e45-e80. https://doi.org/10.1093/cid/cix669
10. Hennessy TW, Marcus R, Deneen V, et al. Survey of physician diagnostic practices for patients with acute diarrhea: clinical and public health implications. Clin Infect Dis. 2004;38 (Suppl 3):S203-S211. https://doi.org/10.1086/381588
11. Morin CA, Roberts CL, Mshar PA, Addiss DG, Hadler JL. What do physicians know about cryptosporidiosis? a survey of Connecticut physicians. Arch Intern Med. 1997;157(9):1017-1022.
12. McHardy IH, Wu M, Shimizu-Cohen R, Couturier MR, Humphries RM. Detection of intestinal protozoa in the clinical laboratory. J Clin Microbiol. 2014;52(3):712-720. https://doi.org/10.1128/jcm.02877-13
13. Valenstein P, Pfaller M, Yungbluth M. The use and abuse of routine stool microbiology: a College of American Pathologists Q-probes study of 601 institutions. Arch Pathol Lab Med. 1996;120(2):206-211.
14. Jones JL, Lopez A, Wahlquist SP, Nadle J, Wilson M; Emerging Infections Program FoodNet Working Group. Survey of clinical laboratory practices for parasitic diseases. Clin Infect Dis. 2004;38(Suppl 3):S198-S202. https://doi.org/10.1086/381587
15. Tewell CE, Talbot TR, Nelson GE, et al. Reducing inappropriate testing for the evaluation of diarrhea among hospitalized patients. Am J Med. 2018;131(2):193-199.e1. https://doi.org/10.1016/j.amjmed.2017.10.006
16. Thielman NM, Guerrant RL. Clinical practice. acute infectious diarrhea. N Engl J Med. 2004;350(1):38-47. https://doi.org/10.1056/nejmcp031534
17. Marti H, Koella JC. Multiple stool examinations for ova and parasites and rate of false-negative results. J Clin Microbiol. 1993;31(11):3044-3045. https://doi.org/10.1128/jcm.31.11.3044-3045.1993

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1Division of Gastroenterology and Hepatology, Maimonides Medical Center, Brooklyn, New York; 2Division of Infectious Diseases, Montefiore Hospital and Medical Center, Bronx, New York; 3Division of Hospital Medicine, Mount Sinai Beth Israel, New York, New York; 4Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, New York.

Disclosures

The authors have nothing to disclose.

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1Division of Gastroenterology and Hepatology, Maimonides Medical Center, Brooklyn, New York; 2Division of Infectious Diseases, Montefiore Hospital and Medical Center, Bronx, New York; 3Division of Hospital Medicine, Mount Sinai Beth Israel, New York, New York; 4Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, New York.

Disclosures

The authors have nothing to disclose.

Author and Disclosure Information

1Division of Gastroenterology and Hepatology, Maimonides Medical Center, Brooklyn, New York; 2Division of Infectious Diseases, Montefiore Hospital and Medical Center, Bronx, New York; 3Division of Hospital Medicine, Mount Sinai Beth Israel, New York, New York; 4Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, New York.

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Related Articles

Inspired by the ABIM Foundation’s Choosing Wisely® campaign, the “Things We Do for No Reason” (TWDFNR) series reviews practices that have become common parts of hospital care but may provide little value to our patients. Practices reviewed in the TWDFNR series do not represent clear-cut conclusions or clinical practice standards but are meant as a starting place for research and active discussions among hospitalists and patients. We invite you to be part of that discussion.

CLINICAL SCENARIO

A 54-year-old immunocompetent man admitted to the hospital for non–ST-segment elevation myocardial infarction develops profuse watery diarrhea after his third day of admission. He denies prior episodes of diarrhea. He does not have any fevers, blood in the stool, recent travel, or antibiotic use. Vital signs include a blood pressure of 128/82 mm Hg, heart rate of 120 beats per minute, respiratory rate of 16 breaths per min, oxygen saturation of 100% on room air, and temperature of 36.9 °C. His physical examination is normal, without signs of abdominal tenderness, rebound, or guarding. Complete blood count is normal, without eosinophilia. The comprehensive metabolic panel shows mild hypokalemia of 3.3 mmol/L. The hospitalist resuscitates him with normal saline, provides oral potassium repletion, and orders a stool culture, Clostridioides difficile test, and an ova and parasite (O&P) test. Loperamide and time resolve his symptoms in 2 days. Results of his stool culture, C difficile, and O&P tests return negative in 3 days.

BACKGROUND

Acute diarrhea is a common complaint in both inpatient and outpatient settings. It is defined as the passage of three or more liquid or poorly formed stools in a 24-hour period lasting less than 14 days. Persistent diarrhea lasts from 14 to 29 days, while chronic diarrhea lasts longer than 30 days. There are 47.8 million cases of acute diarrhea per year in the United States, costing $150 million in US health expenditures.1 Viral pathogens remain the most common cause of acute diarrhea in the United States.1,2 Standard O&P testing consists of applying a stool sample to a slide with either saline or iodine (wet mount) and evaluating the specimen with a microscope.

WHY YOU MIGHT THINK O&P TESTING IS HELPFUL

Giardia and Cryptosporidium remain the most commonly implicated parasitic pathogens in acute diarrheal episodes in the United States.3 Cryptosporidium cases in the United States range from 2.2 to 3.9 per 100,000 persons,4 and Giardia cases in the United States range from 5.8 to 6.4 per 100,000 persons.5 To avoid missing potentially treatable causes, providers often order O&P tests reflexively as part of a standard workup for acute diarrhea. From 2001 to 2007, Associated Regional and University Pathologists Laboratories experienced a 379% increase in O&P testing.6 Many providers ordering these tests assume that standard O&P testing covers most, if not all, parasites and that a negative test will rule out a parasitic cause of disease. Furthermore, providers are unaware that more sensitive tests to detect certain parasites have replaced standard O&P microscopy.3

WHY O&P TESTING IS USUALLY UNNECESSARY

Most hospitalized patients do not have a parasitic infection

In a review of 5,681 completed O&P tests from a tertiary care medical center in Canada over a 5-year period, only 1.4% of tests were positive.7 In a 3-year retrospective analysis of stool samples obtained after 3 days of hospitalization, positive results were found in only 1 of 191 stool cultures and in 0 of 90 O&P samples.8 Current practice guidelines suggest not testing patients with stool studies in cases of acute diarrhea lasting less than 7 days in the absence of significant risk factors for parasitic disease because it has been shown to be a rare event and most cases will self-resolve with supportive care only.1,9

The stool O&P test has low sensitivity

Classically ordered stool O&P tests have low sensitivity for the detection of Giardia and Cryptosporidium, the two most common parasites in the United States.6,10,11 O&P studies detect Giardia in only 66% to 79% of specimen samples and Cryptosporidium in less than 5% of specimens. Diagnostic yields can be improved with the use of special stains such as modified acid-fast stain (MAF).6 Despite use of MAF staining, though, sensitivity for Cryptosporidium detection has remained at only 55%.12 Additionally, several studies have shown that physicians are generally unaware of the test characteristics of stool O&P tests and they do not know to order the newer more sensitive enzyme immunoassays (EIA) or direct fluorescent antibody (DFA) tests even in situations when testing for a parasitic infection is appropriate.10,11,13,14 As stated earlier, a parasitic infection without significant risk factors is a rare event. A negative test with low or moderate sensitivity is not additive to such a low clinical suspicion because it does not significantly change posttest probability.

Testing can have adverse consequences

In addition to the low yield, O&P testing is technically complex, is time intensive, and requires an experienced technician’s interpretation. Inappropriate testing increases the cost of care and staff workload without much benefit.6 As such, some institutions have opted to send the O&P tests to labs with experienced technicians. Other institutions have adopted a restrictive stool O&P testing approach that reduces healthcare time and costs and improves the rate of positive tests.13,15 A study at a single tertiary care medical center demonstrated an estimated cost savings of $21,931 annually by implementing a computer-based algorithm to restrict testing for stool cultures and O&P tests to patients with higher probabilities of infection.15 The algorithm directed clinicians to provide further information when attempting to order stool culture, O&P, or other specific stool tests. For patients hospitalized for more than 3 days, the system did not allow certain testing. For patients with worrisome features like severe symptoms or an immunocompromised state, the algorithm directed the clinician to place an infectious disease or gastroenterology consult rather than order stool tests. Decreased laboratory costs of all stool studies (including O&P) in adult inpatient locations led to the cost savings. Additionally, the study authors felt that they likely underestimated the cost savings because they did not account for other expenses in the analysis, such as nursing workload and supplies.15

WHAT YOU SHOULD DO INSTEAD

Clinicians should evaluate patients on a case-by-case basis and determine the need to test based on the presence of high-risk features (Table).

High-Risk Features Warranting Further Stool Testing
Perform O&P testing only in patients with a high pretest probability of having a parasitic disease that will not resolve on its own.1,16 For example, if a patient recently returned from South America with acute diarrhea, EIA testing should be performed for Entamoeba histolytica. If you order O&P tests, you should order at least three spaced over 10 days to increase sensitivity. The yield with one test is 50% to 60%, but with three tests, it is >95%.17 Additionally, it is important to send a fresh stool sample that has not been contaminated with water or urine, both of which may lead to false positives. Most cases of acute diarrheal illnesses, however, do not require O&P evaluation and resolve with supportive treatment alone.

When performing parasitic testing in patients without a recent travel history but with other high-risk features, test for the most prevalent parasites in the United States (ie, Giardia, Cryptosporidium, and Entamoeba histolytica) with DFA or EIA tests.3 DFA testing for Giardia is 99% sensitive.12 In patients with symptoms lasting more than 7 days and recent travel, in addition to the above DFA/EIA tests, perform O&P testing with wet mount, modified acid-fast bacilli stain to detect rare parasites such as helminths, Strongyloides, Cyclospora, and Cystoisospora.3 In patients who live or travel to endemic areas (about 10% of traveler’s diarrhea is caused by parasitic infections), have unexplained eosinophilia, or are part of a community outbreak (eg, childcare institutions or drinking water/food outbreaks), test for Giardia, Cryptosporidium, Cyclospora, Cystoisospora, Entamoeba histolytica, and Isospora belli.9 In addition, among patients with AIDS or immunosuppression, testing should include assays for Microsporidia, Strongyloides, and Mycobacterium avium complex (Figure).9,16 Newer tests, such as the multiplex real-time polymerase chain reaction assay, can also simultaneously detect Entamoeba histolytica, Giardia lamblia, and Cryptosporidium parvum. For more information on parasitic testing, we suggest reading the review article “Beyond O&P times three.”3 It is important to familiarize yourself with the parasitic tests available at your respective clinics/hospital so the optimal test can be used.

Flow Chart for Parasite Testing

RECOMMENDATIONS

  • Prescribe a trial of “wait and see” for patients without high-risk features for parasitic disease.
  • Test patients with high-risk features for parasitic disease by utilizing targeted testing.
  • For patients with high-risk features but no travel history, first perform DFA, EIA, or multiplex real-time polymerase chain reaction testing to evaluate for Giardia, Cryptosporidium, and Entamoeba histolytica.
  • If DFA/EIA testing is negative, obtain O&P tests with and without stains, such as acid-fast bacilli, for detection of other rare parasites.

CONCLUSION

Hospitalists should risk-stratify patients to determine when O&P testing is appropriate. Employ more targeted testing, especially use of DFA/EIA tests when evaluating for parasites. Avoid parasitic testing if symptoms have lasted less than 7 days and the patient has no other high-risk features. Become familiar with the tests available at your institution and their sensitivities. As in our clinical scenario, most acute cases of diarrhea resolve without intervention and should be managed and treated conservatively.

Do you think this is a low-value practice? Is this truly a “Thing We Do for No Reason”? Share what you do in your practice and join in the conversation online by retweeting it on Twitter (#TWDFNR) and liking it on Facebook. We invite you to propose ideas for other “Things We Do for No Reason ” topics by emailing TWDFNR@hospitalmedicine.org .

Acknowledgments

The authors thank Dr Lenny Feldman for his assistance with editing the manuscript.

Inspired by the ABIM Foundation’s Choosing Wisely® campaign, the “Things We Do for No Reason” (TWDFNR) series reviews practices that have become common parts of hospital care but may provide little value to our patients. Practices reviewed in the TWDFNR series do not represent clear-cut conclusions or clinical practice standards but are meant as a starting place for research and active discussions among hospitalists and patients. We invite you to be part of that discussion.

CLINICAL SCENARIO

A 54-year-old immunocompetent man admitted to the hospital for non–ST-segment elevation myocardial infarction develops profuse watery diarrhea after his third day of admission. He denies prior episodes of diarrhea. He does not have any fevers, blood in the stool, recent travel, or antibiotic use. Vital signs include a blood pressure of 128/82 mm Hg, heart rate of 120 beats per minute, respiratory rate of 16 breaths per min, oxygen saturation of 100% on room air, and temperature of 36.9 °C. His physical examination is normal, without signs of abdominal tenderness, rebound, or guarding. Complete blood count is normal, without eosinophilia. The comprehensive metabolic panel shows mild hypokalemia of 3.3 mmol/L. The hospitalist resuscitates him with normal saline, provides oral potassium repletion, and orders a stool culture, Clostridioides difficile test, and an ova and parasite (O&P) test. Loperamide and time resolve his symptoms in 2 days. Results of his stool culture, C difficile, and O&P tests return negative in 3 days.

BACKGROUND

Acute diarrhea is a common complaint in both inpatient and outpatient settings. It is defined as the passage of three or more liquid or poorly formed stools in a 24-hour period lasting less than 14 days. Persistent diarrhea lasts from 14 to 29 days, while chronic diarrhea lasts longer than 30 days. There are 47.8 million cases of acute diarrhea per year in the United States, costing $150 million in US health expenditures.1 Viral pathogens remain the most common cause of acute diarrhea in the United States.1,2 Standard O&P testing consists of applying a stool sample to a slide with either saline or iodine (wet mount) and evaluating the specimen with a microscope.

WHY YOU MIGHT THINK O&P TESTING IS HELPFUL

Giardia and Cryptosporidium remain the most commonly implicated parasitic pathogens in acute diarrheal episodes in the United States.3 Cryptosporidium cases in the United States range from 2.2 to 3.9 per 100,000 persons,4 and Giardia cases in the United States range from 5.8 to 6.4 per 100,000 persons.5 To avoid missing potentially treatable causes, providers often order O&P tests reflexively as part of a standard workup for acute diarrhea. From 2001 to 2007, Associated Regional and University Pathologists Laboratories experienced a 379% increase in O&P testing.6 Many providers ordering these tests assume that standard O&P testing covers most, if not all, parasites and that a negative test will rule out a parasitic cause of disease. Furthermore, providers are unaware that more sensitive tests to detect certain parasites have replaced standard O&P microscopy.3

WHY O&P TESTING IS USUALLY UNNECESSARY

Most hospitalized patients do not have a parasitic infection

In a review of 5,681 completed O&P tests from a tertiary care medical center in Canada over a 5-year period, only 1.4% of tests were positive.7 In a 3-year retrospective analysis of stool samples obtained after 3 days of hospitalization, positive results were found in only 1 of 191 stool cultures and in 0 of 90 O&P samples.8 Current practice guidelines suggest not testing patients with stool studies in cases of acute diarrhea lasting less than 7 days in the absence of significant risk factors for parasitic disease because it has been shown to be a rare event and most cases will self-resolve with supportive care only.1,9

The stool O&P test has low sensitivity

Classically ordered stool O&P tests have low sensitivity for the detection of Giardia and Cryptosporidium, the two most common parasites in the United States.6,10,11 O&P studies detect Giardia in only 66% to 79% of specimen samples and Cryptosporidium in less than 5% of specimens. Diagnostic yields can be improved with the use of special stains such as modified acid-fast stain (MAF).6 Despite use of MAF staining, though, sensitivity for Cryptosporidium detection has remained at only 55%.12 Additionally, several studies have shown that physicians are generally unaware of the test characteristics of stool O&P tests and they do not know to order the newer more sensitive enzyme immunoassays (EIA) or direct fluorescent antibody (DFA) tests even in situations when testing for a parasitic infection is appropriate.10,11,13,14 As stated earlier, a parasitic infection without significant risk factors is a rare event. A negative test with low or moderate sensitivity is not additive to such a low clinical suspicion because it does not significantly change posttest probability.

Testing can have adverse consequences

In addition to the low yield, O&P testing is technically complex, is time intensive, and requires an experienced technician’s interpretation. Inappropriate testing increases the cost of care and staff workload without much benefit.6 As such, some institutions have opted to send the O&P tests to labs with experienced technicians. Other institutions have adopted a restrictive stool O&P testing approach that reduces healthcare time and costs and improves the rate of positive tests.13,15 A study at a single tertiary care medical center demonstrated an estimated cost savings of $21,931 annually by implementing a computer-based algorithm to restrict testing for stool cultures and O&P tests to patients with higher probabilities of infection.15 The algorithm directed clinicians to provide further information when attempting to order stool culture, O&P, or other specific stool tests. For patients hospitalized for more than 3 days, the system did not allow certain testing. For patients with worrisome features like severe symptoms or an immunocompromised state, the algorithm directed the clinician to place an infectious disease or gastroenterology consult rather than order stool tests. Decreased laboratory costs of all stool studies (including O&P) in adult inpatient locations led to the cost savings. Additionally, the study authors felt that they likely underestimated the cost savings because they did not account for other expenses in the analysis, such as nursing workload and supplies.15

WHAT YOU SHOULD DO INSTEAD

Clinicians should evaluate patients on a case-by-case basis and determine the need to test based on the presence of high-risk features (Table).

High-Risk Features Warranting Further Stool Testing
Perform O&P testing only in patients with a high pretest probability of having a parasitic disease that will not resolve on its own.1,16 For example, if a patient recently returned from South America with acute diarrhea, EIA testing should be performed for Entamoeba histolytica. If you order O&P tests, you should order at least three spaced over 10 days to increase sensitivity. The yield with one test is 50% to 60%, but with three tests, it is >95%.17 Additionally, it is important to send a fresh stool sample that has not been contaminated with water or urine, both of which may lead to false positives. Most cases of acute diarrheal illnesses, however, do not require O&P evaluation and resolve with supportive treatment alone.

When performing parasitic testing in patients without a recent travel history but with other high-risk features, test for the most prevalent parasites in the United States (ie, Giardia, Cryptosporidium, and Entamoeba histolytica) with DFA or EIA tests.3 DFA testing for Giardia is 99% sensitive.12 In patients with symptoms lasting more than 7 days and recent travel, in addition to the above DFA/EIA tests, perform O&P testing with wet mount, modified acid-fast bacilli stain to detect rare parasites such as helminths, Strongyloides, Cyclospora, and Cystoisospora.3 In patients who live or travel to endemic areas (about 10% of traveler’s diarrhea is caused by parasitic infections), have unexplained eosinophilia, or are part of a community outbreak (eg, childcare institutions or drinking water/food outbreaks), test for Giardia, Cryptosporidium, Cyclospora, Cystoisospora, Entamoeba histolytica, and Isospora belli.9 In addition, among patients with AIDS or immunosuppression, testing should include assays for Microsporidia, Strongyloides, and Mycobacterium avium complex (Figure).9,16 Newer tests, such as the multiplex real-time polymerase chain reaction assay, can also simultaneously detect Entamoeba histolytica, Giardia lamblia, and Cryptosporidium parvum. For more information on parasitic testing, we suggest reading the review article “Beyond O&P times three.”3 It is important to familiarize yourself with the parasitic tests available at your respective clinics/hospital so the optimal test can be used.

Flow Chart for Parasite Testing

RECOMMENDATIONS

  • Prescribe a trial of “wait and see” for patients without high-risk features for parasitic disease.
  • Test patients with high-risk features for parasitic disease by utilizing targeted testing.
  • For patients with high-risk features but no travel history, first perform DFA, EIA, or multiplex real-time polymerase chain reaction testing to evaluate for Giardia, Cryptosporidium, and Entamoeba histolytica.
  • If DFA/EIA testing is negative, obtain O&P tests with and without stains, such as acid-fast bacilli, for detection of other rare parasites.

CONCLUSION

Hospitalists should risk-stratify patients to determine when O&P testing is appropriate. Employ more targeted testing, especially use of DFA/EIA tests when evaluating for parasites. Avoid parasitic testing if symptoms have lasted less than 7 days and the patient has no other high-risk features. Become familiar with the tests available at your institution and their sensitivities. As in our clinical scenario, most acute cases of diarrhea resolve without intervention and should be managed and treated conservatively.

Do you think this is a low-value practice? Is this truly a “Thing We Do for No Reason”? Share what you do in your practice and join in the conversation online by retweeting it on Twitter (#TWDFNR) and liking it on Facebook. We invite you to propose ideas for other “Things We Do for No Reason ” topics by emailing TWDFNR@hospitalmedicine.org .

Acknowledgments

The authors thank Dr Lenny Feldman for his assistance with editing the manuscript.

References

1. Riddle MS, DuPont HL, Connor BA. ACG clinical guideline: diagnosis, treatment, and prevention of acute diarrheal infections in adults. Am J Gastroenterol. 2016;111(5):602-622. https://doi.org/10.1038/ajg.2016.126
2. DuPont HL. Acute infectious diarrhea in immunocompetent adults. N Engl J Med. 2014;370(16):1532-1540. https://doi.org/10.1056/nejmra1301069
3. Mohapatra S, Singh DP, Alcid D, Pitchumoni CS. Beyond O&P times three. Am J Gastroenterol. 2018;113(6):805-818. https://doi.org/10.1038/s41395-018-0083-y
4. Painter JE, Hlavsa MC, Collier SA, Xiao L, Yoder JS. Cryptosporidiosis surveillance -- United States, 2011-2012. MMWR Suppl. 2015;64(3):1-14.
5. Painter JE, Gargano JW, Collier SA, Yoder JS. Giardiasis surveillance -- United States, 2011-2012. MMWR Suppl. 2015;64(3):15-25.
6. Polage CR, Stoddard GJ, Rolfs RT, Petti CA. Physician use of parasite tests in the United States from 1997 to 2006 and in a Utah Cryptosporidium outbreak in 2007. J Clin Microbiol. 2011;49(2):591-596. https://doi.org/10.1128/jcm.01806-10
7. Mosli M, Gregor J, Chande N, Lannigan R. Nonutility of routine testing of stool for ova and parasites in a tertiary care Canadian centre. Can J Microbiol. 2012;58(5):653-659. https://doi.org/10.1139/w2012-039
8. Siegel DL, Edelstein PH, Nachamkin I. Inappropriate testing for diarrheal diseases in the hospital. JAMA. 1990;263(7):979-982.
9. Shane AL, Mody RK, Crump JA, et al. 2017 Infectious Diseases Society of America clinical practice guidelines for the diagnosis and management of infectious diarrhea. Clin Infect Dis. 2017;65(12):e45-e80. https://doi.org/10.1093/cid/cix669
10. Hennessy TW, Marcus R, Deneen V, et al. Survey of physician diagnostic practices for patients with acute diarrhea: clinical and public health implications. Clin Infect Dis. 2004;38 (Suppl 3):S203-S211. https://doi.org/10.1086/381588
11. Morin CA, Roberts CL, Mshar PA, Addiss DG, Hadler JL. What do physicians know about cryptosporidiosis? a survey of Connecticut physicians. Arch Intern Med. 1997;157(9):1017-1022.
12. McHardy IH, Wu M, Shimizu-Cohen R, Couturier MR, Humphries RM. Detection of intestinal protozoa in the clinical laboratory. J Clin Microbiol. 2014;52(3):712-720. https://doi.org/10.1128/jcm.02877-13
13. Valenstein P, Pfaller M, Yungbluth M. The use and abuse of routine stool microbiology: a College of American Pathologists Q-probes study of 601 institutions. Arch Pathol Lab Med. 1996;120(2):206-211.
14. Jones JL, Lopez A, Wahlquist SP, Nadle J, Wilson M; Emerging Infections Program FoodNet Working Group. Survey of clinical laboratory practices for parasitic diseases. Clin Infect Dis. 2004;38(Suppl 3):S198-S202. https://doi.org/10.1086/381587
15. Tewell CE, Talbot TR, Nelson GE, et al. Reducing inappropriate testing for the evaluation of diarrhea among hospitalized patients. Am J Med. 2018;131(2):193-199.e1. https://doi.org/10.1016/j.amjmed.2017.10.006
16. Thielman NM, Guerrant RL. Clinical practice. acute infectious diarrhea. N Engl J Med. 2004;350(1):38-47. https://doi.org/10.1056/nejmcp031534
17. Marti H, Koella JC. Multiple stool examinations for ova and parasites and rate of false-negative results. J Clin Microbiol. 1993;31(11):3044-3045. https://doi.org/10.1128/jcm.31.11.3044-3045.1993

References

1. Riddle MS, DuPont HL, Connor BA. ACG clinical guideline: diagnosis, treatment, and prevention of acute diarrheal infections in adults. Am J Gastroenterol. 2016;111(5):602-622. https://doi.org/10.1038/ajg.2016.126
2. DuPont HL. Acute infectious diarrhea in immunocompetent adults. N Engl J Med. 2014;370(16):1532-1540. https://doi.org/10.1056/nejmra1301069
3. Mohapatra S, Singh DP, Alcid D, Pitchumoni CS. Beyond O&P times three. Am J Gastroenterol. 2018;113(6):805-818. https://doi.org/10.1038/s41395-018-0083-y
4. Painter JE, Hlavsa MC, Collier SA, Xiao L, Yoder JS. Cryptosporidiosis surveillance -- United States, 2011-2012. MMWR Suppl. 2015;64(3):1-14.
5. Painter JE, Gargano JW, Collier SA, Yoder JS. Giardiasis surveillance -- United States, 2011-2012. MMWR Suppl. 2015;64(3):15-25.
6. Polage CR, Stoddard GJ, Rolfs RT, Petti CA. Physician use of parasite tests in the United States from 1997 to 2006 and in a Utah Cryptosporidium outbreak in 2007. J Clin Microbiol. 2011;49(2):591-596. https://doi.org/10.1128/jcm.01806-10
7. Mosli M, Gregor J, Chande N, Lannigan R. Nonutility of routine testing of stool for ova and parasites in a tertiary care Canadian centre. Can J Microbiol. 2012;58(5):653-659. https://doi.org/10.1139/w2012-039
8. Siegel DL, Edelstein PH, Nachamkin I. Inappropriate testing for diarrheal diseases in the hospital. JAMA. 1990;263(7):979-982.
9. Shane AL, Mody RK, Crump JA, et al. 2017 Infectious Diseases Society of America clinical practice guidelines for the diagnosis and management of infectious diarrhea. Clin Infect Dis. 2017;65(12):e45-e80. https://doi.org/10.1093/cid/cix669
10. Hennessy TW, Marcus R, Deneen V, et al. Survey of physician diagnostic practices for patients with acute diarrhea: clinical and public health implications. Clin Infect Dis. 2004;38 (Suppl 3):S203-S211. https://doi.org/10.1086/381588
11. Morin CA, Roberts CL, Mshar PA, Addiss DG, Hadler JL. What do physicians know about cryptosporidiosis? a survey of Connecticut physicians. Arch Intern Med. 1997;157(9):1017-1022.
12. McHardy IH, Wu M, Shimizu-Cohen R, Couturier MR, Humphries RM. Detection of intestinal protozoa in the clinical laboratory. J Clin Microbiol. 2014;52(3):712-720. https://doi.org/10.1128/jcm.02877-13
13. Valenstein P, Pfaller M, Yungbluth M. The use and abuse of routine stool microbiology: a College of American Pathologists Q-probes study of 601 institutions. Arch Pathol Lab Med. 1996;120(2):206-211.
14. Jones JL, Lopez A, Wahlquist SP, Nadle J, Wilson M; Emerging Infections Program FoodNet Working Group. Survey of clinical laboratory practices for parasitic diseases. Clin Infect Dis. 2004;38(Suppl 3):S198-S202. https://doi.org/10.1086/381587
15. Tewell CE, Talbot TR, Nelson GE, et al. Reducing inappropriate testing for the evaluation of diarrhea among hospitalized patients. Am J Med. 2018;131(2):193-199.e1. https://doi.org/10.1016/j.amjmed.2017.10.006
16. Thielman NM, Guerrant RL. Clinical practice. acute infectious diarrhea. N Engl J Med. 2004;350(1):38-47. https://doi.org/10.1056/nejmcp031534
17. Marti H, Koella JC. Multiple stool examinations for ova and parasites and rate of false-negative results. J Clin Microbiol. 1993;31(11):3044-3045. https://doi.org/10.1128/jcm.31.11.3044-3045.1993

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Limiting Patient Autonomy: Mandatory COVID-19 Diagnostic Testing

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Despite the important clinical and public health implications of a COVID-19 diagnosis, respect for autonomy allows patients to decline testing without explanation and with impunity. Whether physicians believe a test is indicated for clinical care of an individual patient, prevention of nosocomial transmission, or the greater public health, patients may refuse. Such refusals may be increasing due to quarantine requirements, concerns regarding contact tracing, and the persistent absence of a curative treatment.1,2 Mass screening of all healthcare workers (HCWs) is being considered to prevent hospital transmission,3 and universal screening in nursing homes has thwarted outbreaks while providing data to facilitate resource allocation.4 Given these circumstances, patients’ absolute right to refuse a noninvasive test with the potential for multifaceted downstream benefit is worthy of reconsideration, in favor of mandatory testing. Mandatory testing confers numerous benefits, including mitigating risk to other patients and HCWs, who play a central role in pandemic response. Because infected HCWs may transmit the virus to patients, they also should undergo mandatory testing,3 particularly in the presence of symptoms, since nasal secretions increase the diagnostic yield of testing.5 Although pretest probability (as an estimate of disease prevalence) typically determines the testing strategy for admitted patients, model-based analyses suggest that testing every 3 days for HCWs or continuously hospitalized patients would nearly eliminate infectivity.6

Tools for assisting frustrated HCWs navigating patients’ right to refuse testing have been developed that incorporate education, clear communication, and conflict resolution.7 Such approaches are, however, only moderately successful, making the use of personal protective equipment (PPE) based on a default assumption of COVID-19 positivity common.8 The burden and disheartening waste created by low-yield PPE use among patients unwilling to be tested becomes particularly evident in the context of shortages. Such vexing, stressful shortages, as well as the dual responsibilities of hospitals as stewards of both individual patient and population health, serve as reminders that efficient allocation of resources must be valued alongside the autonomous rights of patients.9 Moreover, recent reports suggest that test avoidance is a growing problem.1,2 Refusal to accept testing may be rooted in anxiety, concerns about the consequences of a positive result (eg, inability to attend school or work), or a desire for self-determination.1,2 The hesitancy that leads to refusal may also arise from misinformation, poor public health messaging, distrust in the establishment, and unproductive considerations related to conscientious objection without foundation.2 Concepts of individual liberty that often underlie steadfast adherence to the principles of self-determination created opposition to masks that antagonized public health efforts to limit the spread of COVID-19. Although influencing inpatients’ behavior to benefit both the public and HCWs may be distinct from community settings, the attitudes that lead to test refusal and defiance of mask-related ordinances likely have substantial commonalities.

THE PATIENT ROLE IN HEALTHCARE DECISIONS

As a pillar of ethical decision-making, patient autonomy plays a powerful role in healthcare decisions in the United States. Whereas values such as beneficence, nonmaleficence, advocacy, and distributive justice impact certain decisions, patient autonomy has evolved into the dominant value. Although the beneficence model had historically guided medical decision-making, the bioethics community spearheaded the emergence of the autonomy model during the past several decades.10 Benevolent deception (ie, therapeutic privilege) and medical paternalism were central features of the beneficence model.11 However, the cornerstone of the autonomy model is informed consent, which provides assurance that patients will be neither deceived nor coerced.10 Professionalism has always presupposed that the beneficence model would result in decisions directed at both improving patient health and minimizing individual patient harms. The public good and consequent positive externalities were acceptable considerations in decisions based on therapeutic privilege before the autonomy model became dominant. In keeping with the philosophical underpinnings of this approach, advocacy for the public health is still considered a justification for limiting informed consent and breaching confidentiality for disease reporting and contact tracing.9

ANALOGOUS EXPERIENCES: ETHICAL LESSONS AND PRACTICAL IMPLICATIONS

In non-healthcare settings, the controversies surrounding vaccination and access to schools for unvaccinated children are perhaps the public and professional debate most analogous to COVID-19 testing refusal.12 Although policymakers may distinguish between testing and vaccination, these interventions similarly hold the potential to limit disease incidence and mitigate health impact. To preserve public health, most states prevent (with varied exemptions) unvaccinated children from attending schools. COVID-19 testing may in the future become a requirement for participation in group social activities, athletic competitions, or physical presence in the workplace to facilitate quarantining and/or targeted use of PPE for transmission risk reduction. Given the dramatic mitigation benefits accruable on college campuses,13 required testing for in-person learning has become common.

There are also parallels, and therefore lessons, to be drawn from experience in testing for HIV, although HIV-related stigma and devalued status of the marginalized populations initially infected impacted the broader societal view of HIV compared with COVID-19. For example, antenatal HIV screening of pregnant women is strongly recommended to facilitate interventions that reduce the chance of vertical transmission.14 The limitations of purely elective testing are one justification for the current standard of opt-out screening. However, in this case, the health complications of refusal are largely the burden of the fetus, over whose future the mother holds a great deal of choice and responsibility, irrespective of HIV status. The public health implications of HIV test refusal are far less immediate than for COVID-19 infection because there is no effective curative therapy for COVID-19 and spread occurs through nonintimate, unintentional, and unpredictable exposure.

Translating societal attitudes and practices into the healthcare setting to consider mandated COVID-19 testing requires additional considerations related to both patients and providers: (1) HCWs have committed to a set of values and professional obligations that include tasks requiring risks15; (2) the public expects HCWs to perform their duties according to a social contract that has few restrictions16; (3) limiting patient access to hospital care due to COVID-19 testing refusal would contradict and create conflicts related to professional conceptions of hospitals and physicians as patient agents15; and (4) patients who conscientiously object to testing may seek healthcare less diligently, which may lead to health decrements. The associated postponement of essential care may unduly burden the healthcare system, particularly in situations such as ambulatory care–sensitive conditions.

HEALTHCARE WORKER PROTECTION, PATIENT ACCESS, AND THE VALUE OF PARSIMONY

The extent to which the public health justification for mandatory testing extends to hospitalized patients to protect HCWs is ambiguous. HCWs are of enormous instrumental value and are therefore essential for the pandemic response and health of the broader population. Their protection may therefore justify curtailing informed consent for diagnostic testing. Downstream effects on the supply of frontline HCWs may be realized. Poor control over working conditions may negatively impact motivation among HCWs. In addition, they may feel disenfranchised while obligatorily taking personal risks in caring for patients unwilling to commit to the common good through diagnostic test consent. Hospitalized patients who refuse testing may remain patients under investigation (PUIs), thus requiring special respiratory precautions (SRP) throughout their hospitalization, thereby placing a persistent burden on those with responsibilities requiring patient contact.17 Repeatedly donning and doffing PPE may remind at-risk HCWs that a myriad of benefits may accrue from frequent, ubiquitous testing. Their motivation may be tempered by the demoralizing requirement to care for patients who will not consent to a simple test, knowing that an opportunity to diminish the burdens of this communicable disease that has taken the lives of many HCWs is being relinquished.

Although HCWs could use SRP universally, their selective application in rooms of known COVID-19–positive patients and those with temporary PUI status has several advantages.17 First, we learned that HIV testing on patients was helpful in enabling surgeons to selectively implement special precautions among infected patients rather than universally applied intensive precautions. Even in the setting of high rates of HIV infection and educational interventions, HCWs do not reliably apply protective measures included in universal precautions.18 In keeping with these experiences, limiting the number of patients on SRP will minimize the “precautions fatigue” that drives nonadherent behavior among HCWs.17 As a result, minimizing the proportion of patients on SRP through testing (and liberation from unnecessary precautions in most cases) will improve uptake of crucial hand hygiene practices and adoption of vigilant PPE use. Second, definitive knowledge of COVID-19 status will increase patient access to care because, whether by personal choice or policy, many HCWs limit in-person contact with patients who are or may be COVID-19 positive. For example, many inpatient dialysis units do not accept patients without a negative COVID-19 nasal swab. Physical therapists may delay or avoid seeing a PUI, which will pose challenges for efficient determination of discharge disposition. Third, selective use of SRP will limit the environmental impact of disposed PPE, which is neither recyclable nor biodegradable. Infectious or regulated biomedical waste products are a significant source of environmental pollution, and the World Health Organization has recommended parsimonious, selective use of PPE to minimize the adverse environmental consequences of biomedical waste products.

CONCLUSION

In summary, there are substantial justifications for mandatory testing for COVID-19 in the hospital for HCWs and patients, as has been successfully piloted in selected long-term care facilities. Patients who refuse to allow testing may have to accept that their care may be compromised. For preservation of HCW supply and maintenance of HCW morale, hospital policies should make explicit, without punishment or coercion, that HCWs may modify the care they provide to patients who refuse to consent to COVID-19 testing.

References

1. Morris NP. Refusing testing during a pandemic. Am J Public Health. 2020;110(9):1354-1355. https://doi.org/10.2105/AJPH.2020.305810
2. Rubin R. First it was masks; now some refuse testing for SARS-CoV-2. JAMA. 2020;324(20):2015-2016. https://doi.org/10.1001/jama.2020.22003
3. Black JRM, Bailey C, Przewrocka J, Dijkstra KK, Swanton C. COVID-19: the case for health-care worker screening to prevent hospital transmission. Lancet. 2020;395(10234):1418-1420. https://doi.org/10.1016/S0140-6736(20)30917-X
4. McBee SM, Thomasson ED, Scott MA, et al. Notes from the field: universal statewide laboratory testing for SARS-CoV-2 in nursing homes—West Virginia, April 21–May 8, 2020. MMWR Morb Mortal Wkly Rep. 2020;69(34):1177-1179. http://dx.doi.org/10.15585/mmwr.mm6934a4
5. Long DR, Gombar S, Hogan CA, et al. Occurrence and timing of subsequent severe acute respiratory syndrome coronavirus 2 reverse-transcription polymerase chain reaction positivity among initially negative patients. Clin Infect Dis. 2021;72(2):323-326. https://doi.org/10.1093/cid/ciaa722
6. Larremore DB, Wilder B, Lester E, et al. Test sensitivity is secondary to frequency and turnaround time for COVID-19 screening. Sci Adv. 2021;7(1):eabd5393. https://advances.sciencemag.org/content/7/1/eabd5393
7. Lu AC, Burgart AM. Elective surgery and COVID-19: a framework for the untested patient. Ann Surg. 2020;272(6):e291-e295. https://doi.org/10.1097/SLA.0000000000004474
8. Podboy A, Cholankeril G, Cianfichi L, Guzman E Jr, Ahmed A, Banerjee S. Implementation and impact of universal preprocedure testing of patients for COVID-19 before endoscopy. Gastroenterology. 2020;159(4):1586-1588. https://doi.org/10.1053/j.gastro.2020.06.022
9. O’Neill O. Some limits of informed consent. J Med Ethics. 2003;29(1):4-7. https://doi.org/10.1136/jme.29.1.4
10. Will JF. A brief historical and theoretical perspective on patient autonomy and medical decision making: part II: the autonomy model. Chest. 2011;139(6):1491-1497. https://doi.org/10.1378/chest.11-0516
11. Will JF. A brief historical and theoretical perspective on patient autonomy and medical decision making: part I: the beneficence model. Chest. 2011;139(3):669-673. https://doi.org/10.1378/chest.10-2532
12. Hendrix KS, Sturm LA, Zimet GD, Meslin EM. Ethics and childhood vaccination policy in the United States. Am J Public Health. 2016;106(2):273-278. https://doi.org/10.2105/AJPH.2015.302952
13. Losina E, Leifer V, Millham L, et al. College campuses and COVID-19 mitigation: clinical and economic value. Ann Intern Med. Published online December 21, 2020. https://doi.org/10.7326/M20-6558
14. Selph SS, Bougatsos C, Dana T, Grusing S, Chou R. Screening for HIV infection in pregnant women: updated evidence report and systematic review for the US Preventive Services Task Force. JAMA. 2019;321(23):2349-2360. https://doi.org/10.1001/jama.2019.2593
15. Dranove D, White WD. Agency and the organization of health care delivery. Inquiry. 1987;24(4):405-415.
16. Huber SJ, Wynia MK. When pestilence prevails...physician responsibilities in epidemics. Am J Bioeth. 2004;4(1):W5-W11. https://www.tandfonline.com/doi/abs/10.1162/152651604773067497
17. Ruhnke GW. COVID-19 diagnostic testing and the psychology of precautions fatigue. Cleve Clin J Med. 2020;88(1):19-21. https://doi.org/10.3949/ccjm.88a.20086
18. Freeman SW, Chambers CV. Compliance with universal precautions in a medical practice with a high rate of HIV infection. J Am Board Fam Pract. 1992;5(3):313-318.

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Despite the important clinical and public health implications of a COVID-19 diagnosis, respect for autonomy allows patients to decline testing without explanation and with impunity. Whether physicians believe a test is indicated for clinical care of an individual patient, prevention of nosocomial transmission, or the greater public health, patients may refuse. Such refusals may be increasing due to quarantine requirements, concerns regarding contact tracing, and the persistent absence of a curative treatment.1,2 Mass screening of all healthcare workers (HCWs) is being considered to prevent hospital transmission,3 and universal screening in nursing homes has thwarted outbreaks while providing data to facilitate resource allocation.4 Given these circumstances, patients’ absolute right to refuse a noninvasive test with the potential for multifaceted downstream benefit is worthy of reconsideration, in favor of mandatory testing. Mandatory testing confers numerous benefits, including mitigating risk to other patients and HCWs, who play a central role in pandemic response. Because infected HCWs may transmit the virus to patients, they also should undergo mandatory testing,3 particularly in the presence of symptoms, since nasal secretions increase the diagnostic yield of testing.5 Although pretest probability (as an estimate of disease prevalence) typically determines the testing strategy for admitted patients, model-based analyses suggest that testing every 3 days for HCWs or continuously hospitalized patients would nearly eliminate infectivity.6

Tools for assisting frustrated HCWs navigating patients’ right to refuse testing have been developed that incorporate education, clear communication, and conflict resolution.7 Such approaches are, however, only moderately successful, making the use of personal protective equipment (PPE) based on a default assumption of COVID-19 positivity common.8 The burden and disheartening waste created by low-yield PPE use among patients unwilling to be tested becomes particularly evident in the context of shortages. Such vexing, stressful shortages, as well as the dual responsibilities of hospitals as stewards of both individual patient and population health, serve as reminders that efficient allocation of resources must be valued alongside the autonomous rights of patients.9 Moreover, recent reports suggest that test avoidance is a growing problem.1,2 Refusal to accept testing may be rooted in anxiety, concerns about the consequences of a positive result (eg, inability to attend school or work), or a desire for self-determination.1,2 The hesitancy that leads to refusal may also arise from misinformation, poor public health messaging, distrust in the establishment, and unproductive considerations related to conscientious objection without foundation.2 Concepts of individual liberty that often underlie steadfast adherence to the principles of self-determination created opposition to masks that antagonized public health efforts to limit the spread of COVID-19. Although influencing inpatients’ behavior to benefit both the public and HCWs may be distinct from community settings, the attitudes that lead to test refusal and defiance of mask-related ordinances likely have substantial commonalities.

THE PATIENT ROLE IN HEALTHCARE DECISIONS

As a pillar of ethical decision-making, patient autonomy plays a powerful role in healthcare decisions in the United States. Whereas values such as beneficence, nonmaleficence, advocacy, and distributive justice impact certain decisions, patient autonomy has evolved into the dominant value. Although the beneficence model had historically guided medical decision-making, the bioethics community spearheaded the emergence of the autonomy model during the past several decades.10 Benevolent deception (ie, therapeutic privilege) and medical paternalism were central features of the beneficence model.11 However, the cornerstone of the autonomy model is informed consent, which provides assurance that patients will be neither deceived nor coerced.10 Professionalism has always presupposed that the beneficence model would result in decisions directed at both improving patient health and minimizing individual patient harms. The public good and consequent positive externalities were acceptable considerations in decisions based on therapeutic privilege before the autonomy model became dominant. In keeping with the philosophical underpinnings of this approach, advocacy for the public health is still considered a justification for limiting informed consent and breaching confidentiality for disease reporting and contact tracing.9

ANALOGOUS EXPERIENCES: ETHICAL LESSONS AND PRACTICAL IMPLICATIONS

In non-healthcare settings, the controversies surrounding vaccination and access to schools for unvaccinated children are perhaps the public and professional debate most analogous to COVID-19 testing refusal.12 Although policymakers may distinguish between testing and vaccination, these interventions similarly hold the potential to limit disease incidence and mitigate health impact. To preserve public health, most states prevent (with varied exemptions) unvaccinated children from attending schools. COVID-19 testing may in the future become a requirement for participation in group social activities, athletic competitions, or physical presence in the workplace to facilitate quarantining and/or targeted use of PPE for transmission risk reduction. Given the dramatic mitigation benefits accruable on college campuses,13 required testing for in-person learning has become common.

There are also parallels, and therefore lessons, to be drawn from experience in testing for HIV, although HIV-related stigma and devalued status of the marginalized populations initially infected impacted the broader societal view of HIV compared with COVID-19. For example, antenatal HIV screening of pregnant women is strongly recommended to facilitate interventions that reduce the chance of vertical transmission.14 The limitations of purely elective testing are one justification for the current standard of opt-out screening. However, in this case, the health complications of refusal are largely the burden of the fetus, over whose future the mother holds a great deal of choice and responsibility, irrespective of HIV status. The public health implications of HIV test refusal are far less immediate than for COVID-19 infection because there is no effective curative therapy for COVID-19 and spread occurs through nonintimate, unintentional, and unpredictable exposure.

Translating societal attitudes and practices into the healthcare setting to consider mandated COVID-19 testing requires additional considerations related to both patients and providers: (1) HCWs have committed to a set of values and professional obligations that include tasks requiring risks15; (2) the public expects HCWs to perform their duties according to a social contract that has few restrictions16; (3) limiting patient access to hospital care due to COVID-19 testing refusal would contradict and create conflicts related to professional conceptions of hospitals and physicians as patient agents15; and (4) patients who conscientiously object to testing may seek healthcare less diligently, which may lead to health decrements. The associated postponement of essential care may unduly burden the healthcare system, particularly in situations such as ambulatory care–sensitive conditions.

HEALTHCARE WORKER PROTECTION, PATIENT ACCESS, AND THE VALUE OF PARSIMONY

The extent to which the public health justification for mandatory testing extends to hospitalized patients to protect HCWs is ambiguous. HCWs are of enormous instrumental value and are therefore essential for the pandemic response and health of the broader population. Their protection may therefore justify curtailing informed consent for diagnostic testing. Downstream effects on the supply of frontline HCWs may be realized. Poor control over working conditions may negatively impact motivation among HCWs. In addition, they may feel disenfranchised while obligatorily taking personal risks in caring for patients unwilling to commit to the common good through diagnostic test consent. Hospitalized patients who refuse testing may remain patients under investigation (PUIs), thus requiring special respiratory precautions (SRP) throughout their hospitalization, thereby placing a persistent burden on those with responsibilities requiring patient contact.17 Repeatedly donning and doffing PPE may remind at-risk HCWs that a myriad of benefits may accrue from frequent, ubiquitous testing. Their motivation may be tempered by the demoralizing requirement to care for patients who will not consent to a simple test, knowing that an opportunity to diminish the burdens of this communicable disease that has taken the lives of many HCWs is being relinquished.

Although HCWs could use SRP universally, their selective application in rooms of known COVID-19–positive patients and those with temporary PUI status has several advantages.17 First, we learned that HIV testing on patients was helpful in enabling surgeons to selectively implement special precautions among infected patients rather than universally applied intensive precautions. Even in the setting of high rates of HIV infection and educational interventions, HCWs do not reliably apply protective measures included in universal precautions.18 In keeping with these experiences, limiting the number of patients on SRP will minimize the “precautions fatigue” that drives nonadherent behavior among HCWs.17 As a result, minimizing the proportion of patients on SRP through testing (and liberation from unnecessary precautions in most cases) will improve uptake of crucial hand hygiene practices and adoption of vigilant PPE use. Second, definitive knowledge of COVID-19 status will increase patient access to care because, whether by personal choice or policy, many HCWs limit in-person contact with patients who are or may be COVID-19 positive. For example, many inpatient dialysis units do not accept patients without a negative COVID-19 nasal swab. Physical therapists may delay or avoid seeing a PUI, which will pose challenges for efficient determination of discharge disposition. Third, selective use of SRP will limit the environmental impact of disposed PPE, which is neither recyclable nor biodegradable. Infectious or regulated biomedical waste products are a significant source of environmental pollution, and the World Health Organization has recommended parsimonious, selective use of PPE to minimize the adverse environmental consequences of biomedical waste products.

CONCLUSION

In summary, there are substantial justifications for mandatory testing for COVID-19 in the hospital for HCWs and patients, as has been successfully piloted in selected long-term care facilities. Patients who refuse to allow testing may have to accept that their care may be compromised. For preservation of HCW supply and maintenance of HCW morale, hospital policies should make explicit, without punishment or coercion, that HCWs may modify the care they provide to patients who refuse to consent to COVID-19 testing.

Despite the important clinical and public health implications of a COVID-19 diagnosis, respect for autonomy allows patients to decline testing without explanation and with impunity. Whether physicians believe a test is indicated for clinical care of an individual patient, prevention of nosocomial transmission, or the greater public health, patients may refuse. Such refusals may be increasing due to quarantine requirements, concerns regarding contact tracing, and the persistent absence of a curative treatment.1,2 Mass screening of all healthcare workers (HCWs) is being considered to prevent hospital transmission,3 and universal screening in nursing homes has thwarted outbreaks while providing data to facilitate resource allocation.4 Given these circumstances, patients’ absolute right to refuse a noninvasive test with the potential for multifaceted downstream benefit is worthy of reconsideration, in favor of mandatory testing. Mandatory testing confers numerous benefits, including mitigating risk to other patients and HCWs, who play a central role in pandemic response. Because infected HCWs may transmit the virus to patients, they also should undergo mandatory testing,3 particularly in the presence of symptoms, since nasal secretions increase the diagnostic yield of testing.5 Although pretest probability (as an estimate of disease prevalence) typically determines the testing strategy for admitted patients, model-based analyses suggest that testing every 3 days for HCWs or continuously hospitalized patients would nearly eliminate infectivity.6

Tools for assisting frustrated HCWs navigating patients’ right to refuse testing have been developed that incorporate education, clear communication, and conflict resolution.7 Such approaches are, however, only moderately successful, making the use of personal protective equipment (PPE) based on a default assumption of COVID-19 positivity common.8 The burden and disheartening waste created by low-yield PPE use among patients unwilling to be tested becomes particularly evident in the context of shortages. Such vexing, stressful shortages, as well as the dual responsibilities of hospitals as stewards of both individual patient and population health, serve as reminders that efficient allocation of resources must be valued alongside the autonomous rights of patients.9 Moreover, recent reports suggest that test avoidance is a growing problem.1,2 Refusal to accept testing may be rooted in anxiety, concerns about the consequences of a positive result (eg, inability to attend school or work), or a desire for self-determination.1,2 The hesitancy that leads to refusal may also arise from misinformation, poor public health messaging, distrust in the establishment, and unproductive considerations related to conscientious objection without foundation.2 Concepts of individual liberty that often underlie steadfast adherence to the principles of self-determination created opposition to masks that antagonized public health efforts to limit the spread of COVID-19. Although influencing inpatients’ behavior to benefit both the public and HCWs may be distinct from community settings, the attitudes that lead to test refusal and defiance of mask-related ordinances likely have substantial commonalities.

THE PATIENT ROLE IN HEALTHCARE DECISIONS

As a pillar of ethical decision-making, patient autonomy plays a powerful role in healthcare decisions in the United States. Whereas values such as beneficence, nonmaleficence, advocacy, and distributive justice impact certain decisions, patient autonomy has evolved into the dominant value. Although the beneficence model had historically guided medical decision-making, the bioethics community spearheaded the emergence of the autonomy model during the past several decades.10 Benevolent deception (ie, therapeutic privilege) and medical paternalism were central features of the beneficence model.11 However, the cornerstone of the autonomy model is informed consent, which provides assurance that patients will be neither deceived nor coerced.10 Professionalism has always presupposed that the beneficence model would result in decisions directed at both improving patient health and minimizing individual patient harms. The public good and consequent positive externalities were acceptable considerations in decisions based on therapeutic privilege before the autonomy model became dominant. In keeping with the philosophical underpinnings of this approach, advocacy for the public health is still considered a justification for limiting informed consent and breaching confidentiality for disease reporting and contact tracing.9

ANALOGOUS EXPERIENCES: ETHICAL LESSONS AND PRACTICAL IMPLICATIONS

In non-healthcare settings, the controversies surrounding vaccination and access to schools for unvaccinated children are perhaps the public and professional debate most analogous to COVID-19 testing refusal.12 Although policymakers may distinguish between testing and vaccination, these interventions similarly hold the potential to limit disease incidence and mitigate health impact. To preserve public health, most states prevent (with varied exemptions) unvaccinated children from attending schools. COVID-19 testing may in the future become a requirement for participation in group social activities, athletic competitions, or physical presence in the workplace to facilitate quarantining and/or targeted use of PPE for transmission risk reduction. Given the dramatic mitigation benefits accruable on college campuses,13 required testing for in-person learning has become common.

There are also parallels, and therefore lessons, to be drawn from experience in testing for HIV, although HIV-related stigma and devalued status of the marginalized populations initially infected impacted the broader societal view of HIV compared with COVID-19. For example, antenatal HIV screening of pregnant women is strongly recommended to facilitate interventions that reduce the chance of vertical transmission.14 The limitations of purely elective testing are one justification for the current standard of opt-out screening. However, in this case, the health complications of refusal are largely the burden of the fetus, over whose future the mother holds a great deal of choice and responsibility, irrespective of HIV status. The public health implications of HIV test refusal are far less immediate than for COVID-19 infection because there is no effective curative therapy for COVID-19 and spread occurs through nonintimate, unintentional, and unpredictable exposure.

Translating societal attitudes and practices into the healthcare setting to consider mandated COVID-19 testing requires additional considerations related to both patients and providers: (1) HCWs have committed to a set of values and professional obligations that include tasks requiring risks15; (2) the public expects HCWs to perform their duties according to a social contract that has few restrictions16; (3) limiting patient access to hospital care due to COVID-19 testing refusal would contradict and create conflicts related to professional conceptions of hospitals and physicians as patient agents15; and (4) patients who conscientiously object to testing may seek healthcare less diligently, which may lead to health decrements. The associated postponement of essential care may unduly burden the healthcare system, particularly in situations such as ambulatory care–sensitive conditions.

HEALTHCARE WORKER PROTECTION, PATIENT ACCESS, AND THE VALUE OF PARSIMONY

The extent to which the public health justification for mandatory testing extends to hospitalized patients to protect HCWs is ambiguous. HCWs are of enormous instrumental value and are therefore essential for the pandemic response and health of the broader population. Their protection may therefore justify curtailing informed consent for diagnostic testing. Downstream effects on the supply of frontline HCWs may be realized. Poor control over working conditions may negatively impact motivation among HCWs. In addition, they may feel disenfranchised while obligatorily taking personal risks in caring for patients unwilling to commit to the common good through diagnostic test consent. Hospitalized patients who refuse testing may remain patients under investigation (PUIs), thus requiring special respiratory precautions (SRP) throughout their hospitalization, thereby placing a persistent burden on those with responsibilities requiring patient contact.17 Repeatedly donning and doffing PPE may remind at-risk HCWs that a myriad of benefits may accrue from frequent, ubiquitous testing. Their motivation may be tempered by the demoralizing requirement to care for patients who will not consent to a simple test, knowing that an opportunity to diminish the burdens of this communicable disease that has taken the lives of many HCWs is being relinquished.

Although HCWs could use SRP universally, their selective application in rooms of known COVID-19–positive patients and those with temporary PUI status has several advantages.17 First, we learned that HIV testing on patients was helpful in enabling surgeons to selectively implement special precautions among infected patients rather than universally applied intensive precautions. Even in the setting of high rates of HIV infection and educational interventions, HCWs do not reliably apply protective measures included in universal precautions.18 In keeping with these experiences, limiting the number of patients on SRP will minimize the “precautions fatigue” that drives nonadherent behavior among HCWs.17 As a result, minimizing the proportion of patients on SRP through testing (and liberation from unnecessary precautions in most cases) will improve uptake of crucial hand hygiene practices and adoption of vigilant PPE use. Second, definitive knowledge of COVID-19 status will increase patient access to care because, whether by personal choice or policy, many HCWs limit in-person contact with patients who are or may be COVID-19 positive. For example, many inpatient dialysis units do not accept patients without a negative COVID-19 nasal swab. Physical therapists may delay or avoid seeing a PUI, which will pose challenges for efficient determination of discharge disposition. Third, selective use of SRP will limit the environmental impact of disposed PPE, which is neither recyclable nor biodegradable. Infectious or regulated biomedical waste products are a significant source of environmental pollution, and the World Health Organization has recommended parsimonious, selective use of PPE to minimize the adverse environmental consequences of biomedical waste products.

CONCLUSION

In summary, there are substantial justifications for mandatory testing for COVID-19 in the hospital for HCWs and patients, as has been successfully piloted in selected long-term care facilities. Patients who refuse to allow testing may have to accept that their care may be compromised. For preservation of HCW supply and maintenance of HCW morale, hospital policies should make explicit, without punishment or coercion, that HCWs may modify the care they provide to patients who refuse to consent to COVID-19 testing.

References

1. Morris NP. Refusing testing during a pandemic. Am J Public Health. 2020;110(9):1354-1355. https://doi.org/10.2105/AJPH.2020.305810
2. Rubin R. First it was masks; now some refuse testing for SARS-CoV-2. JAMA. 2020;324(20):2015-2016. https://doi.org/10.1001/jama.2020.22003
3. Black JRM, Bailey C, Przewrocka J, Dijkstra KK, Swanton C. COVID-19: the case for health-care worker screening to prevent hospital transmission. Lancet. 2020;395(10234):1418-1420. https://doi.org/10.1016/S0140-6736(20)30917-X
4. McBee SM, Thomasson ED, Scott MA, et al. Notes from the field: universal statewide laboratory testing for SARS-CoV-2 in nursing homes—West Virginia, April 21–May 8, 2020. MMWR Morb Mortal Wkly Rep. 2020;69(34):1177-1179. http://dx.doi.org/10.15585/mmwr.mm6934a4
5. Long DR, Gombar S, Hogan CA, et al. Occurrence and timing of subsequent severe acute respiratory syndrome coronavirus 2 reverse-transcription polymerase chain reaction positivity among initially negative patients. Clin Infect Dis. 2021;72(2):323-326. https://doi.org/10.1093/cid/ciaa722
6. Larremore DB, Wilder B, Lester E, et al. Test sensitivity is secondary to frequency and turnaround time for COVID-19 screening. Sci Adv. 2021;7(1):eabd5393. https://advances.sciencemag.org/content/7/1/eabd5393
7. Lu AC, Burgart AM. Elective surgery and COVID-19: a framework for the untested patient. Ann Surg. 2020;272(6):e291-e295. https://doi.org/10.1097/SLA.0000000000004474
8. Podboy A, Cholankeril G, Cianfichi L, Guzman E Jr, Ahmed A, Banerjee S. Implementation and impact of universal preprocedure testing of patients for COVID-19 before endoscopy. Gastroenterology. 2020;159(4):1586-1588. https://doi.org/10.1053/j.gastro.2020.06.022
9. O’Neill O. Some limits of informed consent. J Med Ethics. 2003;29(1):4-7. https://doi.org/10.1136/jme.29.1.4
10. Will JF. A brief historical and theoretical perspective on patient autonomy and medical decision making: part II: the autonomy model. Chest. 2011;139(6):1491-1497. https://doi.org/10.1378/chest.11-0516
11. Will JF. A brief historical and theoretical perspective on patient autonomy and medical decision making: part I: the beneficence model. Chest. 2011;139(3):669-673. https://doi.org/10.1378/chest.10-2532
12. Hendrix KS, Sturm LA, Zimet GD, Meslin EM. Ethics and childhood vaccination policy in the United States. Am J Public Health. 2016;106(2):273-278. https://doi.org/10.2105/AJPH.2015.302952
13. Losina E, Leifer V, Millham L, et al. College campuses and COVID-19 mitigation: clinical and economic value. Ann Intern Med. Published online December 21, 2020. https://doi.org/10.7326/M20-6558
14. Selph SS, Bougatsos C, Dana T, Grusing S, Chou R. Screening for HIV infection in pregnant women: updated evidence report and systematic review for the US Preventive Services Task Force. JAMA. 2019;321(23):2349-2360. https://doi.org/10.1001/jama.2019.2593
15. Dranove D, White WD. Agency and the organization of health care delivery. Inquiry. 1987;24(4):405-415.
16. Huber SJ, Wynia MK. When pestilence prevails...physician responsibilities in epidemics. Am J Bioeth. 2004;4(1):W5-W11. https://www.tandfonline.com/doi/abs/10.1162/152651604773067497
17. Ruhnke GW. COVID-19 diagnostic testing and the psychology of precautions fatigue. Cleve Clin J Med. 2020;88(1):19-21. https://doi.org/10.3949/ccjm.88a.20086
18. Freeman SW, Chambers CV. Compliance with universal precautions in a medical practice with a high rate of HIV infection. J Am Board Fam Pract. 1992;5(3):313-318.

References

1. Morris NP. Refusing testing during a pandemic. Am J Public Health. 2020;110(9):1354-1355. https://doi.org/10.2105/AJPH.2020.305810
2. Rubin R. First it was masks; now some refuse testing for SARS-CoV-2. JAMA. 2020;324(20):2015-2016. https://doi.org/10.1001/jama.2020.22003
3. Black JRM, Bailey C, Przewrocka J, Dijkstra KK, Swanton C. COVID-19: the case for health-care worker screening to prevent hospital transmission. Lancet. 2020;395(10234):1418-1420. https://doi.org/10.1016/S0140-6736(20)30917-X
4. McBee SM, Thomasson ED, Scott MA, et al. Notes from the field: universal statewide laboratory testing for SARS-CoV-2 in nursing homes—West Virginia, April 21–May 8, 2020. MMWR Morb Mortal Wkly Rep. 2020;69(34):1177-1179. http://dx.doi.org/10.15585/mmwr.mm6934a4
5. Long DR, Gombar S, Hogan CA, et al. Occurrence and timing of subsequent severe acute respiratory syndrome coronavirus 2 reverse-transcription polymerase chain reaction positivity among initially negative patients. Clin Infect Dis. 2021;72(2):323-326. https://doi.org/10.1093/cid/ciaa722
6. Larremore DB, Wilder B, Lester E, et al. Test sensitivity is secondary to frequency and turnaround time for COVID-19 screening. Sci Adv. 2021;7(1):eabd5393. https://advances.sciencemag.org/content/7/1/eabd5393
7. Lu AC, Burgart AM. Elective surgery and COVID-19: a framework for the untested patient. Ann Surg. 2020;272(6):e291-e295. https://doi.org/10.1097/SLA.0000000000004474
8. Podboy A, Cholankeril G, Cianfichi L, Guzman E Jr, Ahmed A, Banerjee S. Implementation and impact of universal preprocedure testing of patients for COVID-19 before endoscopy. Gastroenterology. 2020;159(4):1586-1588. https://doi.org/10.1053/j.gastro.2020.06.022
9. O’Neill O. Some limits of informed consent. J Med Ethics. 2003;29(1):4-7. https://doi.org/10.1136/jme.29.1.4
10. Will JF. A brief historical and theoretical perspective on patient autonomy and medical decision making: part II: the autonomy model. Chest. 2011;139(6):1491-1497. https://doi.org/10.1378/chest.11-0516
11. Will JF. A brief historical and theoretical perspective on patient autonomy and medical decision making: part I: the beneficence model. Chest. 2011;139(3):669-673. https://doi.org/10.1378/chest.10-2532
12. Hendrix KS, Sturm LA, Zimet GD, Meslin EM. Ethics and childhood vaccination policy in the United States. Am J Public Health. 2016;106(2):273-278. https://doi.org/10.2105/AJPH.2015.302952
13. Losina E, Leifer V, Millham L, et al. College campuses and COVID-19 mitigation: clinical and economic value. Ann Intern Med. Published online December 21, 2020. https://doi.org/10.7326/M20-6558
14. Selph SS, Bougatsos C, Dana T, Grusing S, Chou R. Screening for HIV infection in pregnant women: updated evidence report and systematic review for the US Preventive Services Task Force. JAMA. 2019;321(23):2349-2360. https://doi.org/10.1001/jama.2019.2593
15. Dranove D, White WD. Agency and the organization of health care delivery. Inquiry. 1987;24(4):405-415.
16. Huber SJ, Wynia MK. When pestilence prevails...physician responsibilities in epidemics. Am J Bioeth. 2004;4(1):W5-W11. https://www.tandfonline.com/doi/abs/10.1162/152651604773067497
17. Ruhnke GW. COVID-19 diagnostic testing and the psychology of precautions fatigue. Cleve Clin J Med. 2020;88(1):19-21. https://doi.org/10.3949/ccjm.88a.20086
18. Freeman SW, Chambers CV. Compliance with universal precautions in a medical practice with a high rate of HIV infection. J Am Board Fam Pract. 1992;5(3):313-318.

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Journal of Hospital Medicine 16(5)
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Journal of Hospital Medicine 16(5)
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314-315. Published Online First March 17, 2021
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