Hospital Medicine

Immigrant physicians and international medical graduates (IMGs) have for decades been very important to the healthcare delivery in the United States. For many currently serving on the front lines, the path has been full of challenges and uncertainties, now acutely worsened by the pandemic at hand. Manpreet Malik, MD, is one of those hospitalists. He grew up in a small city in India. He completed medical school in South India where he met students from all over the world and learned to speak a new language to serve local patients. The multicultural experience inspired him to pursue residency in the United States. Manpreet obtained a J-1 visa for residency and subsequently applied for a J-1 waiver for his first hospitalist job in 2013. Then his employer, a nonprofit organization, applied for H-1B and permanent resident status. He continues on an H-1B status but awaits his green card 7 years later. His wife, a dentist, is also an H-1B visa holder and they have two children. While they have assimilated into American society and flourished professionally, a sense of security eludes them. The COVID-19 pandemic has amplified this for their family. Like many other families, they are both in high-risk occupations and worry about the future, including what would happen if either or both of them contracted the virus. Their carefully planned life feels like a wobbly house of cards.

Immigrant healthcare workers are on the front lines in the fight against COVID-19 in the United States, accounting for 16.4% of healthcare workers amid this pandemic.¹ Of physicians in the United States, 29% are not born in the United States,and of the practicing hospitalists, 32% are IMGs.^1,2 IMGs are physicians who have graduated from medical schools outside of the United States and Canada who lack accreditation by the Liaison Committee on Medical Education.³ IMGs are a heterogeneous group with widely varying cultural, educational, and linguistic backgrounds with around 12,000 IMGs applying yearly for US residency positions.⁴ IMG hospitalists are uniquely positioned at the front lines facing arguably more risks with less recognition.⁵ The top five countries sending physicians to the United States are India, China, the Philippines, South Korea, and Pakistan.⁶ Yet many of these doctors—more than a third of those practicing in this country who graduated from international medical schools—have visa restrictions that limit their ability to work in communities with the greatest need.⁷ Another group of approximately 65,000 IMGs currently living in the United States are not licensed; they have not passed the board exam because they haven’t matched into a residency program to be eligible to take it.⁸ Many are working other jobs such as medical research, even though they could be deployed to serve as scribes or work in triage via telemedicine if their visas permitted.

During the COVID-19 pandemic, immigrant doctors are putting their lives on the line daily to care for patients. Immigrant doctors on visas are not eligible for Medicaid or Social Security benefits. Further, their partners and children are often dependent on them for legal resident status in the United States because of employer-based visa sponsorship. As the primary visa holder, if a non–US-born physician in the United States gets severely ill while fighting the virus, or gets disabled, they may have no benefits to fall back on. These physicians have houses, families, and children who are American citizens, and they are contributing members of society. Physicians on visas pay taxes the same way US citizens do. If their health or employment is jeopardized, their families would be unable to stay in the US legally, becoming undocumented and risking deportation. These physicians, who are fighting COVID-19 today, are helpless to provide a stable structure for their own loved ones.

With the COVID-19 pandemic unfolding, there is a risk of more physician shortages. The US healthcare workforce relies on immigrant physicians to help provide high-quality and accessible patient care. There are challenges for IMGs for getting into residency programs, and this limits the potential workforce during COVID-19. This year, according to the National Resident Matching Program, 4,222 non–US-born IMGs are due to start their US residency training on July 1.⁹ These doctors have the opportunity to serve across the country during this pandemic. According to data from the matching program, IMGs make up a large proportion of the workforce, obtaining 23% of the total number of US residency positions filled, and are in many leading academic institutions. These doctors, many of whom are waiting for their visas to be processed, need to be admitted in order to provide the care that Americans need during this pandemic. A similar number of IMGs will be completing their specialty training and are due to become attending physicians in their chosen field, including areas with critical shortages in this pandemic, such as critical care medicine. These skilled physicians depend on the processing of visa extensions or green cards in order to remain in the United States. Subspecialties like internal medicine and family medicine have a large proportion of actively practicing IMGs,⁷ and therefore provide primary care and inpatient care across the nation, especially in underserved areas. However, the geographic location of their practice is limited to the place that sponsored their visa. So a physician in rural Minnesota, where the outbreak of COVID-19 is not severe, cannot travel to hot spots such as New York or Detroit to provide care, even if they have a desire to serve.

For IMGs, the process of obtaining legal status in the US and pertinent immigration policies includes utilizing the H-1B visa program for highly skilled workers¹⁰ or J-1 visas for residencies.¹¹ H-1B visas are usually granted for sponsored positions in underserved or rural areas for at least 3 years, and the healthcare sector must compete with other industries, such as tech, engineering, and other specialty occupations. Physicians working on H-1B visas may apply for permanent work permits, though there is an annual cap for each country and candidates may wait decades to receive one. As a J-1 visa (cultural exchange program) holder, physicians are required to practice in their home country for 2 years prior to working again in the United States. This requirement could be waived by turning to the Conrad 30 Waiver Program¹² or J-1 waivers if they agreed to work in an underserved area in the United States. A limited number of J-1 waivers for each state are dispensed on a first-come, first-served basis (30 IMGs per state per year). This program currently is only authorized through the end of 2020, although legislation has been introduced to extend it, which could expand the slots.¹³ Applying for a J-1 waiver thus becomes a race against time with high-stakes suspense and anxiety for many IMGs. Most, regardless of visa status, dream of a stable and secure life, with permanent resident status as they serve their communities. For some, however, the endgame could mean deportation and the premature demise of dreams. 

Permanent resident status is allotted by country, and there is a long wait for green cards. Three-quarters of skilled workers waiting for green cards are from India. That translates to more than 700,000 people, of which approximately 200,000 are expected to die of old age before being granted green cards.^14,15 In the meantime, while they live with restrictions on both their employment and mobility, many physicians are doing essential medical work in underserved and rural areas throughout the United States.

We urge immigration reform to increase the physician workforce by providing immigrant doctors and IMGs with more flexibility to travel to areas where they are needed the most during this pandemic. There should be a blanket extension of visa deadlines. IMGs on J-1 student visas and H-1B specialty work visas should be exempt from any future immigration bans or limitations during the COVID-19 pandemic. The time is right for accelerating permanent resident status for these highly skilled IMGs. Green cards soon after finishing residency or fellowship training or satisfying a condition of initial visa approval should be the norm instead of a stressful unending wait. Clinicians who serve in underserved communities should be incentivized, and this should include health benefits. Restrictions related to primary and secondary work sites, as well as number of J-1 waivers, should also be relaxed. This flexibility would allow immigrant physicians to care at a variety of locations or by means of telemedicine.

A physician’s role is to heal and to serve their patients, regardless of their own origin. We are the voices of America’s immigrant physicians, particularly hospitalists, serving as frontline workers in our nation’s response to the COVID-19 crisis. The battle against COVID-19 has strained many of our resources, including the need for physicians. Uncertainty and chaos reign professionally and personally for many healthcare workers across America, and more challenges lie ahead for the foreseeable future. Healthcare workers are the unselfish and unwavering wall that stands between COVID-19 and more lives lost in our country. Every effort should be made to preserve and strengthen the healthcare workforce. Immigrant hospitalists, shackled by visa restrictions, could play an even bigger role if their obstacles were removed. It is time to provide them with the sense of security they deserve and rebuild the house of cards into something with a stronger foundation and more stability for our future.

Immigrant physicians and international medical graduates (IMGs) have for decades been very important to the healthcare delivery in the United States. For many currently serving on the front lines, the path has been full of challenges and uncertainties, now acutely worsened by the pandemic at hand. Manpreet Malik, MD, is one of those hospitalists. He grew up in a small city in India. He completed medical school in South India where he met students from all over the world and learned to speak a new language to serve local patients. The multicultural experience inspired him to pursue residency in the United States. Manpreet obtained a J-1 visa for residency and subsequently applied for a J-1 waiver for his first hospitalist job in 2013. Then his employer, a nonprofit organization, applied for H-1B and permanent resident status. He continues on an H-1B status but awaits his green card 7 years later. His wife, a dentist, is also an H-1B visa holder and they have two children. While they have assimilated into American society and flourished professionally, a sense of security eludes them. The COVID-19 pandemic has amplified this for their family. Like many other families, they are both in high-risk occupations and worry about the future, including what would happen if either or both of them contracted the virus. Their carefully planned life feels like a wobbly house of cards.

Immigrant healthcare workers are on the front lines in the fight against COVID-19 in the United States, accounting for 16.4% of healthcare workers amid this pandemic.¹ Of physicians in the United States, 29% are not born in the United States,and of the practicing hospitalists, 32% are IMGs.^1,2 IMGs are physicians who have graduated from medical schools outside of the United States and Canada who lack accreditation by the Liaison Committee on Medical Education.³ IMGs are a heterogeneous group with widely varying cultural, educational, and linguistic backgrounds with around 12,000 IMGs applying yearly for US residency positions.⁴ IMG hospitalists are uniquely positioned at the front lines facing arguably more risks with less recognition.⁵ The top five countries sending physicians to the United States are India, China, the Philippines, South Korea, and Pakistan.⁶ Yet many of these doctors—more than a third of those practicing in this country who graduated from international medical schools—have visa restrictions that limit their ability to work in communities with the greatest need.⁷ Another group of approximately 65,000 IMGs currently living in the United States are not licensed; they have not passed the board exam because they haven’t matched into a residency program to be eligible to take it.⁸ Many are working other jobs such as medical research, even though they could be deployed to serve as scribes or work in triage via telemedicine if their visas permitted.

During the COVID-19 pandemic, immigrant doctors are putting their lives on the line daily to care for patients. Immigrant doctors on visas are not eligible for Medicaid or Social Security benefits. Further, their partners and children are often dependent on them for legal resident status in the United States because of employer-based visa sponsorship. As the primary visa holder, if a non–US-born physician in the United States gets severely ill while fighting the virus, or gets disabled, they may have no benefits to fall back on. These physicians have houses, families, and children who are American citizens, and they are contributing members of society. Physicians on visas pay taxes the same way US citizens do. If their health or employment is jeopardized, their families would be unable to stay in the US legally, becoming undocumented and risking deportation. These physicians, who are fighting COVID-19 today, are helpless to provide a stable structure for their own loved ones.

With the COVID-19 pandemic unfolding, there is a risk of more physician shortages. The US healthcare workforce relies on immigrant physicians to help provide high-quality and accessible patient care. There are challenges for IMGs for getting into residency programs, and this limits the potential workforce during COVID-19. This year, according to the National Resident Matching Program, 4,222 non–US-born IMGs are due to start their US residency training on July 1.⁹ These doctors have the opportunity to serve across the country during this pandemic. According to data from the matching program, IMGs make up a large proportion of the workforce, obtaining 23% of the total number of US residency positions filled, and are in many leading academic institutions. These doctors, many of whom are waiting for their visas to be processed, need to be admitted in order to provide the care that Americans need during this pandemic. A similar number of IMGs will be completing their specialty training and are due to become attending physicians in their chosen field, including areas with critical shortages in this pandemic, such as critical care medicine. These skilled physicians depend on the processing of visa extensions or green cards in order to remain in the United States. Subspecialties like internal medicine and family medicine have a large proportion of actively practicing IMGs,⁷ and therefore provide primary care and inpatient care across the nation, especially in underserved areas. However, the geographic location of their practice is limited to the place that sponsored their visa. So a physician in rural Minnesota, where the outbreak of COVID-19 is not severe, cannot travel to hot spots such as New York or Detroit to provide care, even if they have a desire to serve.

For IMGs, the process of obtaining legal status in the US and pertinent immigration policies includes utilizing the H-1B visa program for highly skilled workers¹⁰ or J-1 visas for residencies.¹¹ H-1B visas are usually granted for sponsored positions in underserved or rural areas for at least 3 years, and the healthcare sector must compete with other industries, such as tech, engineering, and other specialty occupations. Physicians working on H-1B visas may apply for permanent work permits, though there is an annual cap for each country and candidates may wait decades to receive one. As a J-1 visa (cultural exchange program) holder, physicians are required to practice in their home country for 2 years prior to working again in the United States. This requirement could be waived by turning to the Conrad 30 Waiver Program¹² or J-1 waivers if they agreed to work in an underserved area in the United States. A limited number of J-1 waivers for each state are dispensed on a first-come, first-served basis (30 IMGs per state per year). This program currently is only authorized through the end of 2020, although legislation has been introduced to extend it, which could expand the slots.¹³ Applying for a J-1 waiver thus becomes a race against time with high-stakes suspense and anxiety for many IMGs. Most, regardless of visa status, dream of a stable and secure life, with permanent resident status as they serve their communities. For some, however, the endgame could mean deportation and the premature demise of dreams. 

Permanent resident status is allotted by country, and there is a long wait for green cards. Three-quarters of skilled workers waiting for green cards are from India. That translates to more than 700,000 people, of which approximately 200,000 are expected to die of old age before being granted green cards.^14,15 In the meantime, while they live with restrictions on both their employment and mobility, many physicians are doing essential medical work in underserved and rural areas throughout the United States.

We urge immigration reform to increase the physician workforce by providing immigrant doctors and IMGs with more flexibility to travel to areas where they are needed the most during this pandemic. There should be a blanket extension of visa deadlines. IMGs on J-1 student visas and H-1B specialty work visas should be exempt from any future immigration bans or limitations during the COVID-19 pandemic. The time is right for accelerating permanent resident status for these highly skilled IMGs. Green cards soon after finishing residency or fellowship training or satisfying a condition of initial visa approval should be the norm instead of a stressful unending wait. Clinicians who serve in underserved communities should be incentivized, and this should include health benefits. Restrictions related to primary and secondary work sites, as well as number of J-1 waivers, should also be relaxed. This flexibility would allow immigrant physicians to care at a variety of locations or by means of telemedicine.

A physician’s role is to heal and to serve their patients, regardless of their own origin. We are the voices of America’s immigrant physicians, particularly hospitalists, serving as frontline workers in our nation’s response to the COVID-19 crisis. The battle against COVID-19 has strained many of our resources, including the need for physicians. Uncertainty and chaos reign professionally and personally for many healthcare workers across America, and more challenges lie ahead for the foreseeable future. Healthcare workers are the unselfish and unwavering wall that stands between COVID-19 and more lives lost in our country. Every effort should be made to preserve and strengthen the healthcare workforce. Immigrant hospitalists, shackled by visa restrictions, could play an even bigger role if their obstacles were removed. It is time to provide them with the sense of security they deserve and rebuild the house of cards into something with a stronger foundation and more stability for our future.

Immigrant physicians and international medical graduates (IMGs) have for decades been very important to the healthcare delivery in the United States. For many currently serving on the front lines, the path has been full of challenges and uncertainties, now acutely worsened by the pandemic at hand. Manpreet Malik, MD, is one of those hospitalists. He grew up in a small city in India. He completed medical school in South India where he met students from all over the world and learned to speak a new language to serve local patients. The multicultural experience inspired him to pursue residency in the United States. Manpreet obtained a J-1 visa for residency and subsequently applied for a J-1 waiver for his first hospitalist job in 2013. Then his employer, a nonprofit organization, applied for H-1B and permanent resident status. He continues on an H-1B status but awaits his green card 7 years later. His wife, a dentist, is also an H-1B visa holder and they have two children. While they have assimilated into American society and flourished professionally, a sense of security eludes them. The COVID-19 pandemic has amplified this for their family. Like many other families, they are both in high-risk occupations and worry about the future, including what would happen if either or both of them contracted the virus. Their carefully planned life feels like a wobbly house of cards.

Immigrant healthcare workers are on the front lines in the fight against COVID-19 in the United States, accounting for 16.4% of healthcare workers amid this pandemic.¹ Of physicians in the United States, 29% are not born in the United States,and of the practicing hospitalists, 32% are IMGs.^1,2 IMGs are physicians who have graduated from medical schools outside of the United States and Canada who lack accreditation by the Liaison Committee on Medical Education.³ IMGs are a heterogeneous group with widely varying cultural, educational, and linguistic backgrounds with around 12,000 IMGs applying yearly for US residency positions.⁴ IMG hospitalists are uniquely positioned at the front lines facing arguably more risks with less recognition.⁵ The top five countries sending physicians to the United States are India, China, the Philippines, South Korea, and Pakistan.⁶ Yet many of these doctors—more than a third of those practicing in this country who graduated from international medical schools—have visa restrictions that limit their ability to work in communities with the greatest need.⁷ Another group of approximately 65,000 IMGs currently living in the United States are not licensed; they have not passed the board exam because they haven’t matched into a residency program to be eligible to take it.⁸ Many are working other jobs such as medical research, even though they could be deployed to serve as scribes or work in triage via telemedicine if their visas permitted.

During the COVID-19 pandemic, immigrant doctors are putting their lives on the line daily to care for patients. Immigrant doctors on visas are not eligible for Medicaid or Social Security benefits. Further, their partners and children are often dependent on them for legal resident status in the United States because of employer-based visa sponsorship. As the primary visa holder, if a non–US-born physician in the United States gets severely ill while fighting the virus, or gets disabled, they may have no benefits to fall back on. These physicians have houses, families, and children who are American citizens, and they are contributing members of society. Physicians on visas pay taxes the same way US citizens do. If their health or employment is jeopardized, their families would be unable to stay in the US legally, becoming undocumented and risking deportation. These physicians, who are fighting COVID-19 today, are helpless to provide a stable structure for their own loved ones.

With the COVID-19 pandemic unfolding, there is a risk of more physician shortages. The US healthcare workforce relies on immigrant physicians to help provide high-quality and accessible patient care. There are challenges for IMGs for getting into residency programs, and this limits the potential workforce during COVID-19. This year, according to the National Resident Matching Program, 4,222 non–US-born IMGs are due to start their US residency training on July 1.⁹ These doctors have the opportunity to serve across the country during this pandemic. According to data from the matching program, IMGs make up a large proportion of the workforce, obtaining 23% of the total number of US residency positions filled, and are in many leading academic institutions. These doctors, many of whom are waiting for their visas to be processed, need to be admitted in order to provide the care that Americans need during this pandemic. A similar number of IMGs will be completing their specialty training and are due to become attending physicians in their chosen field, including areas with critical shortages in this pandemic, such as critical care medicine. These skilled physicians depend on the processing of visa extensions or green cards in order to remain in the United States. Subspecialties like internal medicine and family medicine have a large proportion of actively practicing IMGs,⁷ and therefore provide primary care and inpatient care across the nation, especially in underserved areas. However, the geographic location of their practice is limited to the place that sponsored their visa. So a physician in rural Minnesota, where the outbreak of COVID-19 is not severe, cannot travel to hot spots such as New York or Detroit to provide care, even if they have a desire to serve.

For IMGs, the process of obtaining legal status in the US and pertinent immigration policies includes utilizing the H-1B visa program for highly skilled workers¹⁰ or J-1 visas for residencies.¹¹ H-1B visas are usually granted for sponsored positions in underserved or rural areas for at least 3 years, and the healthcare sector must compete with other industries, such as tech, engineering, and other specialty occupations. Physicians working on H-1B visas may apply for permanent work permits, though there is an annual cap for each country and candidates may wait decades to receive one. As a J-1 visa (cultural exchange program) holder, physicians are required to practice in their home country for 2 years prior to working again in the United States. This requirement could be waived by turning to the Conrad 30 Waiver Program¹² or J-1 waivers if they agreed to work in an underserved area in the United States. A limited number of J-1 waivers for each state are dispensed on a first-come, first-served basis (30 IMGs per state per year). This program currently is only authorized through the end of 2020, although legislation has been introduced to extend it, which could expand the slots.¹³ Applying for a J-1 waiver thus becomes a race against time with high-stakes suspense and anxiety for many IMGs. Most, regardless of visa status, dream of a stable and secure life, with permanent resident status as they serve their communities. For some, however, the endgame could mean deportation and the premature demise of dreams. 

Permanent resident status is allotted by country, and there is a long wait for green cards. Three-quarters of skilled workers waiting for green cards are from India. That translates to more than 700,000 people, of which approximately 200,000 are expected to die of old age before being granted green cards.^14,15 In the meantime, while they live with restrictions on both their employment and mobility, many physicians are doing essential medical work in underserved and rural areas throughout the United States.

We urge immigration reform to increase the physician workforce by providing immigrant doctors and IMGs with more flexibility to travel to areas where they are needed the most during this pandemic. There should be a blanket extension of visa deadlines. IMGs on J-1 student visas and H-1B specialty work visas should be exempt from any future immigration bans or limitations during the COVID-19 pandemic. The time is right for accelerating permanent resident status for these highly skilled IMGs. Green cards soon after finishing residency or fellowship training or satisfying a condition of initial visa approval should be the norm instead of a stressful unending wait. Clinicians who serve in underserved communities should be incentivized, and this should include health benefits. Restrictions related to primary and secondary work sites, as well as number of J-1 waivers, should also be relaxed. This flexibility would allow immigrant physicians to care at a variety of locations or by means of telemedicine.

A physician’s role is to heal and to serve their patients, regardless of their own origin. We are the voices of America’s immigrant physicians, particularly hospitalists, serving as frontline workers in our nation’s response to the COVID-19 crisis. The battle against COVID-19 has strained many of our resources, including the need for physicians. Uncertainty and chaos reign professionally and personally for many healthcare workers across America, and more challenges lie ahead for the foreseeable future. Healthcare workers are the unselfish and unwavering wall that stands between COVID-19 and more lives lost in our country. Every effort should be made to preserve and strengthen the healthcare workforce. Immigrant hospitalists, shackled by visa restrictions, could play an even bigger role if their obstacles were removed. It is time to provide them with the sense of security they deserve and rebuild the house of cards into something with a stronger foundation and more stability for our future.

The coronavirus disease of 2019 (COVID-19) pandemic has resulted in a surge in hospitalizations of patients with a novel, serious, and highly contagious infectious disease for which there is yet no proven treatment. Currently, much of the focus has been on intensive care unit (ICU) and ventilator capacity for the sickest of these patients who develop respiratory failure. However, most hospitalized patients are being cared for in general medical units.¹ Some evidence exists to describe adaptations to capacity needs outside of medical wards,^2-4 but few studies have specifically addressed the ward setting. Therefore, there is a pressing need for evidence to describe how to expand capacity and deliver medical ward–based care.

To better understand how inpatient care in the United States is adapting to the COVID-19 pandemic, we surveyed 72 sites participating in the Hospital Medicine Reengineering Network (HOMERuN), a national consortium of hospital medicine groups.⁵ We report results of this survey, carried out between April 3 and April 5, 2020.

Sites and Subjects

HOMERuN is a collaborative network of hospitalists from across the United States whose primary goal is to catalyze research and share best practices across hospital medicine groups. Using surveys of Hospital Medicine leaders, targeted medical record review, and other methods, HOMERuN’s funded research interests to date have included care transitions, workforce issues, patient and family engagement, and diagnostic errors. Sites participating in HOMERuN sites are relatively large urban academic medical centers (Appendix).

Survey Development and Deployment

We designed a focused survey that aimed to provide a snapshot of evolving operational and clinical aspects of COVID-19 care (Appendix). Domains included COVID-19 testing turnaround times, personal protective equipment (PPE) stewardship,⁶ features of respiratory isolation units (RIUs; ie, dedicated units for patients with known or suspected COVID-19), and observed effects on clinical care. We tested the instrument to ensure feasibility and clarity internally, performed brief cognitive testing with several hospital medicine leaders in HOMERuN, then disseminated the survey by email on April 3, with two follow-up emails on 2 subsequent days. Our study was deemed non–human subjects research by the University of California, San Francisco, Committee on Human Research. Descriptive statistics were used to characterize survey responses.

Of 72 hospitals surveyed, 51 (71%) responded. Mean hospital bed count was 940, three were safety-net hospitals, and one was a community-based teaching center; responding and nonresponding hospitals did not differ significantly in terms of bed count (Appendix).

Health System Adaptations, Testing, and PPE Status

Nearly all responding hospitals (46 of 51; 90%) had RIUs for patients with known or suspected COVID-19 (Table 1). Nearly all hospitals took steps to keep potentially sick healthcare providers from infecting others (eg, staying home if sick or exposed). Among respondents, 32% had rapid response teams, 24% had respiratory therapy teams, and 29% had case management teams that were dedicated to COVID-19 care. Thirty-two (63%) had developed models, such as ethics or palliative care consult services, to assist with difficult resource-allocation decisions (eg, how to prioritize ventilator use if demand exceeded supply). Twenty-three (45%) had developed post-acute care monitoring programs dedicated to COVID-19 patients.

At the time of our survey, only 2 sites (4%) reported COVID-19 test time turnaround under 1 hour, and 15 (30%) reported turnaround in less than 6 hours. Of the 29 sites able to provide estimates of PPE stockpile, 14 (48%) reported a supply of 2 weeks or less. The most common approaches to PPE stewardship focused on reuse of masks and face shields if not obviously soiled, centralizing PPE distribution, and disinfecting or sterilizing masks. Ten sites (20%) were utilizing 3-D printed masks, while 10% used homemade face shields or masks.

Characteristics of COVID-19 RIUs

Forty-six hospitals (90% of all respondents) in our cohort had developed RIUs at the time of survey administration. The earliest RIU implementation date was February 10, 2020, and the most recent was launched on the day of our survey. Admission to RIUs was primarily based on clinical factors associated with known or suspected COVID-19 infection (Table 2). The number of non–critical care RIU beds among locations at that time ranged from 10 or less to more than 50. The mean number of hospitalist attendings caring for patients in the RIUs was 10.2, with a mean 4.1 advanced practice providers, 5.5 residents, and 0 medical students. The number of planned patients per attending was typically 5 to 15. Nurses and physicians typically rounded separately. Medical distancing (eg, reducing patient room entry) was accomplished most commonly by grouped timing of medication administration (76% of sites), video links to room outside of rounding times (54% of sites), the use of video or telemedicine during rounds (17%), and clustering of activities such as medication administration or phlebotomy. The most common criteria prompting discharge from the RIU were a negative COVID-19 test (59%) and hospital discharge (57%), though comments from many respondents suggested that discharge criteria were changing rapidly.

Effects of Isolation Measures on In-Room Encounters and Diagnostic Processes

More than 90% of sites reported decreases in in-room encounter frequency across all provider types whether as a result of policies in place or not. Reductions were reported among hospitalists, advanced practice providers, residents, consultants, and therapists (Table 3). Reduced room entry most often resulted from an established or developing policy, but many noted reduced room entry without formal policies in place. Nearly all sites reported moving specialty consultations to phone or video evaluations. Diagnostic error was commonly reported, with missed non–COVID-19 medical diagnoses among COVID-19 infected patients being reported by 22 sites (46%) and missed COVID-19 diagnoses in patients admitted for other reasons by 22 sites (45%).

In this study of medical wards at academic medical centers, we found that, in response to the COVID-19 pandemic, hospitals made several changes in a short period of time to adapt to the crisis. These included implementation and rapid expansion of dedicated RIUs, greatly expanded use of inpatient telehealth for patient assessments and consultation, implementation of other approaches to minimize room entry (such as grouping in-room activities), and deployment of ethics consultation services to help manage issues around potential scarcity of life-saving measures such as ventilators. We also found that availability of PPE and timely testing was limited. Finally, a large proportion of sites reported potential diagnostic problems in the assessment of both patients suspected and those not suspected of having COVID-19.

RIUs are emerging as a primary modality for caring for non-ICU COVID-19 patients, though they never involved medical students; we hope the role of students in particular will increase as new models of training emerge in response to the pandemic.⁷ In contrast, telemedicine evolved rapidly to hold a substantial role in RIUs, with both ward and specialty teams using video visit technology to communicate with patients. COVID-19 has been viewed as a perfect use case for outpatient telemedicine,⁸ and a growing number of studies are examining its outpatient use^9,10; however, to date, somewhat less attention has been paid to inpatient deployment. Although our data suggest telemedicine has found a prominent place in RIUs, it remains to be seen whether it is associated with differences in patient or provider outcomes. For example, deficiencies in the physical examination, limited face-to-face contact, and lack of physical presence could all affect the patient–provider relationship, patient engagement, and the accuracy of the diagnostic process.

Our data suggest the possibility of missing non–COVID-19 diagnoses in patients suspected of COVID-19 and missing COVID-19 in those admitted for nonrespiratory reasons. The latter may be addressed as routine COVID-19 screening of admitted patients becomes commonplace. For the former, however, it is possible that physicians are “anchoring” their thinking on COVID-19 to the exclusion of other diagnoses, that physicians are not fully aware of complications unique to COVID-19 infection (such as thromboembolism), and/or that the above-mentioned limitations of telemedicine have decreased diagnostic performance.

Although PPE stockpile data were not easily available for some sites, a distressingly large number reported stockpiles of 2 weeks or less, with reuse being the most common approach to extending PPE supply. We also found it concerning that 43% of hospital leaders did not know their stockpile data; we believe this is an important question that hospital leaders need to be asking. Most sites in our study reported test turnaround times of longer than 6 hours; lack of rapid COVID-19 testing further stresses PPE stockpile and may slow patients’ transition out of the RIU or discharge to home.

Our study has several limitations, including the evolving nature of the pandemic and rapid adaptations of care systems in the pandemic’s surge phase. However, we attempted to frame our questions in ways that provided a focused snapshot of care. Furthermore, respondents may not have had exhaustive knowledge of their institution’s COVID-19 response strategies, but most were the directors of their hospitalist services, and we encouraged the respondents to confer with others to gather high-fidelity data. Finally, as a survey of large academic medical centers, our results may not apply to nonacademic centers.

Approaches to caring for non-ICU patients during the COVID-19 pandemic are rapidly evolving. Expansion of RIUs and developing the workforce to support them has been a primary focus, with rapid innovation in use of technology emerging as a critical adaptation while PPE limitations persist and needs for “medical distancing” continue to grow. Although rates of missed COVID-19 diagnoses will likely be reduced with testing and systems improvements, physicians and systems will also need to consider how to utilize emerging technology in ways that can improve clinical care and provider safety while aiding diagnostic thinking. This survey illustrates the rapid adaptations made by our hospitals in response to the pandemic; ongoing adaptation will likely be needed to optimally care for hospitalized patients with COVID-19 while the pandemic continues to evolve.

Thanks to members of the HOMERuN COVID-19 Collaborative Group: Baylor Scott & White Medical Center – Temple, Texas - Tresa McNeal MD; Beth Israel Deaconess Medical Center - Shani Herzig MD MPH, Joseph Li MD, Julius Yang MD PhD; Brigham and Women’s Hospital - Christopher Roy MD, Jeffrey Schnipper MD MPH; Cedars-Sinai Medical Center - Ed Seferian MD, ; ChristianaCare - Surekha Bhamidipati MD; Cleveland Clinic - Matthew Pappas MD MPH; Dartmouth-Hitchcock Medical Center - Jonathan Lurie MD MS; Dell Medical School at The University of Texas at Austin - Chris Moriates MD, Luci Leykum MD MBA MSc; Denver Health and Hospitals Authority - Diana Mancini MD; Emory University Hospital - Dan Hunt MD; Johns Hopkins Hospital - Daniel J Brotman MD, Zishan K Siddiqui MD, Shaker Eid MD MBA; Maine Medical Center - Daniel A Meyer MD, Robert Trowbridge MD; Massachusetts General Hospital - Melissa Mattison MD; Mayo Clinic Rochester – Caroline Burton MD, Sagar Dugani MD PhD; Medical College of Wisconsin - Sanjay Bhandari MD; Miriam Hospital - Kwame Dapaah-Afriyie MD MBA; Mount Sinai Hospital - Andrew Dunn MD; NorthShore - David Lovinger MD; Northwestern Memorial Hospital - Kevin O’Leary MD MS; Ohio State University Wexner Medical Center - Eric Schumacher DO; Oregon Health & Science University - Angela Alday MD; Penn Medicine - Ryan Greysen MD MHS MA; Rutgers- Robert Wood Johnson University Hospital - Michael Steinberg MD MPH; Stanford University School of Medicine - Neera Ahuja MD; Tulane Hospital and University Medical Center - Geraldine Ménard MD; UC San Diego Health - Ian Jenkins MD; UC Los Angeles Health - Michael Lazarus MD, Magdalena E. Ptaszny, MD; UC San Francisco Health - Bradley A Sharpe, MD, Margaret Fang MD MPH; UK HealthCare - Mark Williams MD MHM, John Romond MD; University of Chicago – David Meltzer MD PhD, Gregory Ruhnke MD; University of Colorado - Marisha Burden MD; University of Florida - Nila Radhakrishnan MD; University of Iowa Hospitals and Clinics - Kevin Glenn MD MS; University of Miami - Efren Manjarrez MD; University of Michigan - Vineet Chopra MD MSc, Valerie Vaughn MD MSc; University of Missouri-Columbia Hospital - Hasan Naqvi MD; University of Nebraska Medical Center - Chad Vokoun MD; University of North Carolina at Chapel Hill - David Hemsey MD; University of Pittsburgh Medical Center - Gena Marie Walker MD; University of Vermont Medical Center - Steven Grant MD; University of Washington Medical Center - Christopher Kim MD MBA, Andrew White MD; University of Washington-Harborview Medical Center - Maralyssa Bann MD; University of Wisconsin Hospital and Clinics - David Sterken MD, Farah Kaiksow MD MPP, Ann Sheehy MD MS, Jordan Kenik MD MPH; UW Northwest Campus - Ben Wolpaw MD; Vanderbilt University Medical Center - Sunil Kripalani MD MSc, Eduard E Vasilevskis MD, Kathleene T Wooldridge MD MPH; Wake Forest Baptist Health - Erik Summers MD; Washington University St. Louis - Michael Lin MD; Weill Cornell - Justin Choi MD; Yale New Haven Hospital - William Cushing MA, Chris Sankey MD; Zuckerberg San Francisco General Hospital - Sumant Ranji MD.

The coronavirus disease of 2019 (COVID-19) pandemic has resulted in a surge in hospitalizations of patients with a novel, serious, and highly contagious infectious disease for which there is yet no proven treatment. Currently, much of the focus has been on intensive care unit (ICU) and ventilator capacity for the sickest of these patients who develop respiratory failure. However, most hospitalized patients are being cared for in general medical units.¹ Some evidence exists to describe adaptations to capacity needs outside of medical wards,^2-4 but few studies have specifically addressed the ward setting. Therefore, there is a pressing need for evidence to describe how to expand capacity and deliver medical ward–based care.

To better understand how inpatient care in the United States is adapting to the COVID-19 pandemic, we surveyed 72 sites participating in the Hospital Medicine Reengineering Network (HOMERuN), a national consortium of hospital medicine groups.⁵ We report results of this survey, carried out between April 3 and April 5, 2020.

Sites and Subjects

HOMERuN is a collaborative network of hospitalists from across the United States whose primary goal is to catalyze research and share best practices across hospital medicine groups. Using surveys of Hospital Medicine leaders, targeted medical record review, and other methods, HOMERuN’s funded research interests to date have included care transitions, workforce issues, patient and family engagement, and diagnostic errors. Sites participating in HOMERuN sites are relatively large urban academic medical centers (Appendix).

Survey Development and Deployment

We designed a focused survey that aimed to provide a snapshot of evolving operational and clinical aspects of COVID-19 care (Appendix). Domains included COVID-19 testing turnaround times, personal protective equipment (PPE) stewardship,⁶ features of respiratory isolation units (RIUs; ie, dedicated units for patients with known or suspected COVID-19), and observed effects on clinical care. We tested the instrument to ensure feasibility and clarity internally, performed brief cognitive testing with several hospital medicine leaders in HOMERuN, then disseminated the survey by email on April 3, with two follow-up emails on 2 subsequent days. Our study was deemed non–human subjects research by the University of California, San Francisco, Committee on Human Research. Descriptive statistics were used to characterize survey responses.

Of 72 hospitals surveyed, 51 (71%) responded. Mean hospital bed count was 940, three were safety-net hospitals, and one was a community-based teaching center; responding and nonresponding hospitals did not differ significantly in terms of bed count (Appendix).

Health System Adaptations, Testing, and PPE Status

Nearly all responding hospitals (46 of 51; 90%) had RIUs for patients with known or suspected COVID-19 (Table 1). Nearly all hospitals took steps to keep potentially sick healthcare providers from infecting others (eg, staying home if sick or exposed). Among respondents, 32% had rapid response teams, 24% had respiratory therapy teams, and 29% had case management teams that were dedicated to COVID-19 care. Thirty-two (63%) had developed models, such as ethics or palliative care consult services, to assist with difficult resource-allocation decisions (eg, how to prioritize ventilator use if demand exceeded supply). Twenty-three (45%) had developed post-acute care monitoring programs dedicated to COVID-19 patients.

At the time of our survey, only 2 sites (4%) reported COVID-19 test time turnaround under 1 hour, and 15 (30%) reported turnaround in less than 6 hours. Of the 29 sites able to provide estimates of PPE stockpile, 14 (48%) reported a supply of 2 weeks or less. The most common approaches to PPE stewardship focused on reuse of masks and face shields if not obviously soiled, centralizing PPE distribution, and disinfecting or sterilizing masks. Ten sites (20%) were utilizing 3-D printed masks, while 10% used homemade face shields or masks.

Characteristics of COVID-19 RIUs

Forty-six hospitals (90% of all respondents) in our cohort had developed RIUs at the time of survey administration. The earliest RIU implementation date was February 10, 2020, and the most recent was launched on the day of our survey. Admission to RIUs was primarily based on clinical factors associated with known or suspected COVID-19 infection (Table 2). The number of non–critical care RIU beds among locations at that time ranged from 10 or less to more than 50. The mean number of hospitalist attendings caring for patients in the RIUs was 10.2, with a mean 4.1 advanced practice providers, 5.5 residents, and 0 medical students. The number of planned patients per attending was typically 5 to 15. Nurses and physicians typically rounded separately. Medical distancing (eg, reducing patient room entry) was accomplished most commonly by grouped timing of medication administration (76% of sites), video links to room outside of rounding times (54% of sites), the use of video or telemedicine during rounds (17%), and clustering of activities such as medication administration or phlebotomy. The most common criteria prompting discharge from the RIU were a negative COVID-19 test (59%) and hospital discharge (57%), though comments from many respondents suggested that discharge criteria were changing rapidly.

Effects of Isolation Measures on In-Room Encounters and Diagnostic Processes

More than 90% of sites reported decreases in in-room encounter frequency across all provider types whether as a result of policies in place or not. Reductions were reported among hospitalists, advanced practice providers, residents, consultants, and therapists (Table 3). Reduced room entry most often resulted from an established or developing policy, but many noted reduced room entry without formal policies in place. Nearly all sites reported moving specialty consultations to phone or video evaluations. Diagnostic error was commonly reported, with missed non–COVID-19 medical diagnoses among COVID-19 infected patients being reported by 22 sites (46%) and missed COVID-19 diagnoses in patients admitted for other reasons by 22 sites (45%).

In this study of medical wards at academic medical centers, we found that, in response to the COVID-19 pandemic, hospitals made several changes in a short period of time to adapt to the crisis. These included implementation and rapid expansion of dedicated RIUs, greatly expanded use of inpatient telehealth for patient assessments and consultation, implementation of other approaches to minimize room entry (such as grouping in-room activities), and deployment of ethics consultation services to help manage issues around potential scarcity of life-saving measures such as ventilators. We also found that availability of PPE and timely testing was limited. Finally, a large proportion of sites reported potential diagnostic problems in the assessment of both patients suspected and those not suspected of having COVID-19.

RIUs are emerging as a primary modality for caring for non-ICU COVID-19 patients, though they never involved medical students; we hope the role of students in particular will increase as new models of training emerge in response to the pandemic.⁷ In contrast, telemedicine evolved rapidly to hold a substantial role in RIUs, with both ward and specialty teams using video visit technology to communicate with patients. COVID-19 has been viewed as a perfect use case for outpatient telemedicine,⁸ and a growing number of studies are examining its outpatient use^9,10; however, to date, somewhat less attention has been paid to inpatient deployment. Although our data suggest telemedicine has found a prominent place in RIUs, it remains to be seen whether it is associated with differences in patient or provider outcomes. For example, deficiencies in the physical examination, limited face-to-face contact, and lack of physical presence could all affect the patient–provider relationship, patient engagement, and the accuracy of the diagnostic process.

Our data suggest the possibility of missing non–COVID-19 diagnoses in patients suspected of COVID-19 and missing COVID-19 in those admitted for nonrespiratory reasons. The latter may be addressed as routine COVID-19 screening of admitted patients becomes commonplace. For the former, however, it is possible that physicians are “anchoring” their thinking on COVID-19 to the exclusion of other diagnoses, that physicians are not fully aware of complications unique to COVID-19 infection (such as thromboembolism), and/or that the above-mentioned limitations of telemedicine have decreased diagnostic performance.

Although PPE stockpile data were not easily available for some sites, a distressingly large number reported stockpiles of 2 weeks or less, with reuse being the most common approach to extending PPE supply. We also found it concerning that 43% of hospital leaders did not know their stockpile data; we believe this is an important question that hospital leaders need to be asking. Most sites in our study reported test turnaround times of longer than 6 hours; lack of rapid COVID-19 testing further stresses PPE stockpile and may slow patients’ transition out of the RIU or discharge to home.

Our study has several limitations, including the evolving nature of the pandemic and rapid adaptations of care systems in the pandemic’s surge phase. However, we attempted to frame our questions in ways that provided a focused snapshot of care. Furthermore, respondents may not have had exhaustive knowledge of their institution’s COVID-19 response strategies, but most were the directors of their hospitalist services, and we encouraged the respondents to confer with others to gather high-fidelity data. Finally, as a survey of large academic medical centers, our results may not apply to nonacademic centers.

Approaches to caring for non-ICU patients during the COVID-19 pandemic are rapidly evolving. Expansion of RIUs and developing the workforce to support them has been a primary focus, with rapid innovation in use of technology emerging as a critical adaptation while PPE limitations persist and needs for “medical distancing” continue to grow. Although rates of missed COVID-19 diagnoses will likely be reduced with testing and systems improvements, physicians and systems will also need to consider how to utilize emerging technology in ways that can improve clinical care and provider safety while aiding diagnostic thinking. This survey illustrates the rapid adaptations made by our hospitals in response to the pandemic; ongoing adaptation will likely be needed to optimally care for hospitalized patients with COVID-19 while the pandemic continues to evolve.

Thanks to members of the HOMERuN COVID-19 Collaborative Group: Baylor Scott & White Medical Center – Temple, Texas - Tresa McNeal MD; Beth Israel Deaconess Medical Center - Shani Herzig MD MPH, Joseph Li MD, Julius Yang MD PhD; Brigham and Women’s Hospital - Christopher Roy MD, Jeffrey Schnipper MD MPH; Cedars-Sinai Medical Center - Ed Seferian MD, ; ChristianaCare - Surekha Bhamidipati MD; Cleveland Clinic - Matthew Pappas MD MPH; Dartmouth-Hitchcock Medical Center - Jonathan Lurie MD MS; Dell Medical School at The University of Texas at Austin - Chris Moriates MD, Luci Leykum MD MBA MSc; Denver Health and Hospitals Authority - Diana Mancini MD; Emory University Hospital - Dan Hunt MD; Johns Hopkins Hospital - Daniel J Brotman MD, Zishan K Siddiqui MD, Shaker Eid MD MBA; Maine Medical Center - Daniel A Meyer MD, Robert Trowbridge MD; Massachusetts General Hospital - Melissa Mattison MD; Mayo Clinic Rochester – Caroline Burton MD, Sagar Dugani MD PhD; Medical College of Wisconsin - Sanjay Bhandari MD; Miriam Hospital - Kwame Dapaah-Afriyie MD MBA; Mount Sinai Hospital - Andrew Dunn MD; NorthShore - David Lovinger MD; Northwestern Memorial Hospital - Kevin O’Leary MD MS; Ohio State University Wexner Medical Center - Eric Schumacher DO; Oregon Health & Science University - Angela Alday MD; Penn Medicine - Ryan Greysen MD MHS MA; Rutgers- Robert Wood Johnson University Hospital - Michael Steinberg MD MPH; Stanford University School of Medicine - Neera Ahuja MD; Tulane Hospital and University Medical Center - Geraldine Ménard MD; UC San Diego Health - Ian Jenkins MD; UC Los Angeles Health - Michael Lazarus MD, Magdalena E. Ptaszny, MD; UC San Francisco Health - Bradley A Sharpe, MD, Margaret Fang MD MPH; UK HealthCare - Mark Williams MD MHM, John Romond MD; University of Chicago – David Meltzer MD PhD, Gregory Ruhnke MD; University of Colorado - Marisha Burden MD; University of Florida - Nila Radhakrishnan MD; University of Iowa Hospitals and Clinics - Kevin Glenn MD MS; University of Miami - Efren Manjarrez MD; University of Michigan - Vineet Chopra MD MSc, Valerie Vaughn MD MSc; University of Missouri-Columbia Hospital - Hasan Naqvi MD; University of Nebraska Medical Center - Chad Vokoun MD; University of North Carolina at Chapel Hill - David Hemsey MD; University of Pittsburgh Medical Center - Gena Marie Walker MD; University of Vermont Medical Center - Steven Grant MD; University of Washington Medical Center - Christopher Kim MD MBA, Andrew White MD; University of Washington-Harborview Medical Center - Maralyssa Bann MD; University of Wisconsin Hospital and Clinics - David Sterken MD, Farah Kaiksow MD MPP, Ann Sheehy MD MS, Jordan Kenik MD MPH; UW Northwest Campus - Ben Wolpaw MD; Vanderbilt University Medical Center - Sunil Kripalani MD MSc, Eduard E Vasilevskis MD, Kathleene T Wooldridge MD MPH; Wake Forest Baptist Health - Erik Summers MD; Washington University St. Louis - Michael Lin MD; Weill Cornell - Justin Choi MD; Yale New Haven Hospital - William Cushing MA, Chris Sankey MD; Zuckerberg San Francisco General Hospital - Sumant Ranji MD.

The coronavirus disease of 2019 (COVID-19) pandemic has resulted in a surge in hospitalizations of patients with a novel, serious, and highly contagious infectious disease for which there is yet no proven treatment. Currently, much of the focus has been on intensive care unit (ICU) and ventilator capacity for the sickest of these patients who develop respiratory failure. However, most hospitalized patients are being cared for in general medical units.¹ Some evidence exists to describe adaptations to capacity needs outside of medical wards,^2-4 but few studies have specifically addressed the ward setting. Therefore, there is a pressing need for evidence to describe how to expand capacity and deliver medical ward–based care.

To better understand how inpatient care in the United States is adapting to the COVID-19 pandemic, we surveyed 72 sites participating in the Hospital Medicine Reengineering Network (HOMERuN), a national consortium of hospital medicine groups.⁵ We report results of this survey, carried out between April 3 and April 5, 2020.

Sites and Subjects

HOMERuN is a collaborative network of hospitalists from across the United States whose primary goal is to catalyze research and share best practices across hospital medicine groups. Using surveys of Hospital Medicine leaders, targeted medical record review, and other methods, HOMERuN’s funded research interests to date have included care transitions, workforce issues, patient and family engagement, and diagnostic errors. Sites participating in HOMERuN sites are relatively large urban academic medical centers (Appendix).

Survey Development and Deployment

We designed a focused survey that aimed to provide a snapshot of evolving operational and clinical aspects of COVID-19 care (Appendix). Domains included COVID-19 testing turnaround times, personal protective equipment (PPE) stewardship,⁶ features of respiratory isolation units (RIUs; ie, dedicated units for patients with known or suspected COVID-19), and observed effects on clinical care. We tested the instrument to ensure feasibility and clarity internally, performed brief cognitive testing with several hospital medicine leaders in HOMERuN, then disseminated the survey by email on April 3, with two follow-up emails on 2 subsequent days. Our study was deemed non–human subjects research by the University of California, San Francisco, Committee on Human Research. Descriptive statistics were used to characterize survey responses.

Of 72 hospitals surveyed, 51 (71%) responded. Mean hospital bed count was 940, three were safety-net hospitals, and one was a community-based teaching center; responding and nonresponding hospitals did not differ significantly in terms of bed count (Appendix).

Health System Adaptations, Testing, and PPE Status

Nearly all responding hospitals (46 of 51; 90%) had RIUs for patients with known or suspected COVID-19 (Table 1). Nearly all hospitals took steps to keep potentially sick healthcare providers from infecting others (eg, staying home if sick or exposed). Among respondents, 32% had rapid response teams, 24% had respiratory therapy teams, and 29% had case management teams that were dedicated to COVID-19 care. Thirty-two (63%) had developed models, such as ethics or palliative care consult services, to assist with difficult resource-allocation decisions (eg, how to prioritize ventilator use if demand exceeded supply). Twenty-three (45%) had developed post-acute care monitoring programs dedicated to COVID-19 patients.

At the time of our survey, only 2 sites (4%) reported COVID-19 test time turnaround under 1 hour, and 15 (30%) reported turnaround in less than 6 hours. Of the 29 sites able to provide estimates of PPE stockpile, 14 (48%) reported a supply of 2 weeks or less. The most common approaches to PPE stewardship focused on reuse of masks and face shields if not obviously soiled, centralizing PPE distribution, and disinfecting or sterilizing masks. Ten sites (20%) were utilizing 3-D printed masks, while 10% used homemade face shields or masks.

Characteristics of COVID-19 RIUs

Forty-six hospitals (90% of all respondents) in our cohort had developed RIUs at the time of survey administration. The earliest RIU implementation date was February 10, 2020, and the most recent was launched on the day of our survey. Admission to RIUs was primarily based on clinical factors associated with known or suspected COVID-19 infection (Table 2). The number of non–critical care RIU beds among locations at that time ranged from 10 or less to more than 50. The mean number of hospitalist attendings caring for patients in the RIUs was 10.2, with a mean 4.1 advanced practice providers, 5.5 residents, and 0 medical students. The number of planned patients per attending was typically 5 to 15. Nurses and physicians typically rounded separately. Medical distancing (eg, reducing patient room entry) was accomplished most commonly by grouped timing of medication administration (76% of sites), video links to room outside of rounding times (54% of sites), the use of video or telemedicine during rounds (17%), and clustering of activities such as medication administration or phlebotomy. The most common criteria prompting discharge from the RIU were a negative COVID-19 test (59%) and hospital discharge (57%), though comments from many respondents suggested that discharge criteria were changing rapidly.

Effects of Isolation Measures on In-Room Encounters and Diagnostic Processes

More than 90% of sites reported decreases in in-room encounter frequency across all provider types whether as a result of policies in place or not. Reductions were reported among hospitalists, advanced practice providers, residents, consultants, and therapists (Table 3). Reduced room entry most often resulted from an established or developing policy, but many noted reduced room entry without formal policies in place. Nearly all sites reported moving specialty consultations to phone or video evaluations. Diagnostic error was commonly reported, with missed non–COVID-19 medical diagnoses among COVID-19 infected patients being reported by 22 sites (46%) and missed COVID-19 diagnoses in patients admitted for other reasons by 22 sites (45%).

In this study of medical wards at academic medical centers, we found that, in response to the COVID-19 pandemic, hospitals made several changes in a short period of time to adapt to the crisis. These included implementation and rapid expansion of dedicated RIUs, greatly expanded use of inpatient telehealth for patient assessments and consultation, implementation of other approaches to minimize room entry (such as grouping in-room activities), and deployment of ethics consultation services to help manage issues around potential scarcity of life-saving measures such as ventilators. We also found that availability of PPE and timely testing was limited. Finally, a large proportion of sites reported potential diagnostic problems in the assessment of both patients suspected and those not suspected of having COVID-19.

RIUs are emerging as a primary modality for caring for non-ICU COVID-19 patients, though they never involved medical students; we hope the role of students in particular will increase as new models of training emerge in response to the pandemic.⁷ In contrast, telemedicine evolved rapidly to hold a substantial role in RIUs, with both ward and specialty teams using video visit technology to communicate with patients. COVID-19 has been viewed as a perfect use case for outpatient telemedicine,⁸ and a growing number of studies are examining its outpatient use^9,10; however, to date, somewhat less attention has been paid to inpatient deployment. Although our data suggest telemedicine has found a prominent place in RIUs, it remains to be seen whether it is associated with differences in patient or provider outcomes. For example, deficiencies in the physical examination, limited face-to-face contact, and lack of physical presence could all affect the patient–provider relationship, patient engagement, and the accuracy of the diagnostic process.

Our data suggest the possibility of missing non–COVID-19 diagnoses in patients suspected of COVID-19 and missing COVID-19 in those admitted for nonrespiratory reasons. The latter may be addressed as routine COVID-19 screening of admitted patients becomes commonplace. For the former, however, it is possible that physicians are “anchoring” their thinking on COVID-19 to the exclusion of other diagnoses, that physicians are not fully aware of complications unique to COVID-19 infection (such as thromboembolism), and/or that the above-mentioned limitations of telemedicine have decreased diagnostic performance.

Although PPE stockpile data were not easily available for some sites, a distressingly large number reported stockpiles of 2 weeks or less, with reuse being the most common approach to extending PPE supply. We also found it concerning that 43% of hospital leaders did not know their stockpile data; we believe this is an important question that hospital leaders need to be asking. Most sites in our study reported test turnaround times of longer than 6 hours; lack of rapid COVID-19 testing further stresses PPE stockpile and may slow patients’ transition out of the RIU or discharge to home.

Our study has several limitations, including the evolving nature of the pandemic and rapid adaptations of care systems in the pandemic’s surge phase. However, we attempted to frame our questions in ways that provided a focused snapshot of care. Furthermore, respondents may not have had exhaustive knowledge of their institution’s COVID-19 response strategies, but most were the directors of their hospitalist services, and we encouraged the respondents to confer with others to gather high-fidelity data. Finally, as a survey of large academic medical centers, our results may not apply to nonacademic centers.

Approaches to caring for non-ICU patients during the COVID-19 pandemic are rapidly evolving. Expansion of RIUs and developing the workforce to support them has been a primary focus, with rapid innovation in use of technology emerging as a critical adaptation while PPE limitations persist and needs for “medical distancing” continue to grow. Although rates of missed COVID-19 diagnoses will likely be reduced with testing and systems improvements, physicians and systems will also need to consider how to utilize emerging technology in ways that can improve clinical care and provider safety while aiding diagnostic thinking. This survey illustrates the rapid adaptations made by our hospitals in response to the pandemic; ongoing adaptation will likely be needed to optimally care for hospitalized patients with COVID-19 while the pandemic continues to evolve.

Thanks to members of the HOMERuN COVID-19 Collaborative Group: Baylor Scott & White Medical Center – Temple, Texas - Tresa McNeal MD; Beth Israel Deaconess Medical Center - Shani Herzig MD MPH, Joseph Li MD, Julius Yang MD PhD; Brigham and Women’s Hospital - Christopher Roy MD, Jeffrey Schnipper MD MPH; Cedars-Sinai Medical Center - Ed Seferian MD, ; ChristianaCare - Surekha Bhamidipati MD; Cleveland Clinic - Matthew Pappas MD MPH; Dartmouth-Hitchcock Medical Center - Jonathan Lurie MD MS; Dell Medical School at The University of Texas at Austin - Chris Moriates MD, Luci Leykum MD MBA MSc; Denver Health and Hospitals Authority - Diana Mancini MD; Emory University Hospital - Dan Hunt MD; Johns Hopkins Hospital - Daniel J Brotman MD, Zishan K Siddiqui MD, Shaker Eid MD MBA; Maine Medical Center - Daniel A Meyer MD, Robert Trowbridge MD; Massachusetts General Hospital - Melissa Mattison MD; Mayo Clinic Rochester – Caroline Burton MD, Sagar Dugani MD PhD; Medical College of Wisconsin - Sanjay Bhandari MD; Miriam Hospital - Kwame Dapaah-Afriyie MD MBA; Mount Sinai Hospital - Andrew Dunn MD; NorthShore - David Lovinger MD; Northwestern Memorial Hospital - Kevin O’Leary MD MS; Ohio State University Wexner Medical Center - Eric Schumacher DO; Oregon Health & Science University - Angela Alday MD; Penn Medicine - Ryan Greysen MD MHS MA; Rutgers- Robert Wood Johnson University Hospital - Michael Steinberg MD MPH; Stanford University School of Medicine - Neera Ahuja MD; Tulane Hospital and University Medical Center - Geraldine Ménard MD; UC San Diego Health - Ian Jenkins MD; UC Los Angeles Health - Michael Lazarus MD, Magdalena E. Ptaszny, MD; UC San Francisco Health - Bradley A Sharpe, MD, Margaret Fang MD MPH; UK HealthCare - Mark Williams MD MHM, John Romond MD; University of Chicago – David Meltzer MD PhD, Gregory Ruhnke MD; University of Colorado - Marisha Burden MD; University of Florida - Nila Radhakrishnan MD; University of Iowa Hospitals and Clinics - Kevin Glenn MD MS; University of Miami - Efren Manjarrez MD; University of Michigan - Vineet Chopra MD MSc, Valerie Vaughn MD MSc; University of Missouri-Columbia Hospital - Hasan Naqvi MD; University of Nebraska Medical Center - Chad Vokoun MD; University of North Carolina at Chapel Hill - David Hemsey MD; University of Pittsburgh Medical Center - Gena Marie Walker MD; University of Vermont Medical Center - Steven Grant MD; University of Washington Medical Center - Christopher Kim MD MBA, Andrew White MD; University of Washington-Harborview Medical Center - Maralyssa Bann MD; University of Wisconsin Hospital and Clinics - David Sterken MD, Farah Kaiksow MD MPP, Ann Sheehy MD MS, Jordan Kenik MD MPH; UW Northwest Campus - Ben Wolpaw MD; Vanderbilt University Medical Center - Sunil Kripalani MD MSc, Eduard E Vasilevskis MD, Kathleene T Wooldridge MD MPH; Wake Forest Baptist Health - Erik Summers MD; Washington University St. Louis - Michael Lin MD; Weill Cornell - Justin Choi MD; Yale New Haven Hospital - William Cushing MA, Chris Sankey MD; Zuckerberg San Francisco General Hospital - Sumant Ranji MD.

Frequent daily laboratory testing for inpatients contributes to excessive costs,¹ anemia,² and unnecessary testing.³ The ABIM Foundation’s Choosing Wisely^® campaign recommends avoiding routine labs, like complete blood counts (CBCs) and basic metabolic panels (BMP), in the face of clinical and laboratory stability.^4,5 Prior interventions have reduced unnecessary labs without adverse outcomes.^6-8

In addition to lab frequency, hospitalized patients face suboptimal lab timing. Labs are often ordered as early as 4 am at many institutions.^9,10 This practice disrupts sleep, undermining patient health.^11-13 While prior interventions have reduced daily phlebotomy, few have optimized lab timing for patient sleep.¹⁰ No study has harnessed the electronic health record (EHR) to optimize frequency and timing of labs simultaneously.¹⁴ We aimed to determine the effectiveness of a multicomponent intervention, called Order SMARTT (Sleep: Making Appropriate Reductions in Testing and Timing), to reduce frequency and optimize timing of daily routine labs for medical inpatients.

Setting

This study was conducted on the University of Chicago Medicine (UCM) general medicine services, which consisted of a resident-covered service supervised by general medicine, subspecialist, or hospitalist attendings and a hospitalist service staffed by hospitalists and advanced practice providers.

Development of Order SMARTT

To inform intervention development, we surveyed providers about lab-ordering preferences with use of questions from a prior survey to provide a benchmark (Appendix Table 2).¹⁵ While reducing lab frequency was supported, the modal response for how frequently a stable patient should receive routine labs was every 48 hours (Appendix Table 2). Therefore, we hypothesized that labs ordered every 48 hours may be popular. Taking labs every 48 hours would not require an urgent 4 am draw, so we created a 48-hour 6 am phlebotomy option to “step down” from daily labs. To promote these options, we created two EHR tools: First, an “Order Sleep” shortcut was launched in March 2018 by which physicians could type “sleep” in routine lab orders and three sleep-friendly options would become available (a 48-hour 6 am draw, a daily 6 am draw, or a daily 10 pm draw), and second, a “4 am Labs” column and icon on the electronic patient list to signal who had 4 am labs ordered was launched May 2018 (Appendix Table 1).

Physician Education

We created a 20-minute presentation on the harms of excessive labs and the benefits of sleep-friendly ordering. Instructional Order SMARTT posters were posted in clinician workrooms that emphasized forgoing labs on stable patients and using the “Order Sleep” shortcut when nonurgent labs were needed.

Labs Utilization Data

We used Epic Systems software (Verona, Wisconsin) and our institutional Tableau scorecard to obtain data on CBC and BMP ordering, patient census, and demographics for medical inpatients between July 1, 2017, and November 1, 2018.

Cost Analysis

Costs of lab tests (actual cost to our institution) were obtained from our institutional phlebotomy services’ estimates of direct variable labor and benefits costs and direct variable supplies cost.

Statistical Analysis

Data analysis was performed with SAS version 9.4 statistical software (Cary, North Carolina, USA) and R version 3.6.2 (Vienna, Austria). Descriptive statistics were used to summarize data. Surveys were analyzed using chi-square tests for categorical variables and two-sample t tests for continuous variables. For lab ordering data, interrupted time series analyses (ITSA) were used to determine the changes in ordering practices with the implementation of the two interventions controlling for service lines (resident vs hospitalist service). ITSA enables examination of changes in lab ordering while controlling for time. The AUTOREG function in SAS was used to build the model and estimate final parameters. This function automatically tests for autocorrelation, heteroscedasticity, and estimates any autoregressive parameters required in the model. Our main model tested the association between our two separate interventions on ordering practices, controlling for service (hospitalist or resident).¹⁶

Of 125 residents, 82 (65.6%) attended the session and completed the survey. Attendance and response rate for hospitalists was 80% (16 of 20). Similar to a prior study, many residents (73.1%) reported they would be comfortable if patients received less daily laboratory testing (Appendix Table 2).

We reviewed data from 7,045 total patients over 50,951 total patient days between July1, 2017, and November 1, 2018 (Appendix Table 3).

Total Lab Draws

After accounting for total patient days, we saw 26.3% reduction on average in total lab draws per patient-day per week postintervention (4.68 before vs 3.45 after; difference, 1.23; 95% CI, 0.82-1.63; P < .05; Appendix Table 3). When total lab draws were stratified by service, we saw 28% reduction on average in total lab draws per patient-day per week on resident services (4.67 before vs 3.36 after; difference, 1.31; 95% CI, 0.88-1.74; P < .05) and 23.9% reduction on average in lab draws/patient-day per week on the hospitalist service (4.73 before vs 3.60 after; difference, 1.13; 95% CI, 0.61-1.64; P < .05; Appendix Table 3).

Sleep-Friendly Labs by Intervention

For patients with routine labs, the proportion of sleep-friendly labs drawn per patient-day increased from 6% preintervention to 21% postintervention (P < .001). ITSA demonstrated both interventions were associated with improving lab timing. There was a statistically significant increase in sleep-friendly labs ordered per patient encounter per week immediately after the launch of “Order Sleep” (intercept, 0.49; standard error (SE), 0.14; P = .001) and the “4 am Labs” column (intercept, 0.32; SE, 0.13; P = .02; Table, Figure A).

Sleep-Friendly Lab Orders by Service

Over the study period, there was no significant difference in total sleep-friendly labs ordered/month between resident and hospitalist services (84.88 vs 86.19; P = .95).

In ITSA, “Order Sleep” was associated with a statistically significant immediate increase in sleep-friendly lab orders per patient encounter per week on resident services (intercept, 1.03; SE, 0.29; P < .001). However, this initial increase was followed by a decrease over time in sleep-friendly lab orders per week (slope change, –0.1; SE, 0.04; P = .02; Table, Figure B). There was no statistically significant change observed on the hospitalist service with “Order Sleep.”

In contrast, the “4 am Labs” column was associated with a statistically significant immediate increase in sleep-friendly lab orders per patient encounter per week on hospitalist service (intercept, 1.17; SE, 0.50; P = .02; Table, Figure B). While there was no immediate change on resident service, we observed a significant increase over time in sleep-friendly orders per encounter per week on resident services with the introduction of the “4 am Labs” column (slope change, 0.11; SE, 0.04; P = .01; Table, Figure B).

Cost Savings

Using an estimated cost of $7.70 for CBCs and $8.01 for BMPs from our laboratory, our intervention saved an estimated $60,278 in lab costs alone over the 16-month study period (Appendix Table 4).

To our knowledge, this is the first study showing a multicomponent intervention using EHR tools can both reduce frequency and optimize timing of routine lab ordering. Our project had two interventions implemented at two different times: First, an “Order Sleep” shortcut was introduced to select sleep-friendly lab timing, including a 6 am draw every 48 hours, and later, a “4 am Labs” column was added to electronic patient lists to passively nudge physicians to consider sleep-friendly labs. The “Order Sleep” tool was associated with a significant immediate increase in sleep-friendly lab ordering on resident services, while the “4 am Labs” column was associated with a significant immediate increase in sleep-friendly lab ordering on the hospitalist service. An overall reduction in total lab draws was seen on both services.

While the “Order Sleep” tool was initially associated with significant increases in sleep-friendly orders on resident services, this change was not sustained. This could have been caused by the short-lived effect of education more than sustained adoption of the tool. In contrast, the “4 am Labs” column on the patient list resulted in a significant sustained increase in sleep-friendly labs on resident services. While residents responded to both tools, both interventions were associated with lasting changes in practice.

The “4 am Labs” column on patient lists was associated with increased adoption of sleep-friendly labs for hospitalist services. Hospitalists care for a larger census with more frequent handoffs and greater reliance on the patient list, which makes patient lists in general an important tool to target value improvement.

While other institutions have attempted to shift lab-timing by altering phlebotomy workflows¹⁰ or via conscious decision-making on rounds,⁹ our study differs in several ways. We avoided default options and allowed clinicians to select sleep-friendly labs to promote buy-in. It is sometimes necessary to order 4 am labs for sick patients who need urgent decision-making, which highlights the need to preserve this option for clinicians. Similarly, our intervention did not aim to eliminate lab draws entirely but offer a more judicious frequency of every 48 hours, consistent with the survey preferences noted. This intervention encouraged reappraisal of patients’ overall needs for labs and created variability in ordering times to reduce the volume of labs ordered at 4 am.

Our study had several limitations. First, this was a single center study on adult medicine services, which limits generalizability. Although we considered surgical services, their early rounds made deviations from 4 am undesirable. Given the observational study design, we cannot assume causal relationships or rule out secular trends. There were large swings in sleep-friendly lab ordering during our study that could be attributed to different physicians rotating on the services monthly. We did not obtain objective data on patient sleep or patient satisfaction because of the low response rate to the HCAHPS (Hospital Consumer Assessment of Healthcare Providers and Systems) survey.

In conclusion, a multicomponent intervention using EHR tools can reduce inpatient daily lab frequency and optimize lab timing to help promote patient sleep.

The authors would like to thank The University of Chicago Center for Healthcare Delivery Science and Innovation for sponsoring their annual Choosing Wisely Challenge, which allowed for access to institutional support and resources for this study. We would also like to thank Mary Kate Springman, MHA, and John Fahrenbach, PhD, for their assistance with this project. Dr Tapaskar also received mentorship through the Future Leader Program for the High Value Practice Academic Alliance.

Frequent daily laboratory testing for inpatients contributes to excessive costs,¹ anemia,² and unnecessary testing.³ The ABIM Foundation’s Choosing Wisely^® campaign recommends avoiding routine labs, like complete blood counts (CBCs) and basic metabolic panels (BMP), in the face of clinical and laboratory stability.^4,5 Prior interventions have reduced unnecessary labs without adverse outcomes.^6-8

In addition to lab frequency, hospitalized patients face suboptimal lab timing. Labs are often ordered as early as 4 am at many institutions.^9,10 This practice disrupts sleep, undermining patient health.^11-13 While prior interventions have reduced daily phlebotomy, few have optimized lab timing for patient sleep.¹⁰ No study has harnessed the electronic health record (EHR) to optimize frequency and timing of labs simultaneously.¹⁴ We aimed to determine the effectiveness of a multicomponent intervention, called Order SMARTT (Sleep: Making Appropriate Reductions in Testing and Timing), to reduce frequency and optimize timing of daily routine labs for medical inpatients.

Setting

This study was conducted on the University of Chicago Medicine (UCM) general medicine services, which consisted of a resident-covered service supervised by general medicine, subspecialist, or hospitalist attendings and a hospitalist service staffed by hospitalists and advanced practice providers.

Development of Order SMARTT

To inform intervention development, we surveyed providers about lab-ordering preferences with use of questions from a prior survey to provide a benchmark (Appendix Table 2).¹⁵ While reducing lab frequency was supported, the modal response for how frequently a stable patient should receive routine labs was every 48 hours (Appendix Table 2). Therefore, we hypothesized that labs ordered every 48 hours may be popular. Taking labs every 48 hours would not require an urgent 4 am draw, so we created a 48-hour 6 am phlebotomy option to “step down” from daily labs. To promote these options, we created two EHR tools: First, an “Order Sleep” shortcut was launched in March 2018 by which physicians could type “sleep” in routine lab orders and three sleep-friendly options would become available (a 48-hour 6 am draw, a daily 6 am draw, or a daily 10 pm draw), and second, a “4 am Labs” column and icon on the electronic patient list to signal who had 4 am labs ordered was launched May 2018 (Appendix Table 1).

Physician Education

We created a 20-minute presentation on the harms of excessive labs and the benefits of sleep-friendly ordering. Instructional Order SMARTT posters were posted in clinician workrooms that emphasized forgoing labs on stable patients and using the “Order Sleep” shortcut when nonurgent labs were needed.

Labs Utilization Data

We used Epic Systems software (Verona, Wisconsin) and our institutional Tableau scorecard to obtain data on CBC and BMP ordering, patient census, and demographics for medical inpatients between July 1, 2017, and November 1, 2018.

Cost Analysis

Costs of lab tests (actual cost to our institution) were obtained from our institutional phlebotomy services’ estimates of direct variable labor and benefits costs and direct variable supplies cost.

Statistical Analysis

Data analysis was performed with SAS version 9.4 statistical software (Cary, North Carolina, USA) and R version 3.6.2 (Vienna, Austria). Descriptive statistics were used to summarize data. Surveys were analyzed using chi-square tests for categorical variables and two-sample t tests for continuous variables. For lab ordering data, interrupted time series analyses (ITSA) were used to determine the changes in ordering practices with the implementation of the two interventions controlling for service lines (resident vs hospitalist service). ITSA enables examination of changes in lab ordering while controlling for time. The AUTOREG function in SAS was used to build the model and estimate final parameters. This function automatically tests for autocorrelation, heteroscedasticity, and estimates any autoregressive parameters required in the model. Our main model tested the association between our two separate interventions on ordering practices, controlling for service (hospitalist or resident).¹⁶

Of 125 residents, 82 (65.6%) attended the session and completed the survey. Attendance and response rate for hospitalists was 80% (16 of 20). Similar to a prior study, many residents (73.1%) reported they would be comfortable if patients received less daily laboratory testing (Appendix Table 2).

We reviewed data from 7,045 total patients over 50,951 total patient days between July1, 2017, and November 1, 2018 (Appendix Table 3).

Total Lab Draws

After accounting for total patient days, we saw 26.3% reduction on average in total lab draws per patient-day per week postintervention (4.68 before vs 3.45 after; difference, 1.23; 95% CI, 0.82-1.63; P < .05; Appendix Table 3). When total lab draws were stratified by service, we saw 28% reduction on average in total lab draws per patient-day per week on resident services (4.67 before vs 3.36 after; difference, 1.31; 95% CI, 0.88-1.74; P < .05) and 23.9% reduction on average in lab draws/patient-day per week on the hospitalist service (4.73 before vs 3.60 after; difference, 1.13; 95% CI, 0.61-1.64; P < .05; Appendix Table 3).

Sleep-Friendly Labs by Intervention

For patients with routine labs, the proportion of sleep-friendly labs drawn per patient-day increased from 6% preintervention to 21% postintervention (P < .001). ITSA demonstrated both interventions were associated with improving lab timing. There was a statistically significant increase in sleep-friendly labs ordered per patient encounter per week immediately after the launch of “Order Sleep” (intercept, 0.49; standard error (SE), 0.14; P = .001) and the “4 am Labs” column (intercept, 0.32; SE, 0.13; P = .02; Table, Figure A).

Sleep-Friendly Lab Orders by Service

Over the study period, there was no significant difference in total sleep-friendly labs ordered/month between resident and hospitalist services (84.88 vs 86.19; P = .95).

In ITSA, “Order Sleep” was associated with a statistically significant immediate increase in sleep-friendly lab orders per patient encounter per week on resident services (intercept, 1.03; SE, 0.29; P < .001). However, this initial increase was followed by a decrease over time in sleep-friendly lab orders per week (slope change, –0.1; SE, 0.04; P = .02; Table, Figure B). There was no statistically significant change observed on the hospitalist service with “Order Sleep.”

In contrast, the “4 am Labs” column was associated with a statistically significant immediate increase in sleep-friendly lab orders per patient encounter per week on hospitalist service (intercept, 1.17; SE, 0.50; P = .02; Table, Figure B). While there was no immediate change on resident service, we observed a significant increase over time in sleep-friendly orders per encounter per week on resident services with the introduction of the “4 am Labs” column (slope change, 0.11; SE, 0.04; P = .01; Table, Figure B).

Cost Savings

Using an estimated cost of $7.70 for CBCs and $8.01 for BMPs from our laboratory, our intervention saved an estimated $60,278 in lab costs alone over the 16-month study period (Appendix Table 4).

To our knowledge, this is the first study showing a multicomponent intervention using EHR tools can both reduce frequency and optimize timing of routine lab ordering. Our project had two interventions implemented at two different times: First, an “Order Sleep” shortcut was introduced to select sleep-friendly lab timing, including a 6 am draw every 48 hours, and later, a “4 am Labs” column was added to electronic patient lists to passively nudge physicians to consider sleep-friendly labs. The “Order Sleep” tool was associated with a significant immediate increase in sleep-friendly lab ordering on resident services, while the “4 am Labs” column was associated with a significant immediate increase in sleep-friendly lab ordering on the hospitalist service. An overall reduction in total lab draws was seen on both services.

While the “Order Sleep” tool was initially associated with significant increases in sleep-friendly orders on resident services, this change was not sustained. This could have been caused by the short-lived effect of education more than sustained adoption of the tool. In contrast, the “4 am Labs” column on the patient list resulted in a significant sustained increase in sleep-friendly labs on resident services. While residents responded to both tools, both interventions were associated with lasting changes in practice.

The “4 am Labs” column on patient lists was associated with increased adoption of sleep-friendly labs for hospitalist services. Hospitalists care for a larger census with more frequent handoffs and greater reliance on the patient list, which makes patient lists in general an important tool to target value improvement.

While other institutions have attempted to shift lab-timing by altering phlebotomy workflows¹⁰ or via conscious decision-making on rounds,⁹ our study differs in several ways. We avoided default options and allowed clinicians to select sleep-friendly labs to promote buy-in. It is sometimes necessary to order 4 am labs for sick patients who need urgent decision-making, which highlights the need to preserve this option for clinicians. Similarly, our intervention did not aim to eliminate lab draws entirely but offer a more judicious frequency of every 48 hours, consistent with the survey preferences noted. This intervention encouraged reappraisal of patients’ overall needs for labs and created variability in ordering times to reduce the volume of labs ordered at 4 am.

Our study had several limitations. First, this was a single center study on adult medicine services, which limits generalizability. Although we considered surgical services, their early rounds made deviations from 4 am undesirable. Given the observational study design, we cannot assume causal relationships or rule out secular trends. There were large swings in sleep-friendly lab ordering during our study that could be attributed to different physicians rotating on the services monthly. We did not obtain objective data on patient sleep or patient satisfaction because of the low response rate to the HCAHPS (Hospital Consumer Assessment of Healthcare Providers and Systems) survey.

In conclusion, a multicomponent intervention using EHR tools can reduce inpatient daily lab frequency and optimize lab timing to help promote patient sleep.

The authors would like to thank The University of Chicago Center for Healthcare Delivery Science and Innovation for sponsoring their annual Choosing Wisely Challenge, which allowed for access to institutional support and resources for this study. We would also like to thank Mary Kate Springman, MHA, and John Fahrenbach, PhD, for their assistance with this project. Dr Tapaskar also received mentorship through the Future Leader Program for the High Value Practice Academic Alliance.

Frequent daily laboratory testing for inpatients contributes to excessive costs,¹ anemia,² and unnecessary testing.³ The ABIM Foundation’s Choosing Wisely^® campaign recommends avoiding routine labs, like complete blood counts (CBCs) and basic metabolic panels (BMP), in the face of clinical and laboratory stability.^4,5 Prior interventions have reduced unnecessary labs without adverse outcomes.^6-8

In addition to lab frequency, hospitalized patients face suboptimal lab timing. Labs are often ordered as early as 4 am at many institutions.^9,10 This practice disrupts sleep, undermining patient health.^11-13 While prior interventions have reduced daily phlebotomy, few have optimized lab timing for patient sleep.¹⁰ No study has harnessed the electronic health record (EHR) to optimize frequency and timing of labs simultaneously.¹⁴ We aimed to determine the effectiveness of a multicomponent intervention, called Order SMARTT (Sleep: Making Appropriate Reductions in Testing and Timing), to reduce frequency and optimize timing of daily routine labs for medical inpatients.

Setting

This study was conducted on the University of Chicago Medicine (UCM) general medicine services, which consisted of a resident-covered service supervised by general medicine, subspecialist, or hospitalist attendings and a hospitalist service staffed by hospitalists and advanced practice providers.

Development of Order SMARTT

To inform intervention development, we surveyed providers about lab-ordering preferences with use of questions from a prior survey to provide a benchmark (Appendix Table 2).¹⁵ While reducing lab frequency was supported, the modal response for how frequently a stable patient should receive routine labs was every 48 hours (Appendix Table 2). Therefore, we hypothesized that labs ordered every 48 hours may be popular. Taking labs every 48 hours would not require an urgent 4 am draw, so we created a 48-hour 6 am phlebotomy option to “step down” from daily labs. To promote these options, we created two EHR tools: First, an “Order Sleep” shortcut was launched in March 2018 by which physicians could type “sleep” in routine lab orders and three sleep-friendly options would become available (a 48-hour 6 am draw, a daily 6 am draw, or a daily 10 pm draw), and second, a “4 am Labs” column and icon on the electronic patient list to signal who had 4 am labs ordered was launched May 2018 (Appendix Table 1).

Physician Education

We created a 20-minute presentation on the harms of excessive labs and the benefits of sleep-friendly ordering. Instructional Order SMARTT posters were posted in clinician workrooms that emphasized forgoing labs on stable patients and using the “Order Sleep” shortcut when nonurgent labs were needed.

Labs Utilization Data

We used Epic Systems software (Verona, Wisconsin) and our institutional Tableau scorecard to obtain data on CBC and BMP ordering, patient census, and demographics for medical inpatients between July 1, 2017, and November 1, 2018.

Cost Analysis

Costs of lab tests (actual cost to our institution) were obtained from our institutional phlebotomy services’ estimates of direct variable labor and benefits costs and direct variable supplies cost.

Statistical Analysis

Data analysis was performed with SAS version 9.4 statistical software (Cary, North Carolina, USA) and R version 3.6.2 (Vienna, Austria). Descriptive statistics were used to summarize data. Surveys were analyzed using chi-square tests for categorical variables and two-sample t tests for continuous variables. For lab ordering data, interrupted time series analyses (ITSA) were used to determine the changes in ordering practices with the implementation of the two interventions controlling for service lines (resident vs hospitalist service). ITSA enables examination of changes in lab ordering while controlling for time. The AUTOREG function in SAS was used to build the model and estimate final parameters. This function automatically tests for autocorrelation, heteroscedasticity, and estimates any autoregressive parameters required in the model. Our main model tested the association between our two separate interventions on ordering practices, controlling for service (hospitalist or resident).¹⁶

Of 125 residents, 82 (65.6%) attended the session and completed the survey. Attendance and response rate for hospitalists was 80% (16 of 20). Similar to a prior study, many residents (73.1%) reported they would be comfortable if patients received less daily laboratory testing (Appendix Table 2).

We reviewed data from 7,045 total patients over 50,951 total patient days between July1, 2017, and November 1, 2018 (Appendix Table 3).

Total Lab Draws

After accounting for total patient days, we saw 26.3% reduction on average in total lab draws per patient-day per week postintervention (4.68 before vs 3.45 after; difference, 1.23; 95% CI, 0.82-1.63; P < .05; Appendix Table 3). When total lab draws were stratified by service, we saw 28% reduction on average in total lab draws per patient-day per week on resident services (4.67 before vs 3.36 after; difference, 1.31; 95% CI, 0.88-1.74; P < .05) and 23.9% reduction on average in lab draws/patient-day per week on the hospitalist service (4.73 before vs 3.60 after; difference, 1.13; 95% CI, 0.61-1.64; P < .05; Appendix Table 3).

Sleep-Friendly Labs by Intervention

For patients with routine labs, the proportion of sleep-friendly labs drawn per patient-day increased from 6% preintervention to 21% postintervention (P < .001). ITSA demonstrated both interventions were associated with improving lab timing. There was a statistically significant increase in sleep-friendly labs ordered per patient encounter per week immediately after the launch of “Order Sleep” (intercept, 0.49; standard error (SE), 0.14; P = .001) and the “4 am Labs” column (intercept, 0.32; SE, 0.13; P = .02; Table, Figure A).

Sleep-Friendly Lab Orders by Service

Over the study period, there was no significant difference in total sleep-friendly labs ordered/month between resident and hospitalist services (84.88 vs 86.19; P = .95).

In ITSA, “Order Sleep” was associated with a statistically significant immediate increase in sleep-friendly lab orders per patient encounter per week on resident services (intercept, 1.03; SE, 0.29; P < .001). However, this initial increase was followed by a decrease over time in sleep-friendly lab orders per week (slope change, –0.1; SE, 0.04; P = .02; Table, Figure B). There was no statistically significant change observed on the hospitalist service with “Order Sleep.”

In contrast, the “4 am Labs” column was associated with a statistically significant immediate increase in sleep-friendly lab orders per patient encounter per week on hospitalist service (intercept, 1.17; SE, 0.50; P = .02; Table, Figure B). While there was no immediate change on resident service, we observed a significant increase over time in sleep-friendly orders per encounter per week on resident services with the introduction of the “4 am Labs” column (slope change, 0.11; SE, 0.04; P = .01; Table, Figure B).

Cost Savings

Using an estimated cost of $7.70 for CBCs and $8.01 for BMPs from our laboratory, our intervention saved an estimated $60,278 in lab costs alone over the 16-month study period (Appendix Table 4).

To our knowledge, this is the first study showing a multicomponent intervention using EHR tools can both reduce frequency and optimize timing of routine lab ordering. Our project had two interventions implemented at two different times: First, an “Order Sleep” shortcut was introduced to select sleep-friendly lab timing, including a 6 am draw every 48 hours, and later, a “4 am Labs” column was added to electronic patient lists to passively nudge physicians to consider sleep-friendly labs. The “Order Sleep” tool was associated with a significant immediate increase in sleep-friendly lab ordering on resident services, while the “4 am Labs” column was associated with a significant immediate increase in sleep-friendly lab ordering on the hospitalist service. An overall reduction in total lab draws was seen on both services.

While the “Order Sleep” tool was initially associated with significant increases in sleep-friendly orders on resident services, this change was not sustained. This could have been caused by the short-lived effect of education more than sustained adoption of the tool. In contrast, the “4 am Labs” column on the patient list resulted in a significant sustained increase in sleep-friendly labs on resident services. While residents responded to both tools, both interventions were associated with lasting changes in practice.

The “4 am Labs” column on patient lists was associated with increased adoption of sleep-friendly labs for hospitalist services. Hospitalists care for a larger census with more frequent handoffs and greater reliance on the patient list, which makes patient lists in general an important tool to target value improvement.

While other institutions have attempted to shift lab-timing by altering phlebotomy workflows¹⁰ or via conscious decision-making on rounds,⁹ our study differs in several ways. We avoided default options and allowed clinicians to select sleep-friendly labs to promote buy-in. It is sometimes necessary to order 4 am labs for sick patients who need urgent decision-making, which highlights the need to preserve this option for clinicians. Similarly, our intervention did not aim to eliminate lab draws entirely but offer a more judicious frequency of every 48 hours, consistent with the survey preferences noted. This intervention encouraged reappraisal of patients’ overall needs for labs and created variability in ordering times to reduce the volume of labs ordered at 4 am.

Our study had several limitations. First, this was a single center study on adult medicine services, which limits generalizability. Although we considered surgical services, their early rounds made deviations from 4 am undesirable. Given the observational study design, we cannot assume causal relationships or rule out secular trends. There were large swings in sleep-friendly lab ordering during our study that could be attributed to different physicians rotating on the services monthly. We did not obtain objective data on patient sleep or patient satisfaction because of the low response rate to the HCAHPS (Hospital Consumer Assessment of Healthcare Providers and Systems) survey.

In conclusion, a multicomponent intervention using EHR tools can reduce inpatient daily lab frequency and optimize lab timing to help promote patient sleep.

The authors would like to thank The University of Chicago Center for Healthcare Delivery Science and Innovation for sponsoring their annual Choosing Wisely Challenge, which allowed for access to institutional support and resources for this study. We would also like to thank Mary Kate Springman, MHA, and John Fahrenbach, PhD, for their assistance with this project. Dr Tapaskar also received mentorship through the Future Leader Program for the High Value Practice Academic Alliance.

A large body of evidence has demonstrated significant gender disparities in academic medicine. Women are less likely than men to reach the rank of full professor, be speakers at Grand Rounds, and author studies in medical journals.^1-4 Gender-based differences in these achievements reduce the visibility of women role models in all academic medicine domains, including research, education, health systems leadership, and clinical excellence. Clinical problem-solving exercises are an opportunity to highlight the skills of women physicians as master clinicians and to establish women as clinician role models.

Clinical problem-solving exercises are highly visible demonstrations of clinical excellence in the medical literature. These exercises follow a specific format in which a clinician analyzes a diagnostic dilemma in a step-by-step manner in response to sequential segments of clinical data. The clinical problem-­solving format was introduced in 1992 in the New England Journal of Medicine and has been adopted by other journals.⁵ (The clinical problem-solving format differs from the clinical pathologic conference format, in which an entire case is presented followed by an extended analysis). Clinical problem-­solving publications are forums for learners of all levels to witness an expert clinician reason through a case.

Authorship teams on clinical reasoning exercises typically include the patient’s physician(s), specialists relevant to the final diagnosis, and the invited discussant who analyzes the clinical dilemma. Journals stipulate in the author instructions, series introductions, or standardized manuscript text of the series that the discussant be a skilled and experienced clinician.^5,6 The patient’s physicians who initiate the clinical reasoning manuscript typically select the discussant; in some journals, the series editors may provide input on discussant choice. To our knowledge, this is the only author role in the medical literature in which authors are invited specifically for their diagnostic reasoning ability.

While women have been authors on fewer original research articles and guest editorials than men have,³ the proportion of women among authors of published clinical reasoning exercises is unknown. This represents a gap in our understanding of the landscape of gender inequity in academic medicine. We sought to determine the proportion of women authors in major clinical problem-solving series and examine the change in women authorship over time.

We selected published clinical problem-solving series targeting a general medicine audience. We excluded general medicine journals in which authors were restricted to one institution or those in which the clinical problem-solving format was not a regular series. Series which met these criteria were the Clinical Problem-Solving series in the New England Journal of Medicine (NEJM), the Clinical Care Conundrums series in the Journal of Hospital Medicine (JHM), and the Exercises in Clinical Reasoning series in the Journal of General Internal Medicine (JGIM). We analyzed the proportion of women authors in each clinical reasoning series from the inaugural articles (1992 for NEJM, 2006 for JHM, and 2010 for JGIM) until July 2019. We also analyzed the change in proportion of women authors from year to year by using data up to 2018 to avoid including a partial year.

We used the gender-guesser python library⁷ to categorize the gender of first, last, and all authors based on their first names. The library uses a database of approximately 40,000 names⁸ and maps first names to the genders they are associated with across languages, classifying each name as “man,” “woman,” “mostly man,” ”mostly woman,” “androgynous,” or “unknown.” When a name is commonly associated with multiple genders, or is associated with different genders in different languages, it is classified either as mostly man, mostly woman, or androgynous. When a name is not found in the database, it is classified as unknown. For all names classified by the database as unknown, androgynous, or mostly man/mostly woman, we determined gender identities by finding the authors’ institutional webpages and consulting their listed gender pronouns. We used gender based on first name to best approximate what a reader would interpret as the author’s gender. We used gender rather than biological sex because authors may have changed their names to better express their gender identity, which may differ from sex assigned at birth.

To test for the statistical significance of changes in the proportion of women authors over time, we performed the Cochran-­Armitage trend test. A P value less than .05 was considered significant.

We analyzed 402 articles: 280 from NEJM, 83 from JHM, and 39 from JGIM. There were 1,026 authors of clinical reasoning articles from NEJM, 362 from JHM, and 168 from JGIM. The Table shows the number of total articles, total authors, and women among first, last, and all authors by journal and by year (inaugural year and 2018). Data for all years are shown in the Appendix Table.

Over the entire time period studied, the percentage of women across the three journals was lowest for last authors (28/280 [10.0%] for NEJM, 6/83 [7.2%] for JHM, and 9/39 [23.1%] for JGIM) and highest for first authors (80/280 [28.6%] for NEJM, 36/83 [43.4%] for JHM, and 13/39 [33.3%] for JGIM). The percentage of women among all authors was similar for all three journals: 224/1,026 (21.8%) for NEJM, 83/362 (22.9%) for JHM, and 36/168 (21.4%) for JGIM.

The Figure shows the change in percentage of women authors from year to year through 2018. There was a significant increase in the proportion of women first authors in NEJM (from 0/12 [0.0%] in 1992 to 4/12 [33.3%] in 2018; P < .0001) and JHM (from 2/5 [40.0%] in 2006 to 7/9 [77.8%] in 2018 P = .01). There was also a significant increase in the proportion of women among all authors in NEJM (from 0/17 [0.0%] in 1992 to 17/59 [28.8%] in 2018; P < .0001) and JHM (from 3/19 [15.8%] in 2006 to 14/37 [37.8%] in 2018; P = .005). There was no significant change in the proportion of women last authors in any of the three journals. There were no statistically significant changes in JGIM authorship over time.

Clinical problem-solving exercises provide a forum for physicians to demonstrate diagnostic reasoning skills and clinical acumen. In this study, we focused on three prominent clinical problem-solving series in general medicine journals. We found that women authors were underrepresented in each series. The percentage of women authors has increased over time, especially among first and all authors; however, there was no change in the last author position. In all three series women still constituted less than 40% of all authors and less than 25% of last authors. In comparison, women currently constitute about 40% of general internal medicine physicians, and this proportion has been rapidly growing over time; women now represent over half of all medical school graduates as opposed to 6% in 1960.^9,10 Our findings are consistent with the large body of evidence that describes gender-based differences in opportunities within academic medicine.

Prior studies have shown that gender inequities in academic medicine stem from a longstanding culture of sexism; these inequities are perpetuated in part by having too few visible women role models and mentors.¹¹ These factors may lead to editorial practices that favor articles written by men. In addition, women may be less likely to be invited as expert discussants if other authors have a bias of associating clinical expertise with men physicians. This is consistent with data showing that women are less likely to be invited to write commentaries in peer-reviewed journals.¹²

Gender-based differences in authorship of clinical problem-solving publications also have important implications for women in medicine. In order to address the gender gap in academic achievement, women need visible role models and mentors.¹³ Including more women authors of clinical reasoning publications has the potential to establish more women as master clinicians and role models.

There are a number of actions that can help establish more women clinical problem-solving authors. Editorial boards and editors in chief should track their review and publication practices to hold themselves accountable to author diversity. For example, JHM has announced plans to analyze author representation of women and racial and ethnic minorities, including those among first and senior authors.¹⁴ Clinicians who are assembling author teams for clinical problem-solving manuscripts should also strongly consider if an equal number of men and women have been invited to serve as specialty consultants and case discussants.

Our study has limitations. We used a python library to classify author gender based on first name (supplemented by internet searches), which may have misclassified authors and did not take into account nonbinary gender identities. Because there is no convention for assigning the expert discussant to a specific author position, we could not determine the gender distribution of the discussants. However, given that women were underrepresented among first, last, and all authors in all three journals, they are likely a minority of discussants as well.

A preponderance of male voices in clinical reasoning exercises, in which learners see clinical role models, may perpetuate a culture in which women are not seen—and do not see themselves—as having the potential to be master clinicians. Including more women in clinical reasoning exercises is an opportunity to amplify the voices of women as master clinicians and combat gender discrimination in medicine.

A large body of evidence has demonstrated significant gender disparities in academic medicine. Women are less likely than men to reach the rank of full professor, be speakers at Grand Rounds, and author studies in medical journals.^1-4 Gender-based differences in these achievements reduce the visibility of women role models in all academic medicine domains, including research, education, health systems leadership, and clinical excellence. Clinical problem-solving exercises are an opportunity to highlight the skills of women physicians as master clinicians and to establish women as clinician role models.

Clinical problem-solving exercises are highly visible demonstrations of clinical excellence in the medical literature. These exercises follow a specific format in which a clinician analyzes a diagnostic dilemma in a step-by-step manner in response to sequential segments of clinical data. The clinical problem-­solving format was introduced in 1992 in the New England Journal of Medicine and has been adopted by other journals.⁵ (The clinical problem-solving format differs from the clinical pathologic conference format, in which an entire case is presented followed by an extended analysis). Clinical problem-­solving publications are forums for learners of all levels to witness an expert clinician reason through a case.

Authorship teams on clinical reasoning exercises typically include the patient’s physician(s), specialists relevant to the final diagnosis, and the invited discussant who analyzes the clinical dilemma. Journals stipulate in the author instructions, series introductions, or standardized manuscript text of the series that the discussant be a skilled and experienced clinician.^5,6 The patient’s physicians who initiate the clinical reasoning manuscript typically select the discussant; in some journals, the series editors may provide input on discussant choice. To our knowledge, this is the only author role in the medical literature in which authors are invited specifically for their diagnostic reasoning ability.

While women have been authors on fewer original research articles and guest editorials than men have,³ the proportion of women among authors of published clinical reasoning exercises is unknown. This represents a gap in our understanding of the landscape of gender inequity in academic medicine. We sought to determine the proportion of women authors in major clinical problem-solving series and examine the change in women authorship over time.

We selected published clinical problem-solving series targeting a general medicine audience. We excluded general medicine journals in which authors were restricted to one institution or those in which the clinical problem-solving format was not a regular series. Series which met these criteria were the Clinical Problem-Solving series in the New England Journal of Medicine (NEJM), the Clinical Care Conundrums series in the Journal of Hospital Medicine (JHM), and the Exercises in Clinical Reasoning series in the Journal of General Internal Medicine (JGIM). We analyzed the proportion of women authors in each clinical reasoning series from the inaugural articles (1992 for NEJM, 2006 for JHM, and 2010 for JGIM) until July 2019. We also analyzed the change in proportion of women authors from year to year by using data up to 2018 to avoid including a partial year.

We used the gender-guesser python library⁷ to categorize the gender of first, last, and all authors based on their first names. The library uses a database of approximately 40,000 names⁸ and maps first names to the genders they are associated with across languages, classifying each name as “man,” “woman,” “mostly man,” ”mostly woman,” “androgynous,” or “unknown.” When a name is commonly associated with multiple genders, or is associated with different genders in different languages, it is classified either as mostly man, mostly woman, or androgynous. When a name is not found in the database, it is classified as unknown. For all names classified by the database as unknown, androgynous, or mostly man/mostly woman, we determined gender identities by finding the authors’ institutional webpages and consulting their listed gender pronouns. We used gender based on first name to best approximate what a reader would interpret as the author’s gender. We used gender rather than biological sex because authors may have changed their names to better express their gender identity, which may differ from sex assigned at birth.

To test for the statistical significance of changes in the proportion of women authors over time, we performed the Cochran-­Armitage trend test. A P value less than .05 was considered significant.

We analyzed 402 articles: 280 from NEJM, 83 from JHM, and 39 from JGIM. There were 1,026 authors of clinical reasoning articles from NEJM, 362 from JHM, and 168 from JGIM. The Table shows the number of total articles, total authors, and women among first, last, and all authors by journal and by year (inaugural year and 2018). Data for all years are shown in the Appendix Table.

Over the entire time period studied, the percentage of women across the three journals was lowest for last authors (28/280 [10.0%] for NEJM, 6/83 [7.2%] for JHM, and 9/39 [23.1%] for JGIM) and highest for first authors (80/280 [28.6%] for NEJM, 36/83 [43.4%] for JHM, and 13/39 [33.3%] for JGIM). The percentage of women among all authors was similar for all three journals: 224/1,026 (21.8%) for NEJM, 83/362 (22.9%) for JHM, and 36/168 (21.4%) for JGIM.

The Figure shows the change in percentage of women authors from year to year through 2018. There was a significant increase in the proportion of women first authors in NEJM (from 0/12 [0.0%] in 1992 to 4/12 [33.3%] in 2018; P < .0001) and JHM (from 2/5 [40.0%] in 2006 to 7/9 [77.8%] in 2018 P = .01). There was also a significant increase in the proportion of women among all authors in NEJM (from 0/17 [0.0%] in 1992 to 17/59 [28.8%] in 2018; P < .0001) and JHM (from 3/19 [15.8%] in 2006 to 14/37 [37.8%] in 2018; P = .005). There was no significant change in the proportion of women last authors in any of the three journals. There were no statistically significant changes in JGIM authorship over time.

Clinical problem-solving exercises provide a forum for physicians to demonstrate diagnostic reasoning skills and clinical acumen. In this study, we focused on three prominent clinical problem-solving series in general medicine journals. We found that women authors were underrepresented in each series. The percentage of women authors has increased over time, especially among first and all authors; however, there was no change in the last author position. In all three series women still constituted less than 40% of all authors and less than 25% of last authors. In comparison, women currently constitute about 40% of general internal medicine physicians, and this proportion has been rapidly growing over time; women now represent over half of all medical school graduates as opposed to 6% in 1960.^9,10 Our findings are consistent with the large body of evidence that describes gender-based differences in opportunities within academic medicine.

Prior studies have shown that gender inequities in academic medicine stem from a longstanding culture of sexism; these inequities are perpetuated in part by having too few visible women role models and mentors.¹¹ These factors may lead to editorial practices that favor articles written by men. In addition, women may be less likely to be invited as expert discussants if other authors have a bias of associating clinical expertise with men physicians. This is consistent with data showing that women are less likely to be invited to write commentaries in peer-reviewed journals.¹²

Gender-based differences in authorship of clinical problem-solving publications also have important implications for women in medicine. In order to address the gender gap in academic achievement, women need visible role models and mentors.¹³ Including more women authors of clinical reasoning publications has the potential to establish more women as master clinicians and role models.

There are a number of actions that can help establish more women clinical problem-solving authors. Editorial boards and editors in chief should track their review and publication practices to hold themselves accountable to author diversity. For example, JHM has announced plans to analyze author representation of women and racial and ethnic minorities, including those among first and senior authors.¹⁴ Clinicians who are assembling author teams for clinical problem-solving manuscripts should also strongly consider if an equal number of men and women have been invited to serve as specialty consultants and case discussants.

Our study has limitations. We used a python library to classify author gender based on first name (supplemented by internet searches), which may have misclassified authors and did not take into account nonbinary gender identities. Because there is no convention for assigning the expert discussant to a specific author position, we could not determine the gender distribution of the discussants. However, given that women were underrepresented among first, last, and all authors in all three journals, they are likely a minority of discussants as well.

A preponderance of male voices in clinical reasoning exercises, in which learners see clinical role models, may perpetuate a culture in which women are not seen—and do not see themselves—as having the potential to be master clinicians. Including more women in clinical reasoning exercises is an opportunity to amplify the voices of women as master clinicians and combat gender discrimination in medicine.

A large body of evidence has demonstrated significant gender disparities in academic medicine. Women are less likely than men to reach the rank of full professor, be speakers at Grand Rounds, and author studies in medical journals.^1-4 Gender-based differences in these achievements reduce the visibility of women role models in all academic medicine domains, including research, education, health systems leadership, and clinical excellence. Clinical problem-solving exercises are an opportunity to highlight the skills of women physicians as master clinicians and to establish women as clinician role models.

Clinical problem-solving exercises are highly visible demonstrations of clinical excellence in the medical literature. These exercises follow a specific format in which a clinician analyzes a diagnostic dilemma in a step-by-step manner in response to sequential segments of clinical data. The clinical problem-­solving format was introduced in 1992 in the New England Journal of Medicine and has been adopted by other journals.⁵ (The clinical problem-solving format differs from the clinical pathologic conference format, in which an entire case is presented followed by an extended analysis). Clinical problem-­solving publications are forums for learners of all levels to witness an expert clinician reason through a case.

Authorship teams on clinical reasoning exercises typically include the patient’s physician(s), specialists relevant to the final diagnosis, and the invited discussant who analyzes the clinical dilemma. Journals stipulate in the author instructions, series introductions, or standardized manuscript text of the series that the discussant be a skilled and experienced clinician.^5,6 The patient’s physicians who initiate the clinical reasoning manuscript typically select the discussant; in some journals, the series editors may provide input on discussant choice. To our knowledge, this is the only author role in the medical literature in which authors are invited specifically for their diagnostic reasoning ability.

While women have been authors on fewer original research articles and guest editorials than men have,³ the proportion of women among authors of published clinical reasoning exercises is unknown. This represents a gap in our understanding of the landscape of gender inequity in academic medicine. We sought to determine the proportion of women authors in major clinical problem-solving series and examine the change in women authorship over time.

We selected published clinical problem-solving series targeting a general medicine audience. We excluded general medicine journals in which authors were restricted to one institution or those in which the clinical problem-solving format was not a regular series. Series which met these criteria were the Clinical Problem-Solving series in the New England Journal of Medicine (NEJM), the Clinical Care Conundrums series in the Journal of Hospital Medicine (JHM), and the Exercises in Clinical Reasoning series in the Journal of General Internal Medicine (JGIM). We analyzed the proportion of women authors in each clinical reasoning series from the inaugural articles (1992 for NEJM, 2006 for JHM, and 2010 for JGIM) until July 2019. We also analyzed the change in proportion of women authors from year to year by using data up to 2018 to avoid including a partial year.

We used the gender-guesser python library⁷ to categorize the gender of first, last, and all authors based on their first names. The library uses a database of approximately 40,000 names⁸ and maps first names to the genders they are associated with across languages, classifying each name as “man,” “woman,” “mostly man,” ”mostly woman,” “androgynous,” or “unknown.” When a name is commonly associated with multiple genders, or is associated with different genders in different languages, it is classified either as mostly man, mostly woman, or androgynous. When a name is not found in the database, it is classified as unknown. For all names classified by the database as unknown, androgynous, or mostly man/mostly woman, we determined gender identities by finding the authors’ institutional webpages and consulting their listed gender pronouns. We used gender based on first name to best approximate what a reader would interpret as the author’s gender. We used gender rather than biological sex because authors may have changed their names to better express their gender identity, which may differ from sex assigned at birth.

To test for the statistical significance of changes in the proportion of women authors over time, we performed the Cochran-­Armitage trend test. A P value less than .05 was considered significant.

We analyzed 402 articles: 280 from NEJM, 83 from JHM, and 39 from JGIM. There were 1,026 authors of clinical reasoning articles from NEJM, 362 from JHM, and 168 from JGIM. The Table shows the number of total articles, total authors, and women among first, last, and all authors by journal and by year (inaugural year and 2018). Data for all years are shown in the Appendix Table.

Over the entire time period studied, the percentage of women across the three journals was lowest for last authors (28/280 [10.0%] for NEJM, 6/83 [7.2%] for JHM, and 9/39 [23.1%] for JGIM) and highest for first authors (80/280 [28.6%] for NEJM, 36/83 [43.4%] for JHM, and 13/39 [33.3%] for JGIM). The percentage of women among all authors was similar for all three journals: 224/1,026 (21.8%) for NEJM, 83/362 (22.9%) for JHM, and 36/168 (21.4%) for JGIM.

The Figure shows the change in percentage of women authors from year to year through 2018. There was a significant increase in the proportion of women first authors in NEJM (from 0/12 [0.0%] in 1992 to 4/12 [33.3%] in 2018; P < .0001) and JHM (from 2/5 [40.0%] in 2006 to 7/9 [77.8%] in 2018 P = .01). There was also a significant increase in the proportion of women among all authors in NEJM (from 0/17 [0.0%] in 1992 to 17/59 [28.8%] in 2018; P < .0001) and JHM (from 3/19 [15.8%] in 2006 to 14/37 [37.8%] in 2018; P = .005). There was no significant change in the proportion of women last authors in any of the three journals. There were no statistically significant changes in JGIM authorship over time.

Clinical problem-solving exercises provide a forum for physicians to demonstrate diagnostic reasoning skills and clinical acumen. In this study, we focused on three prominent clinical problem-solving series in general medicine journals. We found that women authors were underrepresented in each series. The percentage of women authors has increased over time, especially among first and all authors; however, there was no change in the last author position. In all three series women still constituted less than 40% of all authors and less than 25% of last authors. In comparison, women currently constitute about 40% of general internal medicine physicians, and this proportion has been rapidly growing over time; women now represent over half of all medical school graduates as opposed to 6% in 1960.^9,10 Our findings are consistent with the large body of evidence that describes gender-based differences in opportunities within academic medicine.

Prior studies have shown that gender inequities in academic medicine stem from a longstanding culture of sexism; these inequities are perpetuated in part by having too few visible women role models and mentors.¹¹ These factors may lead to editorial practices that favor articles written by men. In addition, women may be less likely to be invited as expert discussants if other authors have a bias of associating clinical expertise with men physicians. This is consistent with data showing that women are less likely to be invited to write commentaries in peer-reviewed journals.¹²

Gender-based differences in authorship of clinical problem-solving publications also have important implications for women in medicine. In order to address the gender gap in academic achievement, women need visible role models and mentors.¹³ Including more women authors of clinical reasoning publications has the potential to establish more women as master clinicians and role models.

There are a number of actions that can help establish more women clinical problem-solving authors. Editorial boards and editors in chief should track their review and publication practices to hold themselves accountable to author diversity. For example, JHM has announced plans to analyze author representation of women and racial and ethnic minorities, including those among first and senior authors.¹⁴ Clinicians who are assembling author teams for clinical problem-solving manuscripts should also strongly consider if an equal number of men and women have been invited to serve as specialty consultants and case discussants.

Our study has limitations. We used a python library to classify author gender based on first name (supplemented by internet searches), which may have misclassified authors and did not take into account nonbinary gender identities. Because there is no convention for assigning the expert discussant to a specific author position, we could not determine the gender distribution of the discussants. However, given that women were underrepresented among first, last, and all authors in all three journals, they are likely a minority of discussants as well.

A preponderance of male voices in clinical reasoning exercises, in which learners see clinical role models, may perpetuate a culture in which women are not seen—and do not see themselves—as having the potential to be master clinicians. Including more women in clinical reasoning exercises is an opportunity to amplify the voices of women as master clinicians and combat gender discrimination in medicine.

Total joint arthroplasty (TJA) procedures currently account for more Medicare expenses than any other inpatient procedure.¹ In 2015, Centers for Medicare & Medicaid Services (CMS) announced the Comprehensive Care for Joint Replacement (CJR) model in which hospitals are paid one bundled payment for all related items and services utilized within a 90-day episode of care.² Recent studies have suggested that the best opportunity to lower episode costs appears to be in the post-acute care setting and reducing readmissions.^1,3

Surgical comanagement, which provides shared management of surgical patients between surgeons and hospitalists, is typically used in orthopedic surgery, neurosurgery, vascular surgery, and general surgery.⁴ Among patients with at least one medical comorbidity, surgical comanagement decreases length of stay (LOS), 30-day readmission rate for medical causes, and the proportion of patients with at least two medical consultants.^5,6 Not all studies have shown that comanagement is beneficial. Maxwell et al found no significant differences in mortality or morbidity among hip fracture patients who did or did not receive comanagement⁷; however, comanaged patients were older and had more significant comorbidities, and there was no standard definition of comanagement among the participating institutions.

Comanagement after patients are discharged is a concept that has not been previously published but may become important with the Bundled Payments for Care Improvement initiative and high costs of excess days in acute care (EDAC). Hospitalists may be able to continue their work after discharge as part of the 90-day episode of care.⁸ TJA patients often have comorbidities, and surgical site infections and cardiovascular events are the most common causes of 30-day TJA readmissions.⁹

At our institution, 25% of TJA patients who presented to the Emergency Department (ED) within 90 days of surgery required a stay of less than 48 hours for conditions that did not require inpatient level of care. In addition, 50% of readmissions were secondary to medical complications. We also found significant variation in the management of common postoperative complications, such as postoperative fever, dislocation, anemia, and shortness of breath, especially among the different service lines caring for these patients. Therefore, we developed an Orthopedic EDAC program to reduce readmissions and to implement standardized admission algorithms and evidenced-based treatment protocols for common postoperative problems.

Setting/Participants

We included patients who underwent total knee arthroplasty (TKA), total hip arthroplasty (THA), revision TKA, or revision THA from April 1, 2017, to September 30, 2018, at an urban teaching hospital. Patients were followed for 90 days after discharge. Factors such as age, sex, race, primary payer, Medicare Severity-Diagnosis Related Group (MS-DRG), discharge destination (home, home with home health, skilled nursing facility [SNF], acute rehab, other), and EDAC LOS were compared. An interdisciplinary committee comprising representatives from orthopedic surgery, hospital medicine, emergency medicine, and case management formulated observation criteria for the Orthopedic EDAC program. To be eligible for inclusion, observation patients had to have re-presented within 90 days from their initial surgery, could not be safely discharged home immediately from the ED, and did not require inpatient level of care. Patients qualifying for orthopedic observation were assigned rooms on the orthopedic wards to maintain continuity with nursing, physical therapy/occupational therapy, and case management staff. The University of Pennsylvania institutional review board reviewed this study and determined the project to be exempt.

Study Design

The Figure shows the admitting algorithm for TJA patients re-presenting within 90 days of their surgery. The ED evaluated the eligible patients; if they were not able to discharge the patient home, they notified the orthopedic resident on call for evaluation. Eligible diagnoses for the orthopedic observation in which orthopedics was the primary service included the need for postoperative pain control, fever (without signs or symptoms of sepsis), deep venous thrombosis or pulmonary embolism without hemodynamic instability, hemodynamically stable hypovolemia, symptomatic anemia secondary to acute blood loss anemia following surgery, and postoperative nausea, vomiting, constipation, ileus, and cellulitis. Eligible diagnoses for medical observation on the Medicine service included mild exacerbations of chronic obstructive pulmonary disease (COPD), syncope, upper respiratory tract infections, chest pain, delirium, and other exacerbation of medical problems. Full admission to Orthopedics included patients with wound infections requiring surgical washout, periprosthetic fractures/hematoma requiring operative management, and wound dehiscence requiring repair. All other readmissions requiring a stay of 48 or more hours were admitted to the medical or subspecialty medical service lines (eg, internal medicine, family medicine, geriatrics, cardiology, or pulmonary critical care).

Development of Evidence-Based Algorithms

Patients who re-presented to acute care (for either observation stays or readmissions) were treated based on standardized algorithms. The interdisciplinary work group developed evidence-based evaluation and treatment plans for common postoperative problems, including postoperative fever, postoperative shortness of breath, and postoperative septic joints. This was based on a comprehensive literature review and consensus among emergency medicine, hospital medicine, and orthopedic surgery. Appendix 1 illustrates an example of a standardized algorithm for the workup of hypoxia.

Definition of Readmissions and EDAC

Readmission and observation stays were flagged on re-presentation, and reasons for readmission or observation status were analyzed. Observation cutoffs of “successful” (<48 hours) vs “unsuccessful” (≥48 hours and/or conversion to inpatient status) were based on the CMS Two-Midnight Rule in accordance with past studies.¹⁰ Readmissions were defined as patients who required an acute stay of 48 or more hours within 90 days of discharge from their original surgical stay. Patients admitted under observation status who required a stay of less than 48 hours did not count as a readmission but did count toward EDAC.

We acknowledge that our definition of Orthopedic EDAC is not the same as CMS’s definition of EDAC for other conditions such as congestive heart failure, which includes hours in observation, readmissions, and ED visits. We focused on studying and reducing days in the hospital (observation status and readmissions), and our intervention was not intended to prevent issues that would cause patients to present to the ED. Therefore, including ED visits in our operational definition of EDAC would add an unnecessary source of confounding that would bias our results toward the null hypothesis.

Data Collection and Data Analysis

The Orthopedic EDAC program was implemented on October 1, 2017, based on the above triage and treatment plans. We analyzed demographic and outcome data (readmissions, LOS, time in observation status, reason for readmission/observation status) for 6 months prior (April 1, 2017, to September 30, 2017) and 1 year after (October 1, 2017, to September 30, 2018). Microsoft Excel (Jones, 2013) was used for data analysis. Paired t-test with P < .05 was predefined as significant.

Eligible patients were identified from previous admission diagnoses obtained through Vizient, which is a collaboration of academic medical centers that maintains a hospital discharge data set (the Clinical Data Base/Resource Manager CDB/RM). It included patient demographics, discharge diagnoses, procedures, and outcomes.¹¹ The Vizient database is a respected source of data and has been used for several scholarly studies.^10-12 We queried the Vizient Clinical Data Base/Resource Manager v. 8.12.0.11 (Vizient Inc., Irvine, TX) for the following data from both before and after the program’s implementation: disposition, LOS, insurance information, gender, type of surgery, MS-DRG, and race.

The five included MS-DRGs represented major hip and knee joint replacements with and without major comorbid conditions (MCCs; MS-DRG 469 and MS-DRG 470, respectively) and revision hip or knee replacement with MCCs, with comorbid conditions (CCs), and without MCCs or CCs (MS-DRG 466, MS-DRG 467, and MS-DRG 468, respectively). MCCs included but were not limited to decubitus ulcer, severe malnutrition, quadriplegia, and end-stage renal disease. Examples of CCs included transplant patients, lymphoma, leukemia, and malignancies (except breast or prostate), based on CMS definitions.¹³

Table 1 compares the demographics of the pre-implementation and post-implementation periods. There were a total of 2,662 admissions (799 before program implementation and 1,863 after). TKA and THA patients without MCCs (MS-DRG 470) accounted for 80% of patients during both periods. In both periods, approximately 60% of patients were female, 50% of patients were White, 40% were Black, and 10% were another race. The mean age was 63.6 years old. Most patients had Medicare or commercial insurance. Discharge destinations were similar during both periods.

Table 2 illustrates how the patients who re-presented to acute care were triaged based on the algorithm described in the Figure. Among the 64 patients who re-presented during the pre-implementation period, there were no observation stays; there were 38 patients who were placed under medicine inpatient services. During post-implementation, there were 48 patients (29 on orthopedics, 17 on medicine, and 2 on other service lines) who were admitted under observation status. Twenty-three patients were discharged on observation status. Of those patients, 20 were admitted to orthopedic observation and 3 patients to medicine observation. Among the 71 patients who re-presented during the post-implementation period, 40.8% (29 patients) were admitted to inpatient orthopedic services, and 17 patients were readmitted to medicine services (24.9%). Among re-presenting patients, 70% were admitted to orthopedics inpatient and observation combined, in contrast to just 35% during the pre-implementation period.

Readmissions decreased from 6.1% during pre-implementation to 2% during post-implementation (P = .004). In addition, the LOS for patients re-presenting during post-implementation was significantly lower than it was during pre-implementation. Table 3 details the associated LOS based on study period and readmission diagnosis. The aggregate LOS for all readmissions decreased from 7.75 days to 4.73 days (P = .005). The LOS decreased across all realms of readmission diagnoses. An outlier with an LOS greater than 100 days was removed from the pre-implementation group.

Appendix 2 further looked at patients who had observation orders, reasons for observation stay, and which patients were able to be discharged on observation status. Patients with medical complications such as fever and urinary tract infection were more likely to be discharged on observation status than were patients with wound drainage or redness that was concerning for a periprosthetic joint infection.

To our knowledge, this is the first description of a published Orthopedic EDAC program using orthopedic observation, standardized admitting and treatment algorithms, and comanagement of patients who re-presented after their original surgery. The development of an Orthopedic EDAC program at our hospital with comanagement was successful in reducing readmissions, decreasing LOS for readmitted patients, and increasing continuity of care. A number of points require more elaboration.

The Orthopedic EDAC program’s improvement in both reducing readmissions and decreasing LOS for EDAC (including days for observation and readmissions) was not caused by simply shifting patients with shorter LOS from inpatient to observation because the inpatients did not have a longer LOS. We had lower Orthopedic EDAC during the post-implementation vs pre-implementation even when considering EDAC in terms of both observation and readmissions. The decrease in readmissions is not only from the patients that were discharged on observation status, but also a result of other concurrent interventions, such as encouraging discharge to home rather than to rehabilitation facilities and more rigorous preoperative optimization.

The national rates of 30- and 90-day readmissions after primary TKA were 4% (95% CI, 3.8%-4.0%) and 7% (95% CI, 6.8%-7.2%), respectively,¹⁰ and the average cost of readmission for medical causes was $22,775 for THA and $11,682 for TKA.¹² If one considers the 23 “saved readmissions” with 12 surgical complications and 11 medical complications, we “saved” roughly $591,105. Also, with the decrease in LOS for each readmission for any cause from 7.75 days to 4.73 days, the 48 readmissions had a 150 day lower LOS overall. With the average hospital day costing $2,289/day at nonprofit hospitals,¹³ there are additional cost savings of $343,350 overall. Therefore, the grand total estimated savings during this pilot was $934,455.

The decrease in post-implementation LOS vs pre-implementation LOS was likely multifactorial. The Orthopedic EDAC program improved continuity of care with orthopedic surgery and support staff (registered nurses, social workers, physical therapists) and utilized standardized protocols for work-up of common postoperative problems. These evidence-based protocols reduced waste that resulted in less testing with fewer incidental findings and side effects. The clinical history and patient circumstance did not need to be reestablished and tests did not need to be duplicated, which led to decreased LOS. Observation status allowed us to return patients to SNFs without the tedious procedure of insurance reauthorization and reevaluation by physical therapy and occupational therapy. Other factors such as “discharge before noon” and early physical therapy services ongoing during post-implementation also contributed to the decreased LOS.

Our Orthopedic EDAC program did not deliberately place patients on observation status who met full inpatient criteria solely to decrease the readmission rate. Our average LOS on observation status was 26 hours. In contrast, a study of observation stays at another tertiary academic medical center showed longer LOS: The average observation LOS was 33.3 hours with 44.4% of stays less than 24 hours and 16.5% greater than 48 hours.¹¹ The use of EDAC hours in our study, which included both observation hours and readmission hours, made our impact more than simply a shifting of readmissions to observation stays.

It is important to utilize observation stays as they were intended—ie, stays requiring less than 48 hours. Over the past 10 years, the incidence and duration of observation stays has increased significantly while readmissions have decreased.^14,15 Observation status has serious financial implications, and it is estimated that 10% of observation stays end up costing the patient more than an inpatient stay would and patients must pay 20% of services after the Part B deductible.^16,17 In addition, Medicare beneficiaries have no cap on costs for an observation stay.¹⁶ Therefore, it is important to determine which patients and diagnoses are best suited for observation status. We found that younger patients without comorbidities who came from home and presented with complications such as fever and syncope were most likely to be successfully discharged on observation status with the Orthopedic EDAC program. SNF patients on observation status in particular may have large hospital bills because they often require 3 midnight stays but do not meet inpatient level of care and are thus not covered as inpatients.¹⁸

The Orthopedic EDAC program emphasized continuity of care with the primary orthopedic surgery team. Prior to implementation, orthopedics was often not even notified when their patients were in the ED or readmitted because the prevailing practice was that once surgery was completed, the surgeon’s job was done. Post-implementation, orthopedics was called for every bundled patient re-presenting within 90 days after a TJA. The triage protocol (Figure) was agreed upon prior to implementation by orthopedics, hospital medicine, and emergency medicine. Orthopedic attendings wanted to play a larger role and more strongly influence care of their patients on re-presentation because these attendings had become frustrated with the great disparities in work-up when patients went to various other services instead. Pre-implementation, many patients admitted to the primary orthopedic service had lower acuity, and they tended to be younger and have less medical complexity. Post-implementation, primary orthopedic services took care of more patients under observation status and those with “mechanical” complications that required surgery.

It is important to note that, while comanagement is common preoperatively and immediately postoperatively, studies of comanaged patients on re-presentation have apparently not been previously published. In addition, a recent study by Maxwell et al found that patients who were comanaged perioperatively had higher mortality and morbidity than did patients who were not comanaged.⁷ These findings reflect the need for more studies to be done to best optimize the use of comanagement. Comanagement as part of the Orthopedic EDAC program at our institution was successful in keeping patients who re-presented on the orthopedic service, decreasing LOS, and decreasing readmissions.

The study has some limitations. First, this was a retrospective study, so confounding variables may not be completely eliminated. Second, our study was conducted at a single center for total joint arthroplasty and did not consider other orthopedic conditions; however, our readmission numbers and demographics are similar to past studies. Third, we had small numbers of readmissions and observation patients, which resulted in a small effect size; however, our intervention demonstrated significant changes in LOS and readmissions. Fourth, our data is based on prior billing and coding, which may not always be accurate or inclusive. Fifth, we did not have THA or TKA patients on overnight recovery status or same day surgeries during either period studied; however, we are developing infrastructure to implement this in the future. Finally, ED visit data was not readily available to us, so we were not able to calculate the traditional EDAC. Despite these limitations, this study provides an important look at how an Orthopedic EDAC program can decrease readmissions, decrease LOS, and improve continuity of care in patients undergoing TJA.

An Orthopedic EDAC program with comanagement may decrease readmissions, improve continuity of care on re-presentation, and decrease LOS for total joint arthroplasty patients who presented after initial surgery and lead to substantial cost savings.

The authors have no potential conflicts to disclose. Dr Greysen was supported by a career development award from the National Institute on Aging (K23AG045338).

Total joint arthroplasty (TJA) procedures currently account for more Medicare expenses than any other inpatient procedure.¹ In 2015, Centers for Medicare & Medicaid Services (CMS) announced the Comprehensive Care for Joint Replacement (CJR) model in which hospitals are paid one bundled payment for all related items and services utilized within a 90-day episode of care.² Recent studies have suggested that the best opportunity to lower episode costs appears to be in the post-acute care setting and reducing readmissions.^1,3

Surgical comanagement, which provides shared management of surgical patients between surgeons and hospitalists, is typically used in orthopedic surgery, neurosurgery, vascular surgery, and general surgery.⁴ Among patients with at least one medical comorbidity, surgical comanagement decreases length of stay (LOS), 30-day readmission rate for medical causes, and the proportion of patients with at least two medical consultants.^5,6 Not all studies have shown that comanagement is beneficial. Maxwell et al found no significant differences in mortality or morbidity among hip fracture patients who did or did not receive comanagement⁷; however, comanaged patients were older and had more significant comorbidities, and there was no standard definition of comanagement among the participating institutions.

Comanagement after patients are discharged is a concept that has not been previously published but may become important with the Bundled Payments for Care Improvement initiative and high costs of excess days in acute care (EDAC). Hospitalists may be able to continue their work after discharge as part of the 90-day episode of care.⁸ TJA patients often have comorbidities, and surgical site infections and cardiovascular events are the most common causes of 30-day TJA readmissions.⁹

At our institution, 25% of TJA patients who presented to the Emergency Department (ED) within 90 days of surgery required a stay of less than 48 hours for conditions that did not require inpatient level of care. In addition, 50% of readmissions were secondary to medical complications. We also found significant variation in the management of common postoperative complications, such as postoperative fever, dislocation, anemia, and shortness of breath, especially among the different service lines caring for these patients. Therefore, we developed an Orthopedic EDAC program to reduce readmissions and to implement standardized admission algorithms and evidenced-based treatment protocols for common postoperative problems.

Setting/Participants

We included patients who underwent total knee arthroplasty (TKA), total hip arthroplasty (THA), revision TKA, or revision THA from April 1, 2017, to September 30, 2018, at an urban teaching hospital. Patients were followed for 90 days after discharge. Factors such as age, sex, race, primary payer, Medicare Severity-Diagnosis Related Group (MS-DRG), discharge destination (home, home with home health, skilled nursing facility [SNF], acute rehab, other), and EDAC LOS were compared. An interdisciplinary committee comprising representatives from orthopedic surgery, hospital medicine, emergency medicine, and case management formulated observation criteria for the Orthopedic EDAC program. To be eligible for inclusion, observation patients had to have re-presented within 90 days from their initial surgery, could not be safely discharged home immediately from the ED, and did not require inpatient level of care. Patients qualifying for orthopedic observation were assigned rooms on the orthopedic wards to maintain continuity with nursing, physical therapy/occupational therapy, and case management staff. The University of Pennsylvania institutional review board reviewed this study and determined the project to be exempt.

Study Design

The Figure shows the admitting algorithm for TJA patients re-presenting within 90 days of their surgery. The ED evaluated the eligible patients; if they were not able to discharge the patient home, they notified the orthopedic resident on call for evaluation. Eligible diagnoses for the orthopedic observation in which orthopedics was the primary service included the need for postoperative pain control, fever (without signs or symptoms of sepsis), deep venous thrombosis or pulmonary embolism without hemodynamic instability, hemodynamically stable hypovolemia, symptomatic anemia secondary to acute blood loss anemia following surgery, and postoperative nausea, vomiting, constipation, ileus, and cellulitis. Eligible diagnoses for medical observation on the Medicine service included mild exacerbations of chronic obstructive pulmonary disease (COPD), syncope, upper respiratory tract infections, chest pain, delirium, and other exacerbation of medical problems. Full admission to Orthopedics included patients with wound infections requiring surgical washout, periprosthetic fractures/hematoma requiring operative management, and wound dehiscence requiring repair. All other readmissions requiring a stay of 48 or more hours were admitted to the medical or subspecialty medical service lines (eg, internal medicine, family medicine, geriatrics, cardiology, or pulmonary critical care).

Development of Evidence-Based Algorithms

Patients who re-presented to acute care (for either observation stays or readmissions) were treated based on standardized algorithms. The interdisciplinary work group developed evidence-based evaluation and treatment plans for common postoperative problems, including postoperative fever, postoperative shortness of breath, and postoperative septic joints. This was based on a comprehensive literature review and consensus among emergency medicine, hospital medicine, and orthopedic surgery. Appendix 1 illustrates an example of a standardized algorithm for the workup of hypoxia.

Definition of Readmissions and EDAC

Readmission and observation stays were flagged on re-presentation, and reasons for readmission or observation status were analyzed. Observation cutoffs of “successful” (<48 hours) vs “unsuccessful” (≥48 hours and/or conversion to inpatient status) were based on the CMS Two-Midnight Rule in accordance with past studies.¹⁰ Readmissions were defined as patients who required an acute stay of 48 or more hours within 90 days of discharge from their original surgical stay. Patients admitted under observation status who required a stay of less than 48 hours did not count as a readmission but did count toward EDAC.

We acknowledge that our definition of Orthopedic EDAC is not the same as CMS’s definition of EDAC for other conditions such as congestive heart failure, which includes hours in observation, readmissions, and ED visits. We focused on studying and reducing days in the hospital (observation status and readmissions), and our intervention was not intended to prevent issues that would cause patients to present to the ED. Therefore, including ED visits in our operational definition of EDAC would add an unnecessary source of confounding that would bias our results toward the null hypothesis.

Data Collection and Data Analysis

The Orthopedic EDAC program was implemented on October 1, 2017, based on the above triage and treatment plans. We analyzed demographic and outcome data (readmissions, LOS, time in observation status, reason for readmission/observation status) for 6 months prior (April 1, 2017, to September 30, 2017) and 1 year after (October 1, 2017, to September 30, 2018). Microsoft Excel (Jones, 2013) was used for data analysis. Paired t-test with P < .05 was predefined as significant.

Eligible patients were identified from previous admission diagnoses obtained through Vizient, which is a collaboration of academic medical centers that maintains a hospital discharge data set (the Clinical Data Base/Resource Manager CDB/RM). It included patient demographics, discharge diagnoses, procedures, and outcomes.¹¹ The Vizient database is a respected source of data and has been used for several scholarly studies.^10-12 We queried the Vizient Clinical Data Base/Resource Manager v. 8.12.0.11 (Vizient Inc., Irvine, TX) for the following data from both before and after the program’s implementation: disposition, LOS, insurance information, gender, type of surgery, MS-DRG, and race.

The five included MS-DRGs represented major hip and knee joint replacements with and without major comorbid conditions (MCCs; MS-DRG 469 and MS-DRG 470, respectively) and revision hip or knee replacement with MCCs, with comorbid conditions (CCs), and without MCCs or CCs (MS-DRG 466, MS-DRG 467, and MS-DRG 468, respectively). MCCs included but were not limited to decubitus ulcer, severe malnutrition, quadriplegia, and end-stage renal disease. Examples of CCs included transplant patients, lymphoma, leukemia, and malignancies (except breast or prostate), based on CMS definitions.¹³

Table 1 compares the demographics of the pre-implementation and post-implementation periods. There were a total of 2,662 admissions (799 before program implementation and 1,863 after). TKA and THA patients without MCCs (MS-DRG 470) accounted for 80% of patients during both periods. In both periods, approximately 60% of patients were female, 50% of patients were White, 40% were Black, and 10% were another race. The mean age was 63.6 years old. Most patients had Medicare or commercial insurance. Discharge destinations were similar during both periods.

Table 2 illustrates how the patients who re-presented to acute care were triaged based on the algorithm described in the Figure. Among the 64 patients who re-presented during the pre-implementation period, there were no observation stays; there were 38 patients who were placed under medicine inpatient services. During post-implementation, there were 48 patients (29 on orthopedics, 17 on medicine, and 2 on other service lines) who were admitted under observation status. Twenty-three patients were discharged on observation status. Of those patients, 20 were admitted to orthopedic observation and 3 patients to medicine observation. Among the 71 patients who re-presented during the post-implementation period, 40.8% (29 patients) were admitted to inpatient orthopedic services, and 17 patients were readmitted to medicine services (24.9%). Among re-presenting patients, 70% were admitted to orthopedics inpatient and observation combined, in contrast to just 35% during the pre-implementation period.

Readmissions decreased from 6.1% during pre-implementation to 2% during post-implementation (P = .004). In addition, the LOS for patients re-presenting during post-implementation was significantly lower than it was during pre-implementation. Table 3 details the associated LOS based on study period and readmission diagnosis. The aggregate LOS for all readmissions decreased from 7.75 days to 4.73 days (P = .005). The LOS decreased across all realms of readmission diagnoses. An outlier with an LOS greater than 100 days was removed from the pre-implementation group.

Appendix 2 further looked at patients who had observation orders, reasons for observation stay, and which patients were able to be discharged on observation status. Patients with medical complications such as fever and urinary tract infection were more likely to be discharged on observation status than were patients with wound drainage or redness that was concerning for a periprosthetic joint infection.

To our knowledge, this is the first description of a published Orthopedic EDAC program using orthopedic observation, standardized admitting and treatment algorithms, and comanagement of patients who re-presented after their original surgery. The development of an Orthopedic EDAC program at our hospital with comanagement was successful in reducing readmissions, decreasing LOS for readmitted patients, and increasing continuity of care. A number of points require more elaboration.

The Orthopedic EDAC program’s improvement in both reducing readmissions and decreasing LOS for EDAC (including days for observation and readmissions) was not caused by simply shifting patients with shorter LOS from inpatient to observation because the inpatients did not have a longer LOS. We had lower Orthopedic EDAC during the post-implementation vs pre-implementation even when considering EDAC in terms of both observation and readmissions. The decrease in readmissions is not only from the patients that were discharged on observation status, but also a result of other concurrent interventions, such as encouraging discharge to home rather than to rehabilitation facilities and more rigorous preoperative optimization.

The national rates of 30- and 90-day readmissions after primary TKA were 4% (95% CI, 3.8%-4.0%) and 7% (95% CI, 6.8%-7.2%), respectively,¹⁰ and the average cost of readmission for medical causes was $22,775 for THA and $11,682 for TKA.¹² If one considers the 23 “saved readmissions” with 12 surgical complications and 11 medical complications, we “saved” roughly $591,105. Also, with the decrease in LOS for each readmission for any cause from 7.75 days to 4.73 days, the 48 readmissions had a 150 day lower LOS overall. With the average hospital day costing $2,289/day at nonprofit hospitals,¹³ there are additional cost savings of $343,350 overall. Therefore, the grand total estimated savings during this pilot was $934,455.

The decrease in post-implementation LOS vs pre-implementation LOS was likely multifactorial. The Orthopedic EDAC program improved continuity of care with orthopedic surgery and support staff (registered nurses, social workers, physical therapists) and utilized standardized protocols for work-up of common postoperative problems. These evidence-based protocols reduced waste that resulted in less testing with fewer incidental findings and side effects. The clinical history and patient circumstance did not need to be reestablished and tests did not need to be duplicated, which led to decreased LOS. Observation status allowed us to return patients to SNFs without the tedious procedure of insurance reauthorization and reevaluation by physical therapy and occupational therapy. Other factors such as “discharge before noon” and early physical therapy services ongoing during post-implementation also contributed to the decreased LOS.

Our Orthopedic EDAC program did not deliberately place patients on observation status who met full inpatient criteria solely to decrease the readmission rate. Our average LOS on observation status was 26 hours. In contrast, a study of observation stays at another tertiary academic medical center showed longer LOS: The average observation LOS was 33.3 hours with 44.4% of stays less than 24 hours and 16.5% greater than 48 hours.¹¹ The use of EDAC hours in our study, which included both observation hours and readmission hours, made our impact more than simply a shifting of readmissions to observation stays.

It is important to utilize observation stays as they were intended—ie, stays requiring less than 48 hours. Over the past 10 years, the incidence and duration of observation stays has increased significantly while readmissions have decreased.^14,15 Observation status has serious financial implications, and it is estimated that 10% of observation stays end up costing the patient more than an inpatient stay would and patients must pay 20% of services after the Part B deductible.^16,17 In addition, Medicare beneficiaries have no cap on costs for an observation stay.¹⁶ Therefore, it is important to determine which patients and diagnoses are best suited for observation status. We found that younger patients without comorbidities who came from home and presented with complications such as fever and syncope were most likely to be successfully discharged on observation status with the Orthopedic EDAC program. SNF patients on observation status in particular may have large hospital bills because they often require 3 midnight stays but do not meet inpatient level of care and are thus not covered as inpatients.¹⁸

The Orthopedic EDAC program emphasized continuity of care with the primary orthopedic surgery team. Prior to implementation, orthopedics was often not even notified when their patients were in the ED or readmitted because the prevailing practice was that once surgery was completed, the surgeon’s job was done. Post-implementation, orthopedics was called for every bundled patient re-presenting within 90 days after a TJA. The triage protocol (Figure) was agreed upon prior to implementation by orthopedics, hospital medicine, and emergency medicine. Orthopedic attendings wanted to play a larger role and more strongly influence care of their patients on re-presentation because these attendings had become frustrated with the great disparities in work-up when patients went to various other services instead. Pre-implementation, many patients admitted to the primary orthopedic service had lower acuity, and they tended to be younger and have less medical complexity. Post-implementation, primary orthopedic services took care of more patients under observation status and those with “mechanical” complications that required surgery.

It is important to note that, while comanagement is common preoperatively and immediately postoperatively, studies of comanaged patients on re-presentation have apparently not been previously published. In addition, a recent study by Maxwell et al found that patients who were comanaged perioperatively had higher mortality and morbidity than did patients who were not comanaged.⁷ These findings reflect the need for more studies to be done to best optimize the use of comanagement. Comanagement as part of the Orthopedic EDAC program at our institution was successful in keeping patients who re-presented on the orthopedic service, decreasing LOS, and decreasing readmissions.

The study has some limitations. First, this was a retrospective study, so confounding variables may not be completely eliminated. Second, our study was conducted at a single center for total joint arthroplasty and did not consider other orthopedic conditions; however, our readmission numbers and demographics are similar to past studies. Third, we had small numbers of readmissions and observation patients, which resulted in a small effect size; however, our intervention demonstrated significant changes in LOS and readmissions. Fourth, our data is based on prior billing and coding, which may not always be accurate or inclusive. Fifth, we did not have THA or TKA patients on overnight recovery status or same day surgeries during either period studied; however, we are developing infrastructure to implement this in the future. Finally, ED visit data was not readily available to us, so we were not able to calculate the traditional EDAC. Despite these limitations, this study provides an important look at how an Orthopedic EDAC program can decrease readmissions, decrease LOS, and improve continuity of care in patients undergoing TJA.

An Orthopedic EDAC program with comanagement may decrease readmissions, improve continuity of care on re-presentation, and decrease LOS for total joint arthroplasty patients who presented after initial surgery and lead to substantial cost savings.

The authors have no potential conflicts to disclose. Dr Greysen was supported by a career development award from the National Institute on Aging (K23AG045338).

Total joint arthroplasty (TJA) procedures currently account for more Medicare expenses than any other inpatient procedure.¹ In 2015, Centers for Medicare & Medicaid Services (CMS) announced the Comprehensive Care for Joint Replacement (CJR) model in which hospitals are paid one bundled payment for all related items and services utilized within a 90-day episode of care.² Recent studies have suggested that the best opportunity to lower episode costs appears to be in the post-acute care setting and reducing readmissions.^1,3

Surgical comanagement, which provides shared management of surgical patients between surgeons and hospitalists, is typically used in orthopedic surgery, neurosurgery, vascular surgery, and general surgery.⁴ Among patients with at least one medical comorbidity, surgical comanagement decreases length of stay (LOS), 30-day readmission rate for medical causes, and the proportion of patients with at least two medical consultants.^5,6 Not all studies have shown that comanagement is beneficial. Maxwell et al found no significant differences in mortality or morbidity among hip fracture patients who did or did not receive comanagement⁷; however, comanaged patients were older and had more significant comorbidities, and there was no standard definition of comanagement among the participating institutions.

Comanagement after patients are discharged is a concept that has not been previously published but may become important with the Bundled Payments for Care Improvement initiative and high costs of excess days in acute care (EDAC). Hospitalists may be able to continue their work after discharge as part of the 90-day episode of care.⁸ TJA patients often have comorbidities, and surgical site infections and cardiovascular events are the most common causes of 30-day TJA readmissions.⁹

At our institution, 25% of TJA patients who presented to the Emergency Department (ED) within 90 days of surgery required a stay of less than 48 hours for conditions that did not require inpatient level of care. In addition, 50% of readmissions were secondary to medical complications. We also found significant variation in the management of common postoperative complications, such as postoperative fever, dislocation, anemia, and shortness of breath, especially among the different service lines caring for these patients. Therefore, we developed an Orthopedic EDAC program to reduce readmissions and to implement standardized admission algorithms and evidenced-based treatment protocols for common postoperative problems.

Setting/Participants

We included patients who underwent total knee arthroplasty (TKA), total hip arthroplasty (THA), revision TKA, or revision THA from April 1, 2017, to September 30, 2018, at an urban teaching hospital. Patients were followed for 90 days after discharge. Factors such as age, sex, race, primary payer, Medicare Severity-Diagnosis Related Group (MS-DRG), discharge destination (home, home with home health, skilled nursing facility [SNF], acute rehab, other), and EDAC LOS were compared. An interdisciplinary committee comprising representatives from orthopedic surgery, hospital medicine, emergency medicine, and case management formulated observation criteria for the Orthopedic EDAC program. To be eligible for inclusion, observation patients had to have re-presented within 90 days from their initial surgery, could not be safely discharged home immediately from the ED, and did not require inpatient level of care. Patients qualifying for orthopedic observation were assigned rooms on the orthopedic wards to maintain continuity with nursing, physical therapy/occupational therapy, and case management staff. The University of Pennsylvania institutional review board reviewed this study and determined the project to be exempt.

Study Design

The Figure shows the admitting algorithm for TJA patients re-presenting within 90 days of their surgery. The ED evaluated the eligible patients; if they were not able to discharge the patient home, they notified the orthopedic resident on call for evaluation. Eligible diagnoses for the orthopedic observation in which orthopedics was the primary service included the need for postoperative pain control, fever (without signs or symptoms of sepsis), deep venous thrombosis or pulmonary embolism without hemodynamic instability, hemodynamically stable hypovolemia, symptomatic anemia secondary to acute blood loss anemia following surgery, and postoperative nausea, vomiting, constipation, ileus, and cellulitis. Eligible diagnoses for medical observation on the Medicine service included mild exacerbations of chronic obstructive pulmonary disease (COPD), syncope, upper respiratory tract infections, chest pain, delirium, and other exacerbation of medical problems. Full admission to Orthopedics included patients with wound infections requiring surgical washout, periprosthetic fractures/hematoma requiring operative management, and wound dehiscence requiring repair. All other readmissions requiring a stay of 48 or more hours were admitted to the medical or subspecialty medical service lines (eg, internal medicine, family medicine, geriatrics, cardiology, or pulmonary critical care).

Development of Evidence-Based Algorithms

Patients who re-presented to acute care (for either observation stays or readmissions) were treated based on standardized algorithms. The interdisciplinary work group developed evidence-based evaluation and treatment plans for common postoperative problems, including postoperative fever, postoperative shortness of breath, and postoperative septic joints. This was based on a comprehensive literature review and consensus among emergency medicine, hospital medicine, and orthopedic surgery. Appendix 1 illustrates an example of a standardized algorithm for the workup of hypoxia.

Definition of Readmissions and EDAC

Readmission and observation stays were flagged on re-presentation, and reasons for readmission or observation status were analyzed. Observation cutoffs of “successful” (<48 hours) vs “unsuccessful” (≥48 hours and/or conversion to inpatient status) were based on the CMS Two-Midnight Rule in accordance with past studies.¹⁰ Readmissions were defined as patients who required an acute stay of 48 or more hours within 90 days of discharge from their original surgical stay. Patients admitted under observation status who required a stay of less than 48 hours did not count as a readmission but did count toward EDAC.

We acknowledge that our definition of Orthopedic EDAC is not the same as CMS’s definition of EDAC for other conditions such as congestive heart failure, which includes hours in observation, readmissions, and ED visits. We focused on studying and reducing days in the hospital (observation status and readmissions), and our intervention was not intended to prevent issues that would cause patients to present to the ED. Therefore, including ED visits in our operational definition of EDAC would add an unnecessary source of confounding that would bias our results toward the null hypothesis.

Data Collection and Data Analysis

The Orthopedic EDAC program was implemented on October 1, 2017, based on the above triage and treatment plans. We analyzed demographic and outcome data (readmissions, LOS, time in observation status, reason for readmission/observation status) for 6 months prior (April 1, 2017, to September 30, 2017) and 1 year after (October 1, 2017, to September 30, 2018). Microsoft Excel (Jones, 2013) was used for data analysis. Paired t-test with P < .05 was predefined as significant.

Eligible patients were identified from previous admission diagnoses obtained through Vizient, which is a collaboration of academic medical centers that maintains a hospital discharge data set (the Clinical Data Base/Resource Manager CDB/RM). It included patient demographics, discharge diagnoses, procedures, and outcomes.¹¹ The Vizient database is a respected source of data and has been used for several scholarly studies.^10-12 We queried the Vizient Clinical Data Base/Resource Manager v. 8.12.0.11 (Vizient Inc., Irvine, TX) for the following data from both before and after the program’s implementation: disposition, LOS, insurance information, gender, type of surgery, MS-DRG, and race.

The five included MS-DRGs represented major hip and knee joint replacements with and without major comorbid conditions (MCCs; MS-DRG 469 and MS-DRG 470, respectively) and revision hip or knee replacement with MCCs, with comorbid conditions (CCs), and without MCCs or CCs (MS-DRG 466, MS-DRG 467, and MS-DRG 468, respectively). MCCs included but were not limited to decubitus ulcer, severe malnutrition, quadriplegia, and end-stage renal disease. Examples of CCs included transplant patients, lymphoma, leukemia, and malignancies (except breast or prostate), based on CMS definitions.¹³

Table 1 compares the demographics of the pre-implementation and post-implementation periods. There were a total of 2,662 admissions (799 before program implementation and 1,863 after). TKA and THA patients without MCCs (MS-DRG 470) accounted for 80% of patients during both periods. In both periods, approximately 60% of patients were female, 50% of patients were White, 40% were Black, and 10% were another race. The mean age was 63.6 years old. Most patients had Medicare or commercial insurance. Discharge destinations were similar during both periods.

Table 2 illustrates how the patients who re-presented to acute care were triaged based on the algorithm described in the Figure. Among the 64 patients who re-presented during the pre-implementation period, there were no observation stays; there were 38 patients who were placed under medicine inpatient services. During post-implementation, there were 48 patients (29 on orthopedics, 17 on medicine, and 2 on other service lines) who were admitted under observation status. Twenty-three patients were discharged on observation status. Of those patients, 20 were admitted to orthopedic observation and 3 patients to medicine observation. Among the 71 patients who re-presented during the post-implementation period, 40.8% (29 patients) were admitted to inpatient orthopedic services, and 17 patients were readmitted to medicine services (24.9%). Among re-presenting patients, 70% were admitted to orthopedics inpatient and observation combined, in contrast to just 35% during the pre-implementation period.

Readmissions decreased from 6.1% during pre-implementation to 2% during post-implementation (P = .004). In addition, the LOS for patients re-presenting during post-implementation was significantly lower than it was during pre-implementation. Table 3 details the associated LOS based on study period and readmission diagnosis. The aggregate LOS for all readmissions decreased from 7.75 days to 4.73 days (P = .005). The LOS decreased across all realms of readmission diagnoses. An outlier with an LOS greater than 100 days was removed from the pre-implementation group.

Appendix 2 further looked at patients who had observation orders, reasons for observation stay, and which patients were able to be discharged on observation status. Patients with medical complications such as fever and urinary tract infection were more likely to be discharged on observation status than were patients with wound drainage or redness that was concerning for a periprosthetic joint infection.

To our knowledge, this is the first description of a published Orthopedic EDAC program using orthopedic observation, standardized admitting and treatment algorithms, and comanagement of patients who re-presented after their original surgery. The development of an Orthopedic EDAC program at our hospital with comanagement was successful in reducing readmissions, decreasing LOS for readmitted patients, and increasing continuity of care. A number of points require more elaboration.

The Orthopedic EDAC program’s improvement in both reducing readmissions and decreasing LOS for EDAC (including days for observation and readmissions) was not caused by simply shifting patients with shorter LOS from inpatient to observation because the inpatients did not have a longer LOS. We had lower Orthopedic EDAC during the post-implementation vs pre-implementation even when considering EDAC in terms of both observation and readmissions. The decrease in readmissions is not only from the patients that were discharged on observation status, but also a result of other concurrent interventions, such as encouraging discharge to home rather than to rehabilitation facilities and more rigorous preoperative optimization.

The national rates of 30- and 90-day readmissions after primary TKA were 4% (95% CI, 3.8%-4.0%) and 7% (95% CI, 6.8%-7.2%), respectively,¹⁰ and the average cost of readmission for medical causes was $22,775 for THA and $11,682 for TKA.¹² If one considers the 23 “saved readmissions” with 12 surgical complications and 11 medical complications, we “saved” roughly $591,105. Also, with the decrease in LOS for each readmission for any cause from 7.75 days to 4.73 days, the 48 readmissions had a 150 day lower LOS overall. With the average hospital day costing $2,289/day at nonprofit hospitals,¹³ there are additional cost savings of $343,350 overall. Therefore, the grand total estimated savings during this pilot was $934,455.

The decrease in post-implementation LOS vs pre-implementation LOS was likely multifactorial. The Orthopedic EDAC program improved continuity of care with orthopedic surgery and support staff (registered nurses, social workers, physical therapists) and utilized standardized protocols for work-up of common postoperative problems. These evidence-based protocols reduced waste that resulted in less testing with fewer incidental findings and side effects. The clinical history and patient circumstance did not need to be reestablished and tests did not need to be duplicated, which led to decreased LOS. Observation status allowed us to return patients to SNFs without the tedious procedure of insurance reauthorization and reevaluation by physical therapy and occupational therapy. Other factors such as “discharge before noon” and early physical therapy services ongoing during post-implementation also contributed to the decreased LOS.

Our Orthopedic EDAC program did not deliberately place patients on observation status who met full inpatient criteria solely to decrease the readmission rate. Our average LOS on observation status was 26 hours. In contrast, a study of observation stays at another tertiary academic medical center showed longer LOS: The average observation LOS was 33.3 hours with 44.4% of stays less than 24 hours and 16.5% greater than 48 hours.¹¹ The use of EDAC hours in our study, which included both observation hours and readmission hours, made our impact more than simply a shifting of readmissions to observation stays.

It is important to utilize observation stays as they were intended—ie, stays requiring less than 48 hours. Over the past 10 years, the incidence and duration of observation stays has increased significantly while readmissions have decreased.^14,15 Observation status has serious financial implications, and it is estimated that 10% of observation stays end up costing the patient more than an inpatient stay would and patients must pay 20% of services after the Part B deductible.^16,17 In addition, Medicare beneficiaries have no cap on costs for an observation stay.¹⁶ Therefore, it is important to determine which patients and diagnoses are best suited for observation status. We found that younger patients without comorbidities who came from home and presented with complications such as fever and syncope were most likely to be successfully discharged on observation status with the Orthopedic EDAC program. SNF patients on observation status in particular may have large hospital bills because they often require 3 midnight stays but do not meet inpatient level of care and are thus not covered as inpatients.¹⁸

The Orthopedic EDAC program emphasized continuity of care with the primary orthopedic surgery team. Prior to implementation, orthopedics was often not even notified when their patients were in the ED or readmitted because the prevailing practice was that once surgery was completed, the surgeon’s job was done. Post-implementation, orthopedics was called for every bundled patient re-presenting within 90 days after a TJA. The triage protocol (Figure) was agreed upon prior to implementation by orthopedics, hospital medicine, and emergency medicine. Orthopedic attendings wanted to play a larger role and more strongly influence care of their patients on re-presentation because these attendings had become frustrated with the great disparities in work-up when patients went to various other services instead. Pre-implementation, many patients admitted to the primary orthopedic service had lower acuity, and they tended to be younger and have less medical complexity. Post-implementation, primary orthopedic services took care of more patients under observation status and those with “mechanical” complications that required surgery.

It is important to note that, while comanagement is common preoperatively and immediately postoperatively, studies of comanaged patients on re-presentation have apparently not been previously published. In addition, a recent study by Maxwell et al found that patients who were comanaged perioperatively had higher mortality and morbidity than did patients who were not comanaged.⁷ These findings reflect the need for more studies to be done to best optimize the use of comanagement. Comanagement as part of the Orthopedic EDAC program at our institution was successful in keeping patients who re-presented on the orthopedic service, decreasing LOS, and decreasing readmissions.

The study has some limitations. First, this was a retrospective study, so confounding variables may not be completely eliminated. Second, our study was conducted at a single center for total joint arthroplasty and did not consider other orthopedic conditions; however, our readmission numbers and demographics are similar to past studies. Third, we had small numbers of readmissions and observation patients, which resulted in a small effect size; however, our intervention demonstrated significant changes in LOS and readmissions. Fourth, our data is based on prior billing and coding, which may not always be accurate or inclusive. Fifth, we did not have THA or TKA patients on overnight recovery status or same day surgeries during either period studied; however, we are developing infrastructure to implement this in the future. Finally, ED visit data was not readily available to us, so we were not able to calculate the traditional EDAC. Despite these limitations, this study provides an important look at how an Orthopedic EDAC program can decrease readmissions, decrease LOS, and improve continuity of care in patients undergoing TJA.

An Orthopedic EDAC program with comanagement may decrease readmissions, improve continuity of care on re-presentation, and decrease LOS for total joint arthroplasty patients who presented after initial surgery and lead to substantial cost savings.

The authors have no potential conflicts to disclose. Dr Greysen was supported by a career development award from the National Institute on Aging (K23AG045338).

The demographic composition of physicians has shifted dramatically in the last five decades. The number of women matriculating into medical school rose from 6% in the 1960s¹ to 52% in 2019²; women accounted for 39% of full-time faculty in 2015.³ Despite this evolution of the physician gender array, many challenges remain.⁴ Women represented only 35% of all associate professors and 22% of full professors in 2015.³ Women experience gender-based discrimination, hostility, and unconscious bias as medical trainees^5-9 and as attending physicians^10-13 with significant deleterious effects including burnout and suicidal thoughts.¹⁴ While types of gender-based challenges are well described in the literature, strategies to navigate and respond to these challenges are less understood.

The approaches and techniques of exemplary teaching attending physicians (hereafter referred to as “attendings”) have previously been reported from groups of predominantly male attendings.^15-18 Because of gender-based challenges female physicians face that lead them to reduce their effort or leave the medical field,¹⁹ there is concern that prior scholarship in effective teaching may not adequately capture the approaches and techniques of female attendings. To our knowledge, no studies have specifically examined female attendings. Therefore, we sought to explore the lived experiences of six female attendings with particular emphasis on how they navigate and respond to gender-based challenges in clinical environments.

Study Design and Sampling

This was a multisite study using an exploratory qualitative approach to inquiry. We aimed to examine techniques, approaches, and attitudes of outstanding general medicine teaching attendings among groups previously not well represented (ie, women and self-identified underrepresented minorities [URMs] in medicine). URM was defined by the Association of American Medical Colleges as “those racial and ethnic populations that are underrepresented in the medical profession relative to their numbers in the general population.”²⁰ A modified snowball sampling approach²¹ was employed to identify attendings as delineated below.

To maintain quality while guaranteeing diversity in geography and population, potential institutions in which to observe attendings were determined by first creating the following lists: The top 20 hospitals in the U.S. News & World Report’s 2017-2018 Best Hospitals Honor Roll,²² top-rated institutions by Doximity in each geographic region and among rural training sites,²³ and four historically Black colleges and universities (HBCUs) with medical schools. Institutions visited during a previous similar study¹⁶ were excluded. Next, the list was narrowed to 25 by randomly selecting five in each main geographic region and five rural institutions. These were combined with all four HBCUs to create a final list of 29 institutions.

Next, division of hospital medicine chiefs (and/or general medicine chiefs) and internal medicine residency directors at each of these 29 institutions were asked to nominate exemplary attendings, particularly those who identified as women and URMs. Twelve attendings who were themselves observed in a previous study¹⁶ were also asked for nominations. Finally, recommendations were sought from leaders of relevant American Medical Association member groups.²⁴

Using this sampling method, 43 physicians were identified. An internet search was conducted to identify individual characteristics including medical education, training, clinical and research interests, and educational awards. These characteristics were considered and discussed by the research team. Preference was given to those attendings nominated by more than one individual (n = 3), those who had received teaching awards, and those with interests involving women in medicine. Research team members narrowed the list to seven attendings who were contacted via email and invited to participate. One did not respond, while six agreed to participate. The six attendings identified current team members who would be rounding on the visit date. Attendings were asked to recommend 6-10 former learners; we contacted these former learners and invited them to participate. Former learners were included to understand lasting effects from their attendings.

Data Collection

Observations

All 1-day site visits were conducted by two research team members, a physician (NH) and a qualitative research specialist (MQ). In four visits, an additional author accompanied the research team. In order to ensure consistency and diversity in perspectives, all authors attended at least one visit. These occurred between April 16 and August 28, 2018. Each visit began with direct observation of attendings (n = 6) and current learners (n = 24) during inpatient general medicine teaching rounds. Each researcher unobtrusively recorded their observations via handwritten, open field notes, paying particular attention to group interactions, teaching approach, conversations within and peripheral to the team, and patient–team interactions. After each visit, researchers met to compare and combine field notes.

Interviews and Focus Groups

Researchers then conducted individual, semistructured interviews with attendings and focus groups with current (n = 21) and former (n = 17) learners. Focus groups with learners varied in size from two to five participants. Former learners were occasionally not available for on-site focus groups and were interviewed separately by telephone after the visit. The interview guide for attendings (Appendix 1) was adapted from the prior study¹⁶ but expanded with questions related to experiences, challenges, and approaches of female and URM physicians. A separate guide was used to facilitate focus groups with learners (Appendix 1). Three current learners were unable to participate in focus groups due to clinical duties. All interviews and focus groups were audio recorded and transcribed.

This study was determined to be exempt by the University of Michigan Institutional Review Board. All participants were informed that their participation was completely voluntary and that they could terminate their involvement at any time.

Data Analysis

Data were analyzed using a content analysis approach.²⁵ Inductive coding was used to identify codes derived from the data. Two team members (MQ and MH) independently coded the first transcript to develop a codebook, then met to compare and discuss codes. Codes and definitions were entered into the codebook. These team members continued coding five additional transcripts, meeting to compare codes, discussing any discrepancies until agreement was reached, adding new codes identified, and ensuring consistent code application. They reviewed prior transcripts and recoded if necessary. Once no new codes were identified, one team member coded the remaining transcripts. The same codebook was used to code field note documents using the same iterative process. After all qualitative data were coded and verified, they were entered into NVivo 10. Code reports were generated and reviewed by three team members to identify themes and check for coding consistency.

Role of the Funding Source

This study received no external funding.

We examined six exemplary attendings through direct observation of rounds and individual interviews. We also discussed these attendings with 21 current learners and 17 former learners (Appendix 2). All attendings self-identified as female. The group was diverse in terms of race/ethnicity, with three identifying as Black or African American, two as Asian, and one as White or Caucasian. Levels of experience as an attending ranged from 8 to 20 years (mean, 15.3 years). At the time of observation, two were professors and four were associate professors. The group included all three attendings who had been nominated by more than one individual, and all six had won multiple teaching awards. The observation sites represented several areas of the United States (Table 1).

The coded interview data and field notes were categorized into three broad overlapping themes based on strategies our attendings used to respond to gender-based challenges. The following sections describe types of challenges faced by female attendings along with specific strategies they employed to actively position themselves as physician team leaders, manage gender-based stereotypes and perceptions, and identify and embrace their unique qualities. Illustrative quotations or observations that further elucidate meaning are provided.

Female Attendings Actively Position Themselves as Physician Team Leaders

Our attendings frequently stated that they were assumed to be other healthcare provider types, such as nurses or physical therapists, and that these assumptions originated from patients, faculty, and staff (Table 2). Attending 3 commented, “I think every woman in this role has been mistaken for a different caretaker role, so lots of requests for nursing help. I’m sure I have taken more patients off of bed pans and brought more cups of water than maybe some of my male counterparts.” Some attendings responded to this challenge with the strategy of routinely wearing a white coat during rounds and patient encounters. This external visual cue was seen as a necessary reminder of the female attending role.

We found that patients and healthcare providers often believe teams are led by men, leading to a feeling of invisibility for female attendings. One current learner remarked, “If it was a new patient, more than likely, if we had a female attending, the patient’s eyes would always divert to the male physician.” This was not limited to patients. Attending 6 remembered comments from her consultants including, “‘Who is your attending? Let me talk with them,’ kind of assuming that I’m not the person making the decisions.” Female attendings would respond to this challenge by clearly introducing team members, including themselves, with roles and responsibilities. At times, this would require reintroductions and redirection if individuals still misidentified female team members.

Female attendings’ decision-making and thought processes were frequently second-guessed. This would often lead to power struggles with consultants, nurses, and learners. Attending 5 commented, “Even in residency, I felt this sometimes adversarial relationship with...female nurses where they would treat [female attendings] differently...questioning our decisions.” Female attendings would respond to this challenge by asserting themselves and demonstrating confidence with colleagues and at the bedside. This was an active process for women, as one former learner described: “[Female] attendings have to be a little bit more ‘on’—whatever ‘on’ is—more forceful, more direct....There is more slack given to a male attending.”

Female Attendings Consciously Work to Manage Gender-Based Stereotypes and Perceptions

Our attendings navigated gender-based stereotypes and perceptions, ranging from subtle microaggressions to overt sexual harassment (Table 3). This required balance between extremes of being perceived as “too nice” and “too aggressive,” each of which was associated with negativity. Attending 1 remarked, “I know that other [female] faculty struggle with that a bit, with being...assertive. They are assertive, and it’s interpreted [negatively].” Attending 6 described insidiously sexist comments from patients: “‘You are too young to be a physician, you are too pretty to be a physician.’ ‘Oh, the woman doctor...rather than just ‘doctor.’” During one observation of rounds, a patient remarked to the attending, “You have cold hands. You know, I’m going to have to warm those up.” Our attendings responded to these challenges by proactively avoiding characteristics and behaviors considered to be stereotypically feminine in order to draw attention to their qualities as physicians rather than as women. During interviews, some attendings directed conversation away from themselves and instead placed emphasis on coaching female learners to navigate their own demeanors, behaviors, and responses to gender bias and harassment. This would include intentional planning of how to carry oneself, as well as feedback and debrief sessions after instances of harassment.

Our attendings grappled with how to physically portray themselves to avoid gender-based stereotypes. Attending 6 said, “Sometimes you might be taken less seriously if you pay more attention to your makeup or jewelry.” The same attending recalled “times where people would say inappropriate things based on what I was wearing—and I know that doesn’t happen with my male colleagues.” Our attendings responded to this challenge through purposeful choices of attire, personal appearance, and even external facial expressions that would avoid drawing unwanted or negative personal attention outside of the attending role.

Female Attendings Intentionally Identify and Embrace Their Unique Qualities

Our attendings identified societal gender norms and “traditional” masculine expectations in medicine (Table 4). Attending 4 drew attention to her institution’s healthcare leaders by remarking, “I think that women in medicine have similar challenges as women in other professional fields....Well, I guess it is different in that the pictures on the wall behind me are all White men.” Female attendings responded to this challenge by eschewing stereotypical qualities and intentionally finding and exhibiting their own unique strengths (eg, teaching approaches, areas of expertise, communication styles). By embracing their unique strengths, attendings gained confidence and felt more comfortable as physicians and educators. Advice from Attending 3 for other female physicians encapsulated this strategy: “But if [medicine] is what you love doing, then find a style that works for you, even if it’s different....Embrace being different.”

Several attendings identified patterns of thought in themselves that caused them to doubt their accomplishments and have a persistent fear of being exposed as a fraud, commonly known as impostor syndrome. Attending 2 summarized this with, “I know it’s irrational a little bit, but part of me [asks], ‘Am I getting all these opportunities because I’m female, because I’m a minority?’” Our attendings responded by recognizing impostor syndrome and addressing it through repeated positive self-reinforcing thoughts and language and by “letting go” of the doubt. Attending 4 recalled her feelings after being announced as a teaching award recipient for the fourth year in a row: “It was just like something changed in me....Maybe you are a good attending. Maybe you are doing something that is resonating with a unique class of medical students year after year.”

Our interviews also revealed strategies used by female attendings to support and advance their own careers, as well as those of other female faculty, to address the effects of impostor syndrome. Our participants noted the important role of female mentors and sponsors. One former learner mentioned, “I think some of the administration, there are definitely females that are helping promote [the attending].” During an observation, Attending 1 indicated that she was part of a network of women and junior faculty forged to promote each other’s work since “some people are good at self-promotion and some are not.” This group shares accomplishments by distributing and publicizing their accolades.

This multisite, qualitative study informs the complex ways in which exemplary female teaching attendings must navigate being women in medicine. We identified myriad challenges female attendings face originating from patients, from healthcare workers, and within themselves. Our attendings relied upon the following key strategies to mitigate such challenges: (1) they actively position themselves as physician team leaders, (2) they consciously work to manage gender-based stereotypes and perceptions, and (3) they intentionally identify and embrace their unique qualities.

Prior scholarship surrounding gender-based challenges has focused primarily on strategies to improve healthcare systems for women. Much scrutiny has been placed on elevating institutional culture,^26-29 enacting clear policy surrounding sexual harassment,³⁰ ensuring women are actively recruited and retained,³¹ providing resources to assist in work-life balance,^26,32 and cultivating effective mentorship and social networks.^11,33,34

While our findings support the importance of improving healthcare systems, they are more congruent with recent scholarship on explicit personal tactics to mitigate gender-based challenges. Researchers have suggested physicians use algorithmic responses to patient-initiated sexual harassment,³⁵ advocate for those who experience harassment in real time,³⁶ and engage in dedicated practice responding to harassment.^37,38 Our results build on these studies by outlining strategies intended to navigate complex gender dynamics and role model approaches for learners. Interestingly, it was more common for attendings to discuss how they guide their learners and debrief after difficult situations than to discuss how they personally respond to gender-based harassment. While we are not certain why this occurred, three factors may have contributed. First, attendings mentioned that these conversations are often uncomfortable. Second, attendings appeared to accept a higher level of gender-based challenges than they would have tolerated for their learners. Lastly, although we did not gather demographic data from learners, several attendings voiced a strong desire to advocate for and equip female learners with strategies to address and navigate these challenges for themselves.

Gender stereotypes are ubiquitous and firmly rooted in long-standing belief patterns. Certain characteristics are considered masculine (eg, aggressiveness, confidence) and others feminine (eg, kindness, cooperation).¹⁰ Role congruity theory purports that stereotypes lead women to demonstrate behaviors that reflect socially accepted gender norms³⁹ and that social approval is at risk if they behave in ways discordant with these norms.^10,40 Our study provides perspectives from female physicians who walk the tightrope of forcefully asserting themselves more than their male counterparts while not being overly aggressive, since both approaches may have negative connotations.

This study has several limitations. First, it was conducted with a limited number of site visits, attendings, and learners. Likewise, attendings were internists with relatively advanced academic rank. This may reduce the study’s generalizability since attendings in other fields and at earlier career stages may utilize different strategies. However, we believe that if more senior-level female attendings experienced difficulties being recognized and legitimized in their roles, then one can assume that junior-level female faculty would experience these challenges even more so. Likewise, data saturation was not the goal of this exploratory study. Through intensive qualitative data collection, we sought to obtain an in-depth understanding of challenges and strategies. Second, many exemplary female attendings were overlooked by our selection methodology, particularly since women are often underrepresented in the factors we chose. The multisite design, modified snowball sampling, and purposeful randomized selection methodology were used to ensure quality and diversity. Third, attendings provided lists of their former learners, and thus, selection and recall biases may have been introduced since attendings may have more readily identified learners with whom they formed positive relationships. Finally, we cannot eliminate a potential Hawthorne effect on data collection. Researchers attempted to lessen this by standing apart from teams and remaining unobtrusive.

We identified strategies employed by exemplary female attendings to navigate gender-based challenges in their workplaces. We found that female attendings face unconscious bias, labels, power struggles, and harassment, simply because of their gender. They consciously and constantly navigate these challenges by positioning themselves to be seen and heard as team leaders, balancing aspects of their outward appearance and demeanor, embracing their differences and avoiding assimilation to masculine stereotypes of physician leaders, working to manage self-doubt, and coaching their female learners in these areas.

The authors are indebted to Suzanne Winter, MS, for assisting with coordination of study participants and site visits.

The demographic composition of physicians has shifted dramatically in the last five decades. The number of women matriculating into medical school rose from 6% in the 1960s¹ to 52% in 2019²; women accounted for 39% of full-time faculty in 2015.³ Despite this evolution of the physician gender array, many challenges remain.⁴ Women represented only 35% of all associate professors and 22% of full professors in 2015.³ Women experience gender-based discrimination, hostility, and unconscious bias as medical trainees^5-9 and as attending physicians^10-13 with significant deleterious effects including burnout and suicidal thoughts.¹⁴ While types of gender-based challenges are well described in the literature, strategies to navigate and respond to these challenges are less understood.

The approaches and techniques of exemplary teaching attending physicians (hereafter referred to as “attendings”) have previously been reported from groups of predominantly male attendings.^15-18 Because of gender-based challenges female physicians face that lead them to reduce their effort or leave the medical field,¹⁹ there is concern that prior scholarship in effective teaching may not adequately capture the approaches and techniques of female attendings. To our knowledge, no studies have specifically examined female attendings. Therefore, we sought to explore the lived experiences of six female attendings with particular emphasis on how they navigate and respond to gender-based challenges in clinical environments.

Study Design and Sampling

This was a multisite study using an exploratory qualitative approach to inquiry. We aimed to examine techniques, approaches, and attitudes of outstanding general medicine teaching attendings among groups previously not well represented (ie, women and self-identified underrepresented minorities [URMs] in medicine). URM was defined by the Association of American Medical Colleges as “those racial and ethnic populations that are underrepresented in the medical profession relative to their numbers in the general population.”²⁰ A modified snowball sampling approach²¹ was employed to identify attendings as delineated below.

To maintain quality while guaranteeing diversity in geography and population, potential institutions in which to observe attendings were determined by first creating the following lists: The top 20 hospitals in the U.S. News & World Report’s 2017-2018 Best Hospitals Honor Roll,²² top-rated institutions by Doximity in each geographic region and among rural training sites,²³ and four historically Black colleges and universities (HBCUs) with medical schools. Institutions visited during a previous similar study¹⁶ were excluded. Next, the list was narrowed to 25 by randomly selecting five in each main geographic region and five rural institutions. These were combined with all four HBCUs to create a final list of 29 institutions.

Next, division of hospital medicine chiefs (and/or general medicine chiefs) and internal medicine residency directors at each of these 29 institutions were asked to nominate exemplary attendings, particularly those who identified as women and URMs. Twelve attendings who were themselves observed in a previous study¹⁶ were also asked for nominations. Finally, recommendations were sought from leaders of relevant American Medical Association member groups.²⁴

Using this sampling method, 43 physicians were identified. An internet search was conducted to identify individual characteristics including medical education, training, clinical and research interests, and educational awards. These characteristics were considered and discussed by the research team. Preference was given to those attendings nominated by more than one individual (n = 3), those who had received teaching awards, and those with interests involving women in medicine. Research team members narrowed the list to seven attendings who were contacted via email and invited to participate. One did not respond, while six agreed to participate. The six attendings identified current team members who would be rounding on the visit date. Attendings were asked to recommend 6-10 former learners; we contacted these former learners and invited them to participate. Former learners were included to understand lasting effects from their attendings.

Data Collection

Observations

All 1-day site visits were conducted by two research team members, a physician (NH) and a qualitative research specialist (MQ). In four visits, an additional author accompanied the research team. In order to ensure consistency and diversity in perspectives, all authors attended at least one visit. These occurred between April 16 and August 28, 2018. Each visit began with direct observation of attendings (n = 6) and current learners (n = 24) during inpatient general medicine teaching rounds. Each researcher unobtrusively recorded their observations via handwritten, open field notes, paying particular attention to group interactions, teaching approach, conversations within and peripheral to the team, and patient–team interactions. After each visit, researchers met to compare and combine field notes.

Interviews and Focus Groups

Researchers then conducted individual, semistructured interviews with attendings and focus groups with current (n = 21) and former (n = 17) learners. Focus groups with learners varied in size from two to five participants. Former learners were occasionally not available for on-site focus groups and were interviewed separately by telephone after the visit. The interview guide for attendings (Appendix 1) was adapted from the prior study¹⁶ but expanded with questions related to experiences, challenges, and approaches of female and URM physicians. A separate guide was used to facilitate focus groups with learners (Appendix 1). Three current learners were unable to participate in focus groups due to clinical duties. All interviews and focus groups were audio recorded and transcribed.

This study was determined to be exempt by the University of Michigan Institutional Review Board. All participants were informed that their participation was completely voluntary and that they could terminate their involvement at any time.

Data Analysis

Data were analyzed using a content analysis approach.²⁵ Inductive coding was used to identify codes derived from the data. Two team members (MQ and MH) independently coded the first transcript to develop a codebook, then met to compare and discuss codes. Codes and definitions were entered into the codebook. These team members continued coding five additional transcripts, meeting to compare codes, discussing any discrepancies until agreement was reached, adding new codes identified, and ensuring consistent code application. They reviewed prior transcripts and recoded if necessary. Once no new codes were identified, one team member coded the remaining transcripts. The same codebook was used to code field note documents using the same iterative process. After all qualitative data were coded and verified, they were entered into NVivo 10. Code reports were generated and reviewed by three team members to identify themes and check for coding consistency.

Role of the Funding Source

This study received no external funding.

We examined six exemplary attendings through direct observation of rounds and individual interviews. We also discussed these attendings with 21 current learners and 17 former learners (Appendix 2). All attendings self-identified as female. The group was diverse in terms of race/ethnicity, with three identifying as Black or African American, two as Asian, and one as White or Caucasian. Levels of experience as an attending ranged from 8 to 20 years (mean, 15.3 years). At the time of observation, two were professors and four were associate professors. The group included all three attendings who had been nominated by more than one individual, and all six had won multiple teaching awards. The observation sites represented several areas of the United States (Table 1).

The coded interview data and field notes were categorized into three broad overlapping themes based on strategies our attendings used to respond to gender-based challenges. The following sections describe types of challenges faced by female attendings along with specific strategies they employed to actively position themselves as physician team leaders, manage gender-based stereotypes and perceptions, and identify and embrace their unique qualities. Illustrative quotations or observations that further elucidate meaning are provided.

Female Attendings Actively Position Themselves as Physician Team Leaders

Our attendings frequently stated that they were assumed to be other healthcare provider types, such as nurses or physical therapists, and that these assumptions originated from patients, faculty, and staff (Table 2). Attending 3 commented, “I think every woman in this role has been mistaken for a different caretaker role, so lots of requests for nursing help. I’m sure I have taken more patients off of bed pans and brought more cups of water than maybe some of my male counterparts.” Some attendings responded to this challenge with the strategy of routinely wearing a white coat during rounds and patient encounters. This external visual cue was seen as a necessary reminder of the female attending role.

We found that patients and healthcare providers often believe teams are led by men, leading to a feeling of invisibility for female attendings. One current learner remarked, “If it was a new patient, more than likely, if we had a female attending, the patient’s eyes would always divert to the male physician.” This was not limited to patients. Attending 6 remembered comments from her consultants including, “‘Who is your attending? Let me talk with them,’ kind of assuming that I’m not the person making the decisions.” Female attendings would respond to this challenge by clearly introducing team members, including themselves, with roles and responsibilities. At times, this would require reintroductions and redirection if individuals still misidentified female team members.

Female attendings’ decision-making and thought processes were frequently second-guessed. This would often lead to power struggles with consultants, nurses, and learners. Attending 5 commented, “Even in residency, I felt this sometimes adversarial relationship with...female nurses where they would treat [female attendings] differently...questioning our decisions.” Female attendings would respond to this challenge by asserting themselves and demonstrating confidence with colleagues and at the bedside. This was an active process for women, as one former learner described: “[Female] attendings have to be a little bit more ‘on’—whatever ‘on’ is—more forceful, more direct....There is more slack given to a male attending.”

Female Attendings Consciously Work to Manage Gender-Based Stereotypes and Perceptions

Our attendings navigated gender-based stereotypes and perceptions, ranging from subtle microaggressions to overt sexual harassment (Table 3). This required balance between extremes of being perceived as “too nice” and “too aggressive,” each of which was associated with negativity. Attending 1 remarked, “I know that other [female] faculty struggle with that a bit, with being...assertive. They are assertive, and it’s interpreted [negatively].” Attending 6 described insidiously sexist comments from patients: “‘You are too young to be a physician, you are too pretty to be a physician.’ ‘Oh, the woman doctor...rather than just ‘doctor.’” During one observation of rounds, a patient remarked to the attending, “You have cold hands. You know, I’m going to have to warm those up.” Our attendings responded to these challenges by proactively avoiding characteristics and behaviors considered to be stereotypically feminine in order to draw attention to their qualities as physicians rather than as women. During interviews, some attendings directed conversation away from themselves and instead placed emphasis on coaching female learners to navigate their own demeanors, behaviors, and responses to gender bias and harassment. This would include intentional planning of how to carry oneself, as well as feedback and debrief sessions after instances of harassment.

Our attendings grappled with how to physically portray themselves to avoid gender-based stereotypes. Attending 6 said, “Sometimes you might be taken less seriously if you pay more attention to your makeup or jewelry.” The same attending recalled “times where people would say inappropriate things based on what I was wearing—and I know that doesn’t happen with my male colleagues.” Our attendings responded to this challenge through purposeful choices of attire, personal appearance, and even external facial expressions that would avoid drawing unwanted or negative personal attention outside of the attending role.

Female Attendings Intentionally Identify and Embrace Their Unique Qualities

Our attendings identified societal gender norms and “traditional” masculine expectations in medicine (Table 4). Attending 4 drew attention to her institution’s healthcare leaders by remarking, “I think that women in medicine have similar challenges as women in other professional fields....Well, I guess it is different in that the pictures on the wall behind me are all White men.” Female attendings responded to this challenge by eschewing stereotypical qualities and intentionally finding and exhibiting their own unique strengths (eg, teaching approaches, areas of expertise, communication styles). By embracing their unique strengths, attendings gained confidence and felt more comfortable as physicians and educators. Advice from Attending 3 for other female physicians encapsulated this strategy: “But if [medicine] is what you love doing, then find a style that works for you, even if it’s different....Embrace being different.”

Several attendings identified patterns of thought in themselves that caused them to doubt their accomplishments and have a persistent fear of being exposed as a fraud, commonly known as impostor syndrome. Attending 2 summarized this with, “I know it’s irrational a little bit, but part of me [asks], ‘Am I getting all these opportunities because I’m female, because I’m a minority?’” Our attendings responded by recognizing impostor syndrome and addressing it through repeated positive self-reinforcing thoughts and language and by “letting go” of the doubt. Attending 4 recalled her feelings after being announced as a teaching award recipient for the fourth year in a row: “It was just like something changed in me....Maybe you are a good attending. Maybe you are doing something that is resonating with a unique class of medical students year after year.”

Our interviews also revealed strategies used by female attendings to support and advance their own careers, as well as those of other female faculty, to address the effects of impostor syndrome. Our participants noted the important role of female mentors and sponsors. One former learner mentioned, “I think some of the administration, there are definitely females that are helping promote [the attending].” During an observation, Attending 1 indicated that she was part of a network of women and junior faculty forged to promote each other’s work since “some people are good at self-promotion and some are not.” This group shares accomplishments by distributing and publicizing their accolades.

This multisite, qualitative study informs the complex ways in which exemplary female teaching attendings must navigate being women in medicine. We identified myriad challenges female attendings face originating from patients, from healthcare workers, and within themselves. Our attendings relied upon the following key strategies to mitigate such challenges: (1) they actively position themselves as physician team leaders, (2) they consciously work to manage gender-based stereotypes and perceptions, and (3) they intentionally identify and embrace their unique qualities.

Prior scholarship surrounding gender-based challenges has focused primarily on strategies to improve healthcare systems for women. Much scrutiny has been placed on elevating institutional culture,^26-29 enacting clear policy surrounding sexual harassment,³⁰ ensuring women are actively recruited and retained,³¹ providing resources to assist in work-life balance,^26,32 and cultivating effective mentorship and social networks.^11,33,34

While our findings support the importance of improving healthcare systems, they are more congruent with recent scholarship on explicit personal tactics to mitigate gender-based challenges. Researchers have suggested physicians use algorithmic responses to patient-initiated sexual harassment,³⁵ advocate for those who experience harassment in real time,³⁶ and engage in dedicated practice responding to harassment.^37,38 Our results build on these studies by outlining strategies intended to navigate complex gender dynamics and role model approaches for learners. Interestingly, it was more common for attendings to discuss how they guide their learners and debrief after difficult situations than to discuss how they personally respond to gender-based harassment. While we are not certain why this occurred, three factors may have contributed. First, attendings mentioned that these conversations are often uncomfortable. Second, attendings appeared to accept a higher level of gender-based challenges than they would have tolerated for their learners. Lastly, although we did not gather demographic data from learners, several attendings voiced a strong desire to advocate for and equip female learners with strategies to address and navigate these challenges for themselves.

Gender stereotypes are ubiquitous and firmly rooted in long-standing belief patterns. Certain characteristics are considered masculine (eg, aggressiveness, confidence) and others feminine (eg, kindness, cooperation).¹⁰ Role congruity theory purports that stereotypes lead women to demonstrate behaviors that reflect socially accepted gender norms³⁹ and that social approval is at risk if they behave in ways discordant with these norms.^10,40 Our study provides perspectives from female physicians who walk the tightrope of forcefully asserting themselves more than their male counterparts while not being overly aggressive, since both approaches may have negative connotations.

This study has several limitations. First, it was conducted with a limited number of site visits, attendings, and learners. Likewise, attendings were internists with relatively advanced academic rank. This may reduce the study’s generalizability since attendings in other fields and at earlier career stages may utilize different strategies. However, we believe that if more senior-level female attendings experienced difficulties being recognized and legitimized in their roles, then one can assume that junior-level female faculty would experience these challenges even more so. Likewise, data saturation was not the goal of this exploratory study. Through intensive qualitative data collection, we sought to obtain an in-depth understanding of challenges and strategies. Second, many exemplary female attendings were overlooked by our selection methodology, particularly since women are often underrepresented in the factors we chose. The multisite design, modified snowball sampling, and purposeful randomized selection methodology were used to ensure quality and diversity. Third, attendings provided lists of their former learners, and thus, selection and recall biases may have been introduced since attendings may have more readily identified learners with whom they formed positive relationships. Finally, we cannot eliminate a potential Hawthorne effect on data collection. Researchers attempted to lessen this by standing apart from teams and remaining unobtrusive.

We identified strategies employed by exemplary female attendings to navigate gender-based challenges in their workplaces. We found that female attendings face unconscious bias, labels, power struggles, and harassment, simply because of their gender. They consciously and constantly navigate these challenges by positioning themselves to be seen and heard as team leaders, balancing aspects of their outward appearance and demeanor, embracing their differences and avoiding assimilation to masculine stereotypes of physician leaders, working to manage self-doubt, and coaching their female learners in these areas.

The authors are indebted to Suzanne Winter, MS, for assisting with coordination of study participants and site visits.

The demographic composition of physicians has shifted dramatically in the last five decades. The number of women matriculating into medical school rose from 6% in the 1960s¹ to 52% in 2019²; women accounted for 39% of full-time faculty in 2015.³ Despite this evolution of the physician gender array, many challenges remain.⁴ Women represented only 35% of all associate professors and 22% of full professors in 2015.³ Women experience gender-based discrimination, hostility, and unconscious bias as medical trainees^5-9 and as attending physicians^10-13 with significant deleterious effects including burnout and suicidal thoughts.¹⁴ While types of gender-based challenges are well described in the literature, strategies to navigate and respond to these challenges are less understood.

The approaches and techniques of exemplary teaching attending physicians (hereafter referred to as “attendings”) have previously been reported from groups of predominantly male attendings.^15-18 Because of gender-based challenges female physicians face that lead them to reduce their effort or leave the medical field,¹⁹ there is concern that prior scholarship in effective teaching may not adequately capture the approaches and techniques of female attendings. To our knowledge, no studies have specifically examined female attendings. Therefore, we sought to explore the lived experiences of six female attendings with particular emphasis on how they navigate and respond to gender-based challenges in clinical environments.

Study Design and Sampling

This was a multisite study using an exploratory qualitative approach to inquiry. We aimed to examine techniques, approaches, and attitudes of outstanding general medicine teaching attendings among groups previously not well represented (ie, women and self-identified underrepresented minorities [URMs] in medicine). URM was defined by the Association of American Medical Colleges as “those racial and ethnic populations that are underrepresented in the medical profession relative to their numbers in the general population.”²⁰ A modified snowball sampling approach²¹ was employed to identify attendings as delineated below.

To maintain quality while guaranteeing diversity in geography and population, potential institutions in which to observe attendings were determined by first creating the following lists: The top 20 hospitals in the U.S. News & World Report’s 2017-2018 Best Hospitals Honor Roll,²² top-rated institutions by Doximity in each geographic region and among rural training sites,²³ and four historically Black colleges and universities (HBCUs) with medical schools. Institutions visited during a previous similar study¹⁶ were excluded. Next, the list was narrowed to 25 by randomly selecting five in each main geographic region and five rural institutions. These were combined with all four HBCUs to create a final list of 29 institutions.

Next, division of hospital medicine chiefs (and/or general medicine chiefs) and internal medicine residency directors at each of these 29 institutions were asked to nominate exemplary attendings, particularly those who identified as women and URMs. Twelve attendings who were themselves observed in a previous study¹⁶ were also asked for nominations. Finally, recommendations were sought from leaders of relevant American Medical Association member groups.²⁴

Using this sampling method, 43 physicians were identified. An internet search was conducted to identify individual characteristics including medical education, training, clinical and research interests, and educational awards. These characteristics were considered and discussed by the research team. Preference was given to those attendings nominated by more than one individual (n = 3), those who had received teaching awards, and those with interests involving women in medicine. Research team members narrowed the list to seven attendings who were contacted via email and invited to participate. One did not respond, while six agreed to participate. The six attendings identified current team members who would be rounding on the visit date. Attendings were asked to recommend 6-10 former learners; we contacted these former learners and invited them to participate. Former learners were included to understand lasting effects from their attendings.

Data Collection

Observations

All 1-day site visits were conducted by two research team members, a physician (NH) and a qualitative research specialist (MQ). In four visits, an additional author accompanied the research team. In order to ensure consistency and diversity in perspectives, all authors attended at least one visit. These occurred between April 16 and August 28, 2018. Each visit began with direct observation of attendings (n = 6) and current learners (n = 24) during inpatient general medicine teaching rounds. Each researcher unobtrusively recorded their observations via handwritten, open field notes, paying particular attention to group interactions, teaching approach, conversations within and peripheral to the team, and patient–team interactions. After each visit, researchers met to compare and combine field notes.

Interviews and Focus Groups

Researchers then conducted individual, semistructured interviews with attendings and focus groups with current (n = 21) and former (n = 17) learners. Focus groups with learners varied in size from two to five participants. Former learners were occasionally not available for on-site focus groups and were interviewed separately by telephone after the visit. The interview guide for attendings (Appendix 1) was adapted from the prior study¹⁶ but expanded with questions related to experiences, challenges, and approaches of female and URM physicians. A separate guide was used to facilitate focus groups with learners (Appendix 1). Three current learners were unable to participate in focus groups due to clinical duties. All interviews and focus groups were audio recorded and transcribed.

This study was determined to be exempt by the University of Michigan Institutional Review Board. All participants were informed that their participation was completely voluntary and that they could terminate their involvement at any time.

Data Analysis

Data were analyzed using a content analysis approach.²⁵ Inductive coding was used to identify codes derived from the data. Two team members (MQ and MH) independently coded the first transcript to develop a codebook, then met to compare and discuss codes. Codes and definitions were entered into the codebook. These team members continued coding five additional transcripts, meeting to compare codes, discussing any discrepancies until agreement was reached, adding new codes identified, and ensuring consistent code application. They reviewed prior transcripts and recoded if necessary. Once no new codes were identified, one team member coded the remaining transcripts. The same codebook was used to code field note documents using the same iterative process. After all qualitative data were coded and verified, they were entered into NVivo 10. Code reports were generated and reviewed by three team members to identify themes and check for coding consistency.

Role of the Funding Source

This study received no external funding.

We examined six exemplary attendings through direct observation of rounds and individual interviews. We also discussed these attendings with 21 current learners and 17 former learners (Appendix 2). All attendings self-identified as female. The group was diverse in terms of race/ethnicity, with three identifying as Black or African American, two as Asian, and one as White or Caucasian. Levels of experience as an attending ranged from 8 to 20 years (mean, 15.3 years). At the time of observation, two were professors and four were associate professors. The group included all three attendings who had been nominated by more than one individual, and all six had won multiple teaching awards. The observation sites represented several areas of the United States (Table 1).

The coded interview data and field notes were categorized into three broad overlapping themes based on strategies our attendings used to respond to gender-based challenges. The following sections describe types of challenges faced by female attendings along with specific strategies they employed to actively position themselves as physician team leaders, manage gender-based stereotypes and perceptions, and identify and embrace their unique qualities. Illustrative quotations or observations that further elucidate meaning are provided.

Female Attendings Actively Position Themselves as Physician Team Leaders

Our attendings frequently stated that they were assumed to be other healthcare provider types, such as nurses or physical therapists, and that these assumptions originated from patients, faculty, and staff (Table 2). Attending 3 commented, “I think every woman in this role has been mistaken for a different caretaker role, so lots of requests for nursing help. I’m sure I have taken more patients off of bed pans and brought more cups of water than maybe some of my male counterparts.” Some attendings responded to this challenge with the strategy of routinely wearing a white coat during rounds and patient encounters. This external visual cue was seen as a necessary reminder of the female attending role.

We found that patients and healthcare providers often believe teams are led by men, leading to a feeling of invisibility for female attendings. One current learner remarked, “If it was a new patient, more than likely, if we had a female attending, the patient’s eyes would always divert to the male physician.” This was not limited to patients. Attending 6 remembered comments from her consultants including, “‘Who is your attending? Let me talk with them,’ kind of assuming that I’m not the person making the decisions.” Female attendings would respond to this challenge by clearly introducing team members, including themselves, with roles and responsibilities. At times, this would require reintroductions and redirection if individuals still misidentified female team members.

Female attendings’ decision-making and thought processes were frequently second-guessed. This would often lead to power struggles with consultants, nurses, and learners. Attending 5 commented, “Even in residency, I felt this sometimes adversarial relationship with...female nurses where they would treat [female attendings] differently...questioning our decisions.” Female attendings would respond to this challenge by asserting themselves and demonstrating confidence with colleagues and at the bedside. This was an active process for women, as one former learner described: “[Female] attendings have to be a little bit more ‘on’—whatever ‘on’ is—more forceful, more direct....There is more slack given to a male attending.”

Female Attendings Consciously Work to Manage Gender-Based Stereotypes and Perceptions

Our attendings navigated gender-based stereotypes and perceptions, ranging from subtle microaggressions to overt sexual harassment (Table 3). This required balance between extremes of being perceived as “too nice” and “too aggressive,” each of which was associated with negativity. Attending 1 remarked, “I know that other [female] faculty struggle with that a bit, with being...assertive. They are assertive, and it’s interpreted [negatively].” Attending 6 described insidiously sexist comments from patients: “‘You are too young to be a physician, you are too pretty to be a physician.’ ‘Oh, the woman doctor...rather than just ‘doctor.’” During one observation of rounds, a patient remarked to the attending, “You have cold hands. You know, I’m going to have to warm those up.” Our attendings responded to these challenges by proactively avoiding characteristics and behaviors considered to be stereotypically feminine in order to draw attention to their qualities as physicians rather than as women. During interviews, some attendings directed conversation away from themselves and instead placed emphasis on coaching female learners to navigate their own demeanors, behaviors, and responses to gender bias and harassment. This would include intentional planning of how to carry oneself, as well as feedback and debrief sessions after instances of harassment.

Our attendings grappled with how to physically portray themselves to avoid gender-based stereotypes. Attending 6 said, “Sometimes you might be taken less seriously if you pay more attention to your makeup or jewelry.” The same attending recalled “times where people would say inappropriate things based on what I was wearing—and I know that doesn’t happen with my male colleagues.” Our attendings responded to this challenge through purposeful choices of attire, personal appearance, and even external facial expressions that would avoid drawing unwanted or negative personal attention outside of the attending role.

Female Attendings Intentionally Identify and Embrace Their Unique Qualities

Our attendings identified societal gender norms and “traditional” masculine expectations in medicine (Table 4). Attending 4 drew attention to her institution’s healthcare leaders by remarking, “I think that women in medicine have similar challenges as women in other professional fields....Well, I guess it is different in that the pictures on the wall behind me are all White men.” Female attendings responded to this challenge by eschewing stereotypical qualities and intentionally finding and exhibiting their own unique strengths (eg, teaching approaches, areas of expertise, communication styles). By embracing their unique strengths, attendings gained confidence and felt more comfortable as physicians and educators. Advice from Attending 3 for other female physicians encapsulated this strategy: “But if [medicine] is what you love doing, then find a style that works for you, even if it’s different....Embrace being different.”

Several attendings identified patterns of thought in themselves that caused them to doubt their accomplishments and have a persistent fear of being exposed as a fraud, commonly known as impostor syndrome. Attending 2 summarized this with, “I know it’s irrational a little bit, but part of me [asks], ‘Am I getting all these opportunities because I’m female, because I’m a minority?’” Our attendings responded by recognizing impostor syndrome and addressing it through repeated positive self-reinforcing thoughts and language and by “letting go” of the doubt. Attending 4 recalled her feelings after being announced as a teaching award recipient for the fourth year in a row: “It was just like something changed in me....Maybe you are a good attending. Maybe you are doing something that is resonating with a unique class of medical students year after year.”

Our interviews also revealed strategies used by female attendings to support and advance their own careers, as well as those of other female faculty, to address the effects of impostor syndrome. Our participants noted the important role of female mentors and sponsors. One former learner mentioned, “I think some of the administration, there are definitely females that are helping promote [the attending].” During an observation, Attending 1 indicated that she was part of a network of women and junior faculty forged to promote each other’s work since “some people are good at self-promotion and some are not.” This group shares accomplishments by distributing and publicizing their accolades.

This multisite, qualitative study informs the complex ways in which exemplary female teaching attendings must navigate being women in medicine. We identified myriad challenges female attendings face originating from patients, from healthcare workers, and within themselves. Our attendings relied upon the following key strategies to mitigate such challenges: (1) they actively position themselves as physician team leaders, (2) they consciously work to manage gender-based stereotypes and perceptions, and (3) they intentionally identify and embrace their unique qualities.

Prior scholarship surrounding gender-based challenges has focused primarily on strategies to improve healthcare systems for women. Much scrutiny has been placed on elevating institutional culture,^26-29 enacting clear policy surrounding sexual harassment,³⁰ ensuring women are actively recruited and retained,³¹ providing resources to assist in work-life balance,^26,32 and cultivating effective mentorship and social networks.^11,33,34

While our findings support the importance of improving healthcare systems, they are more congruent with recent scholarship on explicit personal tactics to mitigate gender-based challenges. Researchers have suggested physicians use algorithmic responses to patient-initiated sexual harassment,³⁵ advocate for those who experience harassment in real time,³⁶ and engage in dedicated practice responding to harassment.^37,38 Our results build on these studies by outlining strategies intended to navigate complex gender dynamics and role model approaches for learners. Interestingly, it was more common for attendings to discuss how they guide their learners and debrief after difficult situations than to discuss how they personally respond to gender-based harassment. While we are not certain why this occurred, three factors may have contributed. First, attendings mentioned that these conversations are often uncomfortable. Second, attendings appeared to accept a higher level of gender-based challenges than they would have tolerated for their learners. Lastly, although we did not gather demographic data from learners, several attendings voiced a strong desire to advocate for and equip female learners with strategies to address and navigate these challenges for themselves.

Gender stereotypes are ubiquitous and firmly rooted in long-standing belief patterns. Certain characteristics are considered masculine (eg, aggressiveness, confidence) and others feminine (eg, kindness, cooperation).¹⁰ Role congruity theory purports that stereotypes lead women to demonstrate behaviors that reflect socially accepted gender norms³⁹ and that social approval is at risk if they behave in ways discordant with these norms.^10,40 Our study provides perspectives from female physicians who walk the tightrope of forcefully asserting themselves more than their male counterparts while not being overly aggressive, since both approaches may have negative connotations.

This study has several limitations. First, it was conducted with a limited number of site visits, attendings, and learners. Likewise, attendings were internists with relatively advanced academic rank. This may reduce the study’s generalizability since attendings in other fields and at earlier career stages may utilize different strategies. However, we believe that if more senior-level female attendings experienced difficulties being recognized and legitimized in their roles, then one can assume that junior-level female faculty would experience these challenges even more so. Likewise, data saturation was not the goal of this exploratory study. Through intensive qualitative data collection, we sought to obtain an in-depth understanding of challenges and strategies. Second, many exemplary female attendings were overlooked by our selection methodology, particularly since women are often underrepresented in the factors we chose. The multisite design, modified snowball sampling, and purposeful randomized selection methodology were used to ensure quality and diversity. Third, attendings provided lists of their former learners, and thus, selection and recall biases may have been introduced since attendings may have more readily identified learners with whom they formed positive relationships. Finally, we cannot eliminate a potential Hawthorne effect on data collection. Researchers attempted to lessen this by standing apart from teams and remaining unobtrusive.

We identified strategies employed by exemplary female attendings to navigate gender-based challenges in their workplaces. We found that female attendings face unconscious bias, labels, power struggles, and harassment, simply because of their gender. They consciously and constantly navigate these challenges by positioning themselves to be seen and heard as team leaders, balancing aspects of their outward appearance and demeanor, embracing their differences and avoiding assimilation to masculine stereotypes of physician leaders, working to manage self-doubt, and coaching their female learners in these areas.

The authors are indebted to Suzanne Winter, MS, for assisting with coordination of study participants and site visits.

Viral testing for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) of all patients admitted to the hospital is an appealing objective given the recognition of asymptomatic or minimally symptomatic infections. Yet such testing requires that all admitted patients be classified as persons under investigation (PUIs) until their test results are known. If an outside laboratory is used for the SARS-CoV-2 testing, the delay in obtaining results for these PUIs may cause significant personal protective equipment (PPE) use, postpone some care for non-coronavirus disease 2019 (COVID-19) conditions, block beds, and produce anxiety among staff and other patients. Rapid in-house testing of all admitted patients may resolve these issues but may be limited by the supply of reagents. To address this challenge, we piloted a pooled testing strategy for patients at low risk for SARS-CoV-2 admitted to a community hospital.

From April 17, 2020, to May 11, 2020, we implemented a pooled testing strategy using the GeneXpert^® System (Cepheid, Sunnyvale, California) at Saratoga Hospital, a 171-bed community hospital in upstate New York. Under normal procedures for this system, a single patient swab is placed in a vial containing viral transport media (VTM). An aliquot of this media is then transferred into a Xpert^® Xpress SARS CoV-2 test cartridge and assayed on the GeneXpert® instrument in our laboratory. Obtaining immediate results allowed us to assign admitted patients to either a COVID-19 or a non–COVID-19 unit, improving the issues associated with PUIs. Unfortunately, we did not have enough test cartridges to sustain this strategy of rapid individual testing of all admitted patients, and supply lines have remained uncertain.

We sought to conserve our limited Xpert Xpress SARS CoV-2 test cartridges using the strategy of pooled testing, a technique reported in Germany and by the University of Nebraska.^1,2 In this method, variable numbers of tests are pooled for a single analysis. If the test from the pooled vial is negative, these patients are all considered negative. If the pooled test is positive, all those patients need individual testing. This pooling method has been theorized to preserve test cartridges when the expected frequency of positive results is low.³

All patients admitted or placed on observation underwent SARS-CoV-2 PCR testing. The Emergency Department (ED) staff stratified patients into high or low risk to determine if they would be tested in a single send-out test (high risk) or a rapid in-house pooled group (low risk). High-risk patients were those with compatible history, physical exam, laboratory markers, and radiographic studies for COVID-19 disease. This often included increased supplemental oxygen requirement, multiple elevated inflammatory markers (including D-dimer, C-reactive protein, erythrocyte sedimentation rate, and ferritin levels), lymphopenia, and findings on chest radiograph or computed tomography scan including ground glass changes, multifocal pneumonia, or pneumonia. High-risk patients were admitted to the COVID unit or intensive care unit, had a send-out SARS-CoV-2 polymerase chain reaction (PCR) test, and were treated as a PUI until the results of their testing was known and correlated with their clinical course. Low-risk patients were those without complaints suggestive of COVID-19 infection and who may have had negative inflammatory markers, no significant lymphopenia, and negative imaging. 

The samples from 3 admitted patients thought to be at low-risk for COVID-19 using the clinical judgement of our ED staff were pooled for testing. All samples were obtained using nasopharyngeal swabs by experienced staff. The swabs from these patients were placed into a single vial of 3 mL VTM, maintaining the recommended 1 swab per mL of VTM. An aliquot of this media was then transferred into an Xpert Xpress SARS CoV-2 test cartridge and assayed on the GeneXpert instrument in our laboratory following manufacturer’s instructions. Based on analytic laboratory studies of the Cepheid Xpert Express SARS-CoV-2 test,⁴ we assume a clinical performance comparable to other reverse-transcriptase PCR (RT-PCR) tests, which have so far demonstrated sensitivities of 60% to 80% and specificities of 95% to 99%.⁵

Validation studies were performed on pools made from samples obtained from admitted patients with previously known positive and negative samples tested at the New York State Department of Health, Wadsworth Center laboratory (Albany, New York). A total of 14 samples were used for the instrument validation study, including three samples for pooled testing. The cycle threshold (Ct) value is defined as the number of PCR cycles required for the signal to be detectable. Ct values for each nucleic acid target of a known positive sample tested singly and in the pool with known negative patients were compared. A small shift in Ct values was noted between single and pooled testing, demonstrating no decrease in analytic sensitivity and suggesting that we would experience no decrease in clinical sensitivity.

We selected the pooling of 3 samples into 1 cartridge for several reasons: (1) 3-sample pools are well within the appropriate pooling size for the percentage positive rate in the population being tested. The use of larger pool sizes results in the need for more repeat testing when a positive result is obtained; (2) Given our supply lines, the projected savings would allow us to continue this strategy; and (3) Holding 3 patients in the ED until a pool was ready was manageable given our rate of admissions and ED volume.

The strategy required patients being held in the ED until a pooled group of 3 could be tested. On select occasions when holding patients in the ED to obtain a pool of 3 was not practical, 2 patients were tested in the pool. These decisions required close coordination between the laboratory, ED, and nursing staff.

This strategy resulted in 530 unique patient tests in 179 cartridges (172 with three swabs and 7 with two swabs). We had 4 positive pooled tests, requiring the use of 11 additional cartridges, for a positive rate of 0.8% (4/530) in this low-risk population (patients without COVID-19–related symptoms). There were no patients from negative pools who developed evidence of COVID-19 disease or tested positive for SARS-CoV-2 during their hospitalization. The total number of cartridges used was 190 and the number saved was 340.

The strategy of pooled testing for SARS-CoV-2 in patients admitted to our community hospital allowed us to continue rapid testing of admitted patients at low risk for COVID-19 disease during a period when supplies would otherwise not have been sufficient. We believe this strategy conserved PPE, led to a marked reduction in staff and patient anxiety, and improved patient care. Our impression is that testing all admitted patients has also been reassuring to our community. Like many others, we have observed that public fear of entering the hospital during this pandemic has caused delays in patients seeking care for non–COVID-19 conditions. We believe this strategy will help reduce those fears.

This strategy may require modification as the pandemic progresses. Our ED physicians were able to identify patients who they felt to be low risk for having COVID-19 disease based on signs, symptoms, and clinical impression during a time when we had an 8% positive rate among symptomatic outpatients and an estimated community positive rate in the range of 1% to 2%. If the rate of positive tests in our community rises, the use of pooling may need to be limited or the pool size reduced. If our supply of reagents is further limited or patient testing demand increases, the pool size may need to be increased. This will need to be balanced with our ability to hold patients in the ED while waiting for the pool size to be reached.

The strategy of pooled testing for SARS-CoV-2 has allowed us to continue to immediately test all admitted patients, thus improving patient care. It has required close coordination between multiple members of our laboratory and clinical staff and may require adjustment as the pandemic progresses. We believe it is a valuable tool during a time of limited resources that may have application in testing other low-risk groups, including healthcare workers and clients of occupational medicine services.

The authors gratefully acknowledge the support of Kirsten St. George, MAppSc, PhD, Director, Virology Laboratory, Wadsworth, NYSDOH, and the services supplied by the Wadsworth laboratory to our region.

Viral testing for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) of all patients admitted to the hospital is an appealing objective given the recognition of asymptomatic or minimally symptomatic infections. Yet such testing requires that all admitted patients be classified as persons under investigation (PUIs) until their test results are known. If an outside laboratory is used for the SARS-CoV-2 testing, the delay in obtaining results for these PUIs may cause significant personal protective equipment (PPE) use, postpone some care for non-coronavirus disease 2019 (COVID-19) conditions, block beds, and produce anxiety among staff and other patients. Rapid in-house testing of all admitted patients may resolve these issues but may be limited by the supply of reagents. To address this challenge, we piloted a pooled testing strategy for patients at low risk for SARS-CoV-2 admitted to a community hospital.

From April 17, 2020, to May 11, 2020, we implemented a pooled testing strategy using the GeneXpert^® System (Cepheid, Sunnyvale, California) at Saratoga Hospital, a 171-bed community hospital in upstate New York. Under normal procedures for this system, a single patient swab is placed in a vial containing viral transport media (VTM). An aliquot of this media is then transferred into a Xpert^® Xpress SARS CoV-2 test cartridge and assayed on the GeneXpert® instrument in our laboratory. Obtaining immediate results allowed us to assign admitted patients to either a COVID-19 or a non–COVID-19 unit, improving the issues associated with PUIs. Unfortunately, we did not have enough test cartridges to sustain this strategy of rapid individual testing of all admitted patients, and supply lines have remained uncertain.

We sought to conserve our limited Xpert Xpress SARS CoV-2 test cartridges using the strategy of pooled testing, a technique reported in Germany and by the University of Nebraska.^1,2 In this method, variable numbers of tests are pooled for a single analysis. If the test from the pooled vial is negative, these patients are all considered negative. If the pooled test is positive, all those patients need individual testing. This pooling method has been theorized to preserve test cartridges when the expected frequency of positive results is low.³

All patients admitted or placed on observation underwent SARS-CoV-2 PCR testing. The Emergency Department (ED) staff stratified patients into high or low risk to determine if they would be tested in a single send-out test (high risk) or a rapid in-house pooled group (low risk). High-risk patients were those with compatible history, physical exam, laboratory markers, and radiographic studies for COVID-19 disease. This often included increased supplemental oxygen requirement, multiple elevated inflammatory markers (including D-dimer, C-reactive protein, erythrocyte sedimentation rate, and ferritin levels), lymphopenia, and findings on chest radiograph or computed tomography scan including ground glass changes, multifocal pneumonia, or pneumonia. High-risk patients were admitted to the COVID unit or intensive care unit, had a send-out SARS-CoV-2 polymerase chain reaction (PCR) test, and were treated as a PUI until the results of their testing was known and correlated with their clinical course. Low-risk patients were those without complaints suggestive of COVID-19 infection and who may have had negative inflammatory markers, no significant lymphopenia, and negative imaging. 

The samples from 3 admitted patients thought to be at low-risk for COVID-19 using the clinical judgement of our ED staff were pooled for testing. All samples were obtained using nasopharyngeal swabs by experienced staff. The swabs from these patients were placed into a single vial of 3 mL VTM, maintaining the recommended 1 swab per mL of VTM. An aliquot of this media was then transferred into an Xpert Xpress SARS CoV-2 test cartridge and assayed on the GeneXpert instrument in our laboratory following manufacturer’s instructions. Based on analytic laboratory studies of the Cepheid Xpert Express SARS-CoV-2 test,⁴ we assume a clinical performance comparable to other reverse-transcriptase PCR (RT-PCR) tests, which have so far demonstrated sensitivities of 60% to 80% and specificities of 95% to 99%.⁵

Validation studies were performed on pools made from samples obtained from admitted patients with previously known positive and negative samples tested at the New York State Department of Health, Wadsworth Center laboratory (Albany, New York). A total of 14 samples were used for the instrument validation study, including three samples for pooled testing. The cycle threshold (Ct) value is defined as the number of PCR cycles required for the signal to be detectable. Ct values for each nucleic acid target of a known positive sample tested singly and in the pool with known negative patients were compared. A small shift in Ct values was noted between single and pooled testing, demonstrating no decrease in analytic sensitivity and suggesting that we would experience no decrease in clinical sensitivity.

We selected the pooling of 3 samples into 1 cartridge for several reasons: (1) 3-sample pools are well within the appropriate pooling size for the percentage positive rate in the population being tested. The use of larger pool sizes results in the need for more repeat testing when a positive result is obtained; (2) Given our supply lines, the projected savings would allow us to continue this strategy; and (3) Holding 3 patients in the ED until a pool was ready was manageable given our rate of admissions and ED volume.

The strategy required patients being held in the ED until a pooled group of 3 could be tested. On select occasions when holding patients in the ED to obtain a pool of 3 was not practical, 2 patients were tested in the pool. These decisions required close coordination between the laboratory, ED, and nursing staff.

This strategy resulted in 530 unique patient tests in 179 cartridges (172 with three swabs and 7 with two swabs). We had 4 positive pooled tests, requiring the use of 11 additional cartridges, for a positive rate of 0.8% (4/530) in this low-risk population (patients without COVID-19–related symptoms). There were no patients from negative pools who developed evidence of COVID-19 disease or tested positive for SARS-CoV-2 during their hospitalization. The total number of cartridges used was 190 and the number saved was 340.

The strategy of pooled testing for SARS-CoV-2 in patients admitted to our community hospital allowed us to continue rapid testing of admitted patients at low risk for COVID-19 disease during a period when supplies would otherwise not have been sufficient. We believe this strategy conserved PPE, led to a marked reduction in staff and patient anxiety, and improved patient care. Our impression is that testing all admitted patients has also been reassuring to our community. Like many others, we have observed that public fear of entering the hospital during this pandemic has caused delays in patients seeking care for non–COVID-19 conditions. We believe this strategy will help reduce those fears.

This strategy may require modification as the pandemic progresses. Our ED physicians were able to identify patients who they felt to be low risk for having COVID-19 disease based on signs, symptoms, and clinical impression during a time when we had an 8% positive rate among symptomatic outpatients and an estimated community positive rate in the range of 1% to 2%. If the rate of positive tests in our community rises, the use of pooling may need to be limited or the pool size reduced. If our supply of reagents is further limited or patient testing demand increases, the pool size may need to be increased. This will need to be balanced with our ability to hold patients in the ED while waiting for the pool size to be reached.

The strategy of pooled testing for SARS-CoV-2 has allowed us to continue to immediately test all admitted patients, thus improving patient care. It has required close coordination between multiple members of our laboratory and clinical staff and may require adjustment as the pandemic progresses. We believe it is a valuable tool during a time of limited resources that may have application in testing other low-risk groups, including healthcare workers and clients of occupational medicine services.

The authors gratefully acknowledge the support of Kirsten St. George, MAppSc, PhD, Director, Virology Laboratory, Wadsworth, NYSDOH, and the services supplied by the Wadsworth laboratory to our region.

Viral testing for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) of all patients admitted to the hospital is an appealing objective given the recognition of asymptomatic or minimally symptomatic infections. Yet such testing requires that all admitted patients be classified as persons under investigation (PUIs) until their test results are known. If an outside laboratory is used for the SARS-CoV-2 testing, the delay in obtaining results for these PUIs may cause significant personal protective equipment (PPE) use, postpone some care for non-coronavirus disease 2019 (COVID-19) conditions, block beds, and produce anxiety among staff and other patients. Rapid in-house testing of all admitted patients may resolve these issues but may be limited by the supply of reagents. To address this challenge, we piloted a pooled testing strategy for patients at low risk for SARS-CoV-2 admitted to a community hospital.

From April 17, 2020, to May 11, 2020, we implemented a pooled testing strategy using the GeneXpert^® System (Cepheid, Sunnyvale, California) at Saratoga Hospital, a 171-bed community hospital in upstate New York. Under normal procedures for this system, a single patient swab is placed in a vial containing viral transport media (VTM). An aliquot of this media is then transferred into a Xpert^® Xpress SARS CoV-2 test cartridge and assayed on the GeneXpert® instrument in our laboratory. Obtaining immediate results allowed us to assign admitted patients to either a COVID-19 or a non–COVID-19 unit, improving the issues associated with PUIs. Unfortunately, we did not have enough test cartridges to sustain this strategy of rapid individual testing of all admitted patients, and supply lines have remained uncertain.

We sought to conserve our limited Xpert Xpress SARS CoV-2 test cartridges using the strategy of pooled testing, a technique reported in Germany and by the University of Nebraska.^1,2 In this method, variable numbers of tests are pooled for a single analysis. If the test from the pooled vial is negative, these patients are all considered negative. If the pooled test is positive, all those patients need individual testing. This pooling method has been theorized to preserve test cartridges when the expected frequency of positive results is low.³

All patients admitted or placed on observation underwent SARS-CoV-2 PCR testing. The Emergency Department (ED) staff stratified patients into high or low risk to determine if they would be tested in a single send-out test (high risk) or a rapid in-house pooled group (low risk). High-risk patients were those with compatible history, physical exam, laboratory markers, and radiographic studies for COVID-19 disease. This often included increased supplemental oxygen requirement, multiple elevated inflammatory markers (including D-dimer, C-reactive protein, erythrocyte sedimentation rate, and ferritin levels), lymphopenia, and findings on chest radiograph or computed tomography scan including ground glass changes, multifocal pneumonia, or pneumonia. High-risk patients were admitted to the COVID unit or intensive care unit, had a send-out SARS-CoV-2 polymerase chain reaction (PCR) test, and were treated as a PUI until the results of their testing was known and correlated with their clinical course. Low-risk patients were those without complaints suggestive of COVID-19 infection and who may have had negative inflammatory markers, no significant lymphopenia, and negative imaging. 

The samples from 3 admitted patients thought to be at low-risk for COVID-19 using the clinical judgement of our ED staff were pooled for testing. All samples were obtained using nasopharyngeal swabs by experienced staff. The swabs from these patients were placed into a single vial of 3 mL VTM, maintaining the recommended 1 swab per mL of VTM. An aliquot of this media was then transferred into an Xpert Xpress SARS CoV-2 test cartridge and assayed on the GeneXpert instrument in our laboratory following manufacturer’s instructions. Based on analytic laboratory studies of the Cepheid Xpert Express SARS-CoV-2 test,⁴ we assume a clinical performance comparable to other reverse-transcriptase PCR (RT-PCR) tests, which have so far demonstrated sensitivities of 60% to 80% and specificities of 95% to 99%.⁵

Validation studies were performed on pools made from samples obtained from admitted patients with previously known positive and negative samples tested at the New York State Department of Health, Wadsworth Center laboratory (Albany, New York). A total of 14 samples were used for the instrument validation study, including three samples for pooled testing. The cycle threshold (Ct) value is defined as the number of PCR cycles required for the signal to be detectable. Ct values for each nucleic acid target of a known positive sample tested singly and in the pool with known negative patients were compared. A small shift in Ct values was noted between single and pooled testing, demonstrating no decrease in analytic sensitivity and suggesting that we would experience no decrease in clinical sensitivity.

We selected the pooling of 3 samples into 1 cartridge for several reasons: (1) 3-sample pools are well within the appropriate pooling size for the percentage positive rate in the population being tested. The use of larger pool sizes results in the need for more repeat testing when a positive result is obtained; (2) Given our supply lines, the projected savings would allow us to continue this strategy; and (3) Holding 3 patients in the ED until a pool was ready was manageable given our rate of admissions and ED volume.

The strategy required patients being held in the ED until a pooled group of 3 could be tested. On select occasions when holding patients in the ED to obtain a pool of 3 was not practical, 2 patients were tested in the pool. These decisions required close coordination between the laboratory, ED, and nursing staff.

This strategy resulted in 530 unique patient tests in 179 cartridges (172 with three swabs and 7 with two swabs). We had 4 positive pooled tests, requiring the use of 11 additional cartridges, for a positive rate of 0.8% (4/530) in this low-risk population (patients without COVID-19–related symptoms). There were no patients from negative pools who developed evidence of COVID-19 disease or tested positive for SARS-CoV-2 during their hospitalization. The total number of cartridges used was 190 and the number saved was 340.

The strategy of pooled testing for SARS-CoV-2 in patients admitted to our community hospital allowed us to continue rapid testing of admitted patients at low risk for COVID-19 disease during a period when supplies would otherwise not have been sufficient. We believe this strategy conserved PPE, led to a marked reduction in staff and patient anxiety, and improved patient care. Our impression is that testing all admitted patients has also been reassuring to our community. Like many others, we have observed that public fear of entering the hospital during this pandemic has caused delays in patients seeking care for non–COVID-19 conditions. We believe this strategy will help reduce those fears.

This strategy may require modification as the pandemic progresses. Our ED physicians were able to identify patients who they felt to be low risk for having COVID-19 disease based on signs, symptoms, and clinical impression during a time when we had an 8% positive rate among symptomatic outpatients and an estimated community positive rate in the range of 1% to 2%. If the rate of positive tests in our community rises, the use of pooling may need to be limited or the pool size reduced. If our supply of reagents is further limited or patient testing demand increases, the pool size may need to be increased. This will need to be balanced with our ability to hold patients in the ED while waiting for the pool size to be reached.

The strategy of pooled testing for SARS-CoV-2 has allowed us to continue to immediately test all admitted patients, thus improving patient care. It has required close coordination between multiple members of our laboratory and clinical staff and may require adjustment as the pandemic progresses. We believe it is a valuable tool during a time of limited resources that may have application in testing other low-risk groups, including healthcare workers and clients of occupational medicine services.

The authors gratefully acknowledge the support of Kirsten St. George, MAppSc, PhD, Director, Virology Laboratory, Wadsworth, NYSDOH, and the services supplied by the Wadsworth laboratory to our region.

The coronavirus disease of 2019 (COVID-19) pandemic has affected every facet of our work and personal lives. While many hope we will return to “normal” with the pandemic’s passing, there is reason to believe medicine, and society, will experience irrevocable changes. Although the number of women pursuing and practicing medicine has increased, inequities remain in compensation, academic rank, and leadership positions.^1,2 Within the workplace, women are more likely to be in frontline clinical positions, are more likely to be integral in promoting positive interpersonal relationships and collaborative work environments, and often are less represented in the high-level, decision-making roles in leadership or administration.^3,4 These well-described issues may be exacerbated during this pandemic crisis. We describe how the current COVID-19 pandemic may intensify workplace inequities for women, and propose solutions for hospitalist groups, leaders, and administrators to ensure female hospitalists continue to prosper and thrive in these tenuous times.

Increasing Demands at Home

Female physicians are more likely to have partners who are employed full-time and report spending more time on household activities including cleaning, cooking, and the care of children, compared with their male counterparts.⁵ With school and daycare closings, as well as stay-at-home orders in many US states, there has been an increase in household responsibilities and care needs for children remaining at home with a marked decrease in options for stable or emergency childcare.⁶ As compared with primary care and subspecialty colleagues who can provide a large percentage of their care through telemedicine, this is not the case for hospitalists who must be physically present to care for their patients. Therefore, hospitalists are unable to clinically “work from home” in the same way as many of their colleagues in other specialties. Increased childcare and schooling obligations, coupled with disproportionate household responsibilities and an inability to work from home, will likely result in female hospitalists struggling to meet family needs while pandemic-related work responsibilities are ramping up.⁷ In addition, women who are involved with administrative, leadership, or research activities may struggle to execute their responsibilities as a result of increased domestic duties.

Many hospitalists are also concerned about contracting COVID-19 and exposing their families to the illness given the high infection rate among healthcare workers and the shortage of personal protective equipment (PPE).^8,9 Institutions and national organizations, including the Society of Hospital Medicine, have partnered with industry to provide discounted or complimentary hotel rooms for members to aid self-isolation while providing clinical care.¹⁰ One famous photo in popular and social media showed a pulmonary and critical care physician in a tent in his garage in order to self-isolate from his family.¹¹ However, since women are often the primary caregivers for their children or other family members and may also be responsible for other important household activities, they may be unable or unwilling to remove themselves from their children and families. As a result, female hospitalists may encounter feelings of guilt or inadequacy if they’re unable to isolate in the same manner as male colleagues.⁸

Exaggerating Leadership Gap

One of the keys to a robust response to this pandemic is strong, thoughtful, and strategic leadership.¹² Institutional, regional, and national leaders are at the forefront of designing the solutions to the many problems the COVID-19 pandemic has created. The paucity of women at high-level leadership positions in institutions across the United States, including university-based, community, public, and private institutions, means that there is a lack of female representation when institutional policy is being discussed and decided.⁴ This lack of representation may lead to policies and procedures that negatively affect female hospitalists or, at best, fail to consider the needs of or support female physicians. For example, leaders of a hospital medicine group may create mandatory “backup” coverage for night and weekend shifts for their group during surge periods of the pandemic without considering implications for childcare. Finding weekday, daytime coverage is challenging for many during this time when daycares and school are closed, and finding coverage during weekend or overnight hours will be even more challenging. With increased risks for older adults with high-risk medical conditions, grandparents or other friends or family members that previously would have assisted with childcare may no longer be an option. If a female hospitalist is not a member of the leadership group that helped design this coverage structure, there could be a lack of recognition of the undue strain this coverage model could create for women in the group. Even if not intentional, such policies may hinder women’s career stability and opportunities for further advancement, as well as their ability to adequately provide care for their families. Having women as a part of the leadership group that creates policies and schedules and makes pivotal decisions is imperative, especially regarding topics of providing access and compensation for “emergency childcare,” hazard pay, shift length, work conditions, job security, sick leave, workers compensation, advancement opportunities, and hiring practices.

Compensation

The gender pay gap in medicine has been consistently demonstrated among many specialties.^13,14 The reasons for this inequity are multifactorial, and the COVID-19 pandemic has the potential to further widen this gap. With the unequal burden of unpaid care provided by women and their higher prevalence as frontline workers, they are at greater risk of needing to take unpaid leave to care for a sick family member or themselves.^6,7 Similarly, without hazard pay, those with direct clinical responsibilities bear the risk of illness for themselves and their families without adequate compensation.

Impact on Physical and Mental Health

The overall well-being of the hospitalist workforce is critical to continue to provide the highest level of care for our patients. With higher workloads at home and at work, female hospitalists are at risk for increased burnout. Burnout has been linked to many negative outcomes including poor performance, depression, suicide, and leaving the profession.¹⁵ Burnout is documented to be higher in female physicians with several contributing factors that are aggravated by gender inequities, including having children at home, gender bias, and real or perceived lack of fairness in promotion and compensation.¹⁶ The COVID-19 pandemic has amplified the stress of having children in the home, as well as concerns around fair compensation as described above. The consequences of this have yet to be fully realized but may be dire.

We propose the following recommendations to help mitigate the effects of this epidemic and to continue to move our field forward on our path to equity.

1. Closely monitor the direct and indirect effects of COVID-19 on female hospitalists. While there has been a recent increase in scholarship on the pre–COVID-19 state of gender disparities, there is still much that is unknown. As we experience this upheaval in the way our institutions function, it is even more imperative to track gender deaggregated key indicators of wellness, burnout, and productivity. This includes the use of burnout inventories, salary equity reviews, procedures that track progress toward promotion, and even focus groups of female hospitalists.

2. Inquire about the needs of women in your organization and secure the support they need. This may take the form of including women on key task forces that address personal protective equipment allocation, design new processes, and prepare for surge capacity, as well as providing wellness initiatives, fostering collaborative social networks, or connecting them with emergency childcare resources.

3. Provide a mechanism to account for lack of academic productivity during this time. This period of decreased academic productivity may disproportionately derail progress toward promotion for women. Academic institutions should consider extending deadlines for promotion or tenure, as well as increasing flexibility in metrics used to determine appropriate progress in annual performance reviews.

4. Recognize and reward increased efforts in the areas of clinical or administrative contribution. In this time of crisis, women may be stepping up and leading efforts without titles or positions in ways that are significant and meaningful for their group or organization. Recognizing the ways women are contributing in a tangible and explicit way can provide an avenue for fair compensation, recognition, and career advancement. Female hospitalists should also “manage up” by speaking up and ensuring that leaders are aware of contributions. Amplification is another powerful technique whereby unrecognized contributions can be called out by other women or men.¹⁷

5. Support diversity, inclusion, and equity efforts. Keeping equity targets at the top of priority lists for goals moving forward will be imperative. Many institutions struggled to support strong diversity, inclusion, and equity efforts prior to COVID-19; however, the pandemic has highlighted the stark racial and socioeconomic disparities that exist in healthcare.^18,19 As healthcare institutions and providers work to mitigate these disparities for patients, there would be no better time to look internally at how they pay, support, and promote their own employees. This would include actively identifying and mitigating any disparities that exist for employees by gender, race, religion, sexual orientation, ethnicity, age, or disability status.

6. Advocate for fair compensation for providers caring for COVID-19 patients. Frontline clinicians are bearing significant risks and increased workload during this crisis and should be compensated accordingly. Hazard pay, paid sick leave, medical and supplemental life insurance, and strong workers’ compensation protections for hospitalists who become ill at work are important for all clinicians, including women. Other long-term plans should include institutional interventions such as salary corrections and ongoing monitoring.²⁰

The COVID-19 pandemic will have long-term effects that are yet to be realized, including potentially widening gender disparities in medicine. With the current health and economic crises facing our institutions and nations, it can be tempting for diversity, equity, and inclusion initiatives to fall by the wayside. However, it is imperative that hospitalists, leaders, and institutions monitor the effects of the COVID-19 pandemic on women and proactively work to mitigate worsening disparities. Without this focus there is a risk that the recent gains in equity and advancement for women may be lost.

The coronavirus disease of 2019 (COVID-19) pandemic has affected every facet of our work and personal lives. While many hope we will return to “normal” with the pandemic’s passing, there is reason to believe medicine, and society, will experience irrevocable changes. Although the number of women pursuing and practicing medicine has increased, inequities remain in compensation, academic rank, and leadership positions.^1,2 Within the workplace, women are more likely to be in frontline clinical positions, are more likely to be integral in promoting positive interpersonal relationships and collaborative work environments, and often are less represented in the high-level, decision-making roles in leadership or administration.^3,4 These well-described issues may be exacerbated during this pandemic crisis. We describe how the current COVID-19 pandemic may intensify workplace inequities for women, and propose solutions for hospitalist groups, leaders, and administrators to ensure female hospitalists continue to prosper and thrive in these tenuous times.

Increasing Demands at Home

Female physicians are more likely to have partners who are employed full-time and report spending more time on household activities including cleaning, cooking, and the care of children, compared with their male counterparts.⁵ With school and daycare closings, as well as stay-at-home orders in many US states, there has been an increase in household responsibilities and care needs for children remaining at home with a marked decrease in options for stable or emergency childcare.⁶ As compared with primary care and subspecialty colleagues who can provide a large percentage of their care through telemedicine, this is not the case for hospitalists who must be physically present to care for their patients. Therefore, hospitalists are unable to clinically “work from home” in the same way as many of their colleagues in other specialties. Increased childcare and schooling obligations, coupled with disproportionate household responsibilities and an inability to work from home, will likely result in female hospitalists struggling to meet family needs while pandemic-related work responsibilities are ramping up.⁷ In addition, women who are involved with administrative, leadership, or research activities may struggle to execute their responsibilities as a result of increased domestic duties.

Many hospitalists are also concerned about contracting COVID-19 and exposing their families to the illness given the high infection rate among healthcare workers and the shortage of personal protective equipment (PPE).^8,9 Institutions and national organizations, including the Society of Hospital Medicine, have partnered with industry to provide discounted or complimentary hotel rooms for members to aid self-isolation while providing clinical care.¹⁰ One famous photo in popular and social media showed a pulmonary and critical care physician in a tent in his garage in order to self-isolate from his family.¹¹ However, since women are often the primary caregivers for their children or other family members and may also be responsible for other important household activities, they may be unable or unwilling to remove themselves from their children and families. As a result, female hospitalists may encounter feelings of guilt or inadequacy if they’re unable to isolate in the same manner as male colleagues.⁸

Exaggerating Leadership Gap

One of the keys to a robust response to this pandemic is strong, thoughtful, and strategic leadership.¹² Institutional, regional, and national leaders are at the forefront of designing the solutions to the many problems the COVID-19 pandemic has created. The paucity of women at high-level leadership positions in institutions across the United States, including university-based, community, public, and private institutions, means that there is a lack of female representation when institutional policy is being discussed and decided.⁴ This lack of representation may lead to policies and procedures that negatively affect female hospitalists or, at best, fail to consider the needs of or support female physicians. For example, leaders of a hospital medicine group may create mandatory “backup” coverage for night and weekend shifts for their group during surge periods of the pandemic without considering implications for childcare. Finding weekday, daytime coverage is challenging for many during this time when daycares and school are closed, and finding coverage during weekend or overnight hours will be even more challenging. With increased risks for older adults with high-risk medical conditions, grandparents or other friends or family members that previously would have assisted with childcare may no longer be an option. If a female hospitalist is not a member of the leadership group that helped design this coverage structure, there could be a lack of recognition of the undue strain this coverage model could create for women in the group. Even if not intentional, such policies may hinder women’s career stability and opportunities for further advancement, as well as their ability to adequately provide care for their families. Having women as a part of the leadership group that creates policies and schedules and makes pivotal decisions is imperative, especially regarding topics of providing access and compensation for “emergency childcare,” hazard pay, shift length, work conditions, job security, sick leave, workers compensation, advancement opportunities, and hiring practices.

Compensation

The gender pay gap in medicine has been consistently demonstrated among many specialties.^13,14 The reasons for this inequity are multifactorial, and the COVID-19 pandemic has the potential to further widen this gap. With the unequal burden of unpaid care provided by women and their higher prevalence as frontline workers, they are at greater risk of needing to take unpaid leave to care for a sick family member or themselves.^6,7 Similarly, without hazard pay, those with direct clinical responsibilities bear the risk of illness for themselves and their families without adequate compensation.

Impact on Physical and Mental Health

The overall well-being of the hospitalist workforce is critical to continue to provide the highest level of care for our patients. With higher workloads at home and at work, female hospitalists are at risk for increased burnout. Burnout has been linked to many negative outcomes including poor performance, depression, suicide, and leaving the profession.¹⁵ Burnout is documented to be higher in female physicians with several contributing factors that are aggravated by gender inequities, including having children at home, gender bias, and real or perceived lack of fairness in promotion and compensation.¹⁶ The COVID-19 pandemic has amplified the stress of having children in the home, as well as concerns around fair compensation as described above. The consequences of this have yet to be fully realized but may be dire.

We propose the following recommendations to help mitigate the effects of this epidemic and to continue to move our field forward on our path to equity.

1. Closely monitor the direct and indirect effects of COVID-19 on female hospitalists. While there has been a recent increase in scholarship on the pre–COVID-19 state of gender disparities, there is still much that is unknown. As we experience this upheaval in the way our institutions function, it is even more imperative to track gender deaggregated key indicators of wellness, burnout, and productivity. This includes the use of burnout inventories, salary equity reviews, procedures that track progress toward promotion, and even focus groups of female hospitalists.

2. Inquire about the needs of women in your organization and secure the support they need. This may take the form of including women on key task forces that address personal protective equipment allocation, design new processes, and prepare for surge capacity, as well as providing wellness initiatives, fostering collaborative social networks, or connecting them with emergency childcare resources.

3. Provide a mechanism to account for lack of academic productivity during this time. This period of decreased academic productivity may disproportionately derail progress toward promotion for women. Academic institutions should consider extending deadlines for promotion or tenure, as well as increasing flexibility in metrics used to determine appropriate progress in annual performance reviews.

4. Recognize and reward increased efforts in the areas of clinical or administrative contribution. In this time of crisis, women may be stepping up and leading efforts without titles or positions in ways that are significant and meaningful for their group or organization. Recognizing the ways women are contributing in a tangible and explicit way can provide an avenue for fair compensation, recognition, and career advancement. Female hospitalists should also “manage up” by speaking up and ensuring that leaders are aware of contributions. Amplification is another powerful technique whereby unrecognized contributions can be called out by other women or men.¹⁷

5. Support diversity, inclusion, and equity efforts. Keeping equity targets at the top of priority lists for goals moving forward will be imperative. Many institutions struggled to support strong diversity, inclusion, and equity efforts prior to COVID-19; however, the pandemic has highlighted the stark racial and socioeconomic disparities that exist in healthcare.^18,19 As healthcare institutions and providers work to mitigate these disparities for patients, there would be no better time to look internally at how they pay, support, and promote their own employees. This would include actively identifying and mitigating any disparities that exist for employees by gender, race, religion, sexual orientation, ethnicity, age, or disability status.

6. Advocate for fair compensation for providers caring for COVID-19 patients. Frontline clinicians are bearing significant risks and increased workload during this crisis and should be compensated accordingly. Hazard pay, paid sick leave, medical and supplemental life insurance, and strong workers’ compensation protections for hospitalists who become ill at work are important for all clinicians, including women. Other long-term plans should include institutional interventions such as salary corrections and ongoing monitoring.²⁰

The COVID-19 pandemic will have long-term effects that are yet to be realized, including potentially widening gender disparities in medicine. With the current health and economic crises facing our institutions and nations, it can be tempting for diversity, equity, and inclusion initiatives to fall by the wayside. However, it is imperative that hospitalists, leaders, and institutions monitor the effects of the COVID-19 pandemic on women and proactively work to mitigate worsening disparities. Without this focus there is a risk that the recent gains in equity and advancement for women may be lost.

The coronavirus disease of 2019 (COVID-19) pandemic has affected every facet of our work and personal lives. While many hope we will return to “normal” with the pandemic’s passing, there is reason to believe medicine, and society, will experience irrevocable changes. Although the number of women pursuing and practicing medicine has increased, inequities remain in compensation, academic rank, and leadership positions.^1,2 Within the workplace, women are more likely to be in frontline clinical positions, are more likely to be integral in promoting positive interpersonal relationships and collaborative work environments, and often are less represented in the high-level, decision-making roles in leadership or administration.^3,4 These well-described issues may be exacerbated during this pandemic crisis. We describe how the current COVID-19 pandemic may intensify workplace inequities for women, and propose solutions for hospitalist groups, leaders, and administrators to ensure female hospitalists continue to prosper and thrive in these tenuous times.

Increasing Demands at Home

Female physicians are more likely to have partners who are employed full-time and report spending more time on household activities including cleaning, cooking, and the care of children, compared with their male counterparts.⁵ With school and daycare closings, as well as stay-at-home orders in many US states, there has been an increase in household responsibilities and care needs for children remaining at home with a marked decrease in options for stable or emergency childcare.⁶ As compared with primary care and subspecialty colleagues who can provide a large percentage of their care through telemedicine, this is not the case for hospitalists who must be physically present to care for their patients. Therefore, hospitalists are unable to clinically “work from home” in the same way as many of their colleagues in other specialties. Increased childcare and schooling obligations, coupled with disproportionate household responsibilities and an inability to work from home, will likely result in female hospitalists struggling to meet family needs while pandemic-related work responsibilities are ramping up.⁷ In addition, women who are involved with administrative, leadership, or research activities may struggle to execute their responsibilities as a result of increased domestic duties.

Many hospitalists are also concerned about contracting COVID-19 and exposing their families to the illness given the high infection rate among healthcare workers and the shortage of personal protective equipment (PPE).^8,9 Institutions and national organizations, including the Society of Hospital Medicine, have partnered with industry to provide discounted or complimentary hotel rooms for members to aid self-isolation while providing clinical care.¹⁰ One famous photo in popular and social media showed a pulmonary and critical care physician in a tent in his garage in order to self-isolate from his family.¹¹ However, since women are often the primary caregivers for their children or other family members and may also be responsible for other important household activities, they may be unable or unwilling to remove themselves from their children and families. As a result, female hospitalists may encounter feelings of guilt or inadequacy if they’re unable to isolate in the same manner as male colleagues.⁸

Exaggerating Leadership Gap

One of the keys to a robust response to this pandemic is strong, thoughtful, and strategic leadership.¹² Institutional, regional, and national leaders are at the forefront of designing the solutions to the many problems the COVID-19 pandemic has created. The paucity of women at high-level leadership positions in institutions across the United States, including university-based, community, public, and private institutions, means that there is a lack of female representation when institutional policy is being discussed and decided.⁴ This lack of representation may lead to policies and procedures that negatively affect female hospitalists or, at best, fail to consider the needs of or support female physicians. For example, leaders of a hospital medicine group may create mandatory “backup” coverage for night and weekend shifts for their group during surge periods of the pandemic without considering implications for childcare. Finding weekday, daytime coverage is challenging for many during this time when daycares and school are closed, and finding coverage during weekend or overnight hours will be even more challenging. With increased risks for older adults with high-risk medical conditions, grandparents or other friends or family members that previously would have assisted with childcare may no longer be an option. If a female hospitalist is not a member of the leadership group that helped design this coverage structure, there could be a lack of recognition of the undue strain this coverage model could create for women in the group. Even if not intentional, such policies may hinder women’s career stability and opportunities for further advancement, as well as their ability to adequately provide care for their families. Having women as a part of the leadership group that creates policies and schedules and makes pivotal decisions is imperative, especially regarding topics of providing access and compensation for “emergency childcare,” hazard pay, shift length, work conditions, job security, sick leave, workers compensation, advancement opportunities, and hiring practices.

Compensation

The gender pay gap in medicine has been consistently demonstrated among many specialties.^13,14 The reasons for this inequity are multifactorial, and the COVID-19 pandemic has the potential to further widen this gap. With the unequal burden of unpaid care provided by women and their higher prevalence as frontline workers, they are at greater risk of needing to take unpaid leave to care for a sick family member or themselves.^6,7 Similarly, without hazard pay, those with direct clinical responsibilities bear the risk of illness for themselves and their families without adequate compensation.

Impact on Physical and Mental Health

The overall well-being of the hospitalist workforce is critical to continue to provide the highest level of care for our patients. With higher workloads at home and at work, female hospitalists are at risk for increased burnout. Burnout has been linked to many negative outcomes including poor performance, depression, suicide, and leaving the profession.¹⁵ Burnout is documented to be higher in female physicians with several contributing factors that are aggravated by gender inequities, including having children at home, gender bias, and real or perceived lack of fairness in promotion and compensation.¹⁶ The COVID-19 pandemic has amplified the stress of having children in the home, as well as concerns around fair compensation as described above. The consequences of this have yet to be fully realized but may be dire.

We propose the following recommendations to help mitigate the effects of this epidemic and to continue to move our field forward on our path to equity.

1. Closely monitor the direct and indirect effects of COVID-19 on female hospitalists. While there has been a recent increase in scholarship on the pre–COVID-19 state of gender disparities, there is still much that is unknown. As we experience this upheaval in the way our institutions function, it is even more imperative to track gender deaggregated key indicators of wellness, burnout, and productivity. This includes the use of burnout inventories, salary equity reviews, procedures that track progress toward promotion, and even focus groups of female hospitalists.

2. Inquire about the needs of women in your organization and secure the support they need. This may take the form of including women on key task forces that address personal protective equipment allocation, design new processes, and prepare for surge capacity, as well as providing wellness initiatives, fostering collaborative social networks, or connecting them with emergency childcare resources.

3. Provide a mechanism to account for lack of academic productivity during this time. This period of decreased academic productivity may disproportionately derail progress toward promotion for women. Academic institutions should consider extending deadlines for promotion or tenure, as well as increasing flexibility in metrics used to determine appropriate progress in annual performance reviews.

4. Recognize and reward increased efforts in the areas of clinical or administrative contribution. In this time of crisis, women may be stepping up and leading efforts without titles or positions in ways that are significant and meaningful for their group or organization. Recognizing the ways women are contributing in a tangible and explicit way can provide an avenue for fair compensation, recognition, and career advancement. Female hospitalists should also “manage up” by speaking up and ensuring that leaders are aware of contributions. Amplification is another powerful technique whereby unrecognized contributions can be called out by other women or men.¹⁷

5. Support diversity, inclusion, and equity efforts. Keeping equity targets at the top of priority lists for goals moving forward will be imperative. Many institutions struggled to support strong diversity, inclusion, and equity efforts prior to COVID-19; however, the pandemic has highlighted the stark racial and socioeconomic disparities that exist in healthcare.^18,19 As healthcare institutions and providers work to mitigate these disparities for patients, there would be no better time to look internally at how they pay, support, and promote their own employees. This would include actively identifying and mitigating any disparities that exist for employees by gender, race, religion, sexual orientation, ethnicity, age, or disability status.

6. Advocate for fair compensation for providers caring for COVID-19 patients. Frontline clinicians are bearing significant risks and increased workload during this crisis and should be compensated accordingly. Hazard pay, paid sick leave, medical and supplemental life insurance, and strong workers’ compensation protections for hospitalists who become ill at work are important for all clinicians, including women. Other long-term plans should include institutional interventions such as salary corrections and ongoing monitoring.²⁰

The COVID-19 pandemic will have long-term effects that are yet to be realized, including potentially widening gender disparities in medicine. With the current health and economic crises facing our institutions and nations, it can be tempting for diversity, equity, and inclusion initiatives to fall by the wayside. However, it is imperative that hospitalists, leaders, and institutions monitor the effects of the COVID-19 pandemic on women and proactively work to mitigate worsening disparities. Without this focus there is a risk that the recent gains in equity and advancement for women may be lost.

Rituximab is a genetically engineered chimeric immunoglobulin G1 monoclonal antibody. It functions by binding to the CD20 antigen on the surface of B-cell lymphocytes, leading to complement-dependent cytotoxicity and antibody-dependent cellular cytotoxicity.¹ The US Food and Drug Administration approved this therapy to treat patients with B-cell non-Hodgkin lymphoma and chronic lymphocytic leukemia, along with other nonmalignant indications, including pemphigus vulgaris and rheumatoid arthritis (RA). Historically, a significant amount of time and labor on behalf of medical personnel has been required to administer rituximab according to the original manufacturer’s labeling due to the boxed warning associated with infusion-related reactions (IRRs).²

Originally, the elongated infusion times that were recommended for rituximab were largely due to the perceived risk of serious infusion-related adverse drug reactions. Slower infusion times should reduce the risk of a reaction and are considered to be a good option for those patients who are at a high risk of having a severe IRRs to rituximab. Examples of high-risk patients from previous studies include those with significant cardiovascular disease, a circulating lymphocyte count ≤ 5,000/µL at the start of infusion, and those who have previously had a reaction to rituximab.^3-5 In appropriate patients, research has shown a decreasing incidence of all-grade IRRs for patients who are prescribed rituximab as they receive more doses of the drug.^2,6 The ability to identify suitable patients for 90-minute infusions of rituximab and the prospect of better health system resource utilization has led investigators to study the effects of shortened infusion times.

The RATE trial addressed this subject with a phase 3 safety study on the effects of a 90-minute rituximab infusion for patients with previously untreated diffuse large B-cell and follicular lymphoma.³ The patients in this study received their first dose of rituximab using the traditional infusion approach. If it was well-tolerated, they received subsequent rituximab infusions using a 90-minute protocol. Only 1.1% of patients who had previously received a rituximab infusion developed a grade 3 or 4 IRR when receiving a faster infusion of the drug for the first time.³ This result led to the addition of instructions for a 90-minute infusion to the package insert.²

In contrast to the RATE trial, the RATE-RA trial evaluated the incidence of IRRs in patients who received rituximab for nonmalignant indications. This study assessed patients with RA receiving rituximab for > 120 minutes. The authors reported 0.6% of the patients in the study developed a grade 3 or 4 IRR associated with the first 120-minute infusion of the medication.⁵ The researchers concluded that rituximab can be administered at a faster rate during second and subsequent infusions in patients who have been shown to tolerate traditional infusions without increasing the risk or severity of IRRs.⁵

The US Department of Veterans Affairs (VA) Richard L. Roudebush VA Medical Center (RLRVAMC) in Indianapolis, Indiana, uses traditional directions for the infusion of rituximab due to perceived tolerability and safety concerns specifically in a veteran population—even while other VA medical centers have implemented shortened infusion protocols. This also is despite the fact that available research shows rapid infusions of the drug are well tolerated in a variety of community settings.^7,8 Anticipated benefits of implementing a protocol include savings in chair time at the institution’s infusion clinic along with increased nursing and patient satisfaction. This project was conducted to prepare, implement, and assess the safety of a 90-minute rituximab protocol at the RLRVAMC.

Methods

Proactive measures were required before and during the implementation of the 90-minute protocol to ensure patient safety and staff satisfaction. Updates to the RLRVAMC policy for the management of medical emergencies within the infusion center were reviewed and approved by the acute care committee and nursing leadership. A protocol was developed to identify eligible patients, outline the hypersensitivity protocol, instruct pharmacy personnel on admixture preparation, and provide a titration schedule based on dose. Order sets also were created to assist health care providers (HCPs) with the prescribing of rituximab for nonantineoplastic indications. Educational materials were crafted to assist with order verification, product preparation, labeling, and programming of infusion pumps. Live education was provided for physicians, pharmacists, and nurses to ensure smooth implementation of the protocol and appropriate management of medical emergencies based on the updated policy.

Study Design

Nursing staff in the infusion clinic were surveyed once before a live education session and again after the conclusion of the study. The purpose of the survey was to assess the prior experience and current comfort level of the nursing staff with administering rituximab over 90 minutes. Nurses were asked the following questions: (1) Do you have prior experience administering rituximab via 90-minute infusion; and (2) do you feel comfortable administering rituximab via 90-minute infusion?

A weekly report of patients who received rituximab between November 1, 2018 through April 1, 2019 at the RLRVAMC was generated. HCPs were alerted to eligible patients based on protocol requirements. The HCPs then made the final determination and entered orders accordingly.

This study was a retrospective chart review of all who patients received a rapid infusion of rituximab. Patients who were included if they were aged ≥ 18 years, received rituximab infusions in the RLRVAMC infusion clinic, had an absolute lymphocyte count ≤ 5,000/mm³ at the time of their rapid infusions, had no significant baseline cardiovascular disease or respiratory compromise, and had no prior grade 3 or 4 rituximab IRRs as defined by Common Terminology Criteria for Adverse Events (CTCAE) Version 5.0.⁹ This study was a quality improvement initiative and considered exempt by the institutional review board. All data were deidentified and secured to ensure patient privacy.

The primary endpoint for this study was the incidence of grade 3 or 4 IRRs associated with the rapid infusion of rituximab. Secondary endpoints included the proportion of patients who experienced a grade 3 or 4 infusion reaction, who received proper treatment according to the institution’s hypersensitivity protocol, savings in infusion clinic chair time, and nursing satisfaction with education and implementation of the rapid infusion rituximab protocol.

The following data were collected for all included patients: demographics, lactic acid dehydrogenase level, white blood cell count, and absolute lymphocyte count prior to rituximab infusion, indication for treatment, dose of rituximab for 90-minute infusion, date of infusion, starting time, ending time, number of previous rituximab infusions within the past 3 months, symptoms of infusion reactions during rituximab infusion, and grade of any infusion reactions that occurred.

Estimated savings in infusion clinic chair time was calculated by taking the difference in time between each completed rapid infusion and the estimated amount of time it would have taken for each patient to receive a traditional infusion. The estimated amount of time for traditional infusion was determined by following the institution’s protocol for administering rituximab to patients who previously tolerated their first dose of the drug (eg, 100 mg/h starting rate and increasing by 100 mg/h every 30 minutes to a maximum infusion rate of 400 mg/h). All endpoints were analyzed using descriptive statistics.

Results

Between November 1, 2018 and April 1, 2019, 11 patients received a total of 24 rapid infusions of rituximab. The majority of patients included in the study were older males, and the most common indication for rapid infusion was follicular lymphoma (Table 1).

Primary Endpoint

All patients who received a rapid infusion of rituximab were reviewed in the analysis of the primary and secondary endpoints. Among the 24 rapid infusions of rituximab, 1 infusion was stopped due to the patient experiencing a grade 3 IRR according to criteria from CTCAE Version 5.0. The patient was found to have dysphagia at baseline and experienced severe symptoms in the days following the first infusion that put the patient at high risk for subsequent infusion related concerns. Eligibility criteria for the 90-minute protocol were updated based on these findings. No patient experienced a grade 4 or 5 IRR. The remaining 23 infusions were well tolerated by the patients with no clinically significant events.

Secondary Endpoints

The patient who experienced a grade 3 IRR to rituximab received proper treatment by infusion clinic nurses according to the RLRVAMC hypersensitivity protocol. Patients who received rapid infusions of rituximab had a mean length of infusion of 95.0 minutes. This was in contrast to the mean time of each patient’s previous nonrapid infusion of 134.3 minutes. The difference between the 2 values equated to a savings in infusion clinic chair mean time of 39.3 minutes per patient.

Nurses were asked whether they had prior experience administering rituximab via 90-minute infusion and whether they felt comfortable administering a 90-minute rituximab infusion. Before the live education session, none of the nurses surveyed had prior experience or felt comfortable administering rituximab over 90 minutes. When the nurses were surveyed poststudy, all reported that they were experienced administering rituximab and felt comfortable with the process (Table 2).

Discussion

The infusion of rituximab has been associated with significant challenges related to the time and labor required. Although a vast number of institutions across the country now infuse the medication over an abbreviated time, HCP concerns for patient safety and appropriate use of hypersensitivity protocol in a veteran population delayed implementation at RLRVAMC. The results from this quality improvement initiative highlight the positive impact of the proactive measures that were used to implement the rapid infusion protocol for rituximab on improving HCP prescribing rates, nursing satisfaction, and appropriate management of IRRs.

Rapid infusion saved on average 39.3 minutes per patient in infusion clinic chair time. Each successful rapid infusion of rituximab potentially opened additional time in clinic for ≥ 1 patients to receive an infusion therapy. The RLRVAMC usually operated at maximum capacity, so the ability to accommodate more patients helped decrease hospital admittances for time-sensitive infusions.

The initial criteria used to screen patients to determine whether a rapid infusion of rituximab would be appropriate was based on inclusion and exclusion criteria for past studies on the same subject.^3-5 The incidence of hypersensitivity reactions associated with study participants who received rapid rituximab infusions also resembles past research done on the subject, which is important to note due to prior misconceptions of staff at the institution of a higher risk of reaction in this specific veteran population. One patient with RA experienced a grade 3 IRR in this study. Although this patient met the original inclusion criteria, the patient had baseline dysphagia, and following the first infusion, reported to the emergency department (ED) with symptoms of delayed anaphylaxis. In this case, the order for rapid infusion was placed in advance and the prescriber was unaware of the ED visit. Based on this event, eligibility criteria for 90-minute rituximab infusions were updated to include additional information specifying that candidates for a rapid infusion also may have no baseline airway compromise. This hypersensitivity reaction also highlighted the need for decision support technology to assist HCPs in patient selection as well as empowering nursing and pharmacy staff to identify concerns once they place orders.

Over the course of the study, investigators assisted the HCPs with preparation of orders for the rapid infusion of rituximab for antineoplastic indications. Due to feasibility issues with this practice moving forward, order sets containing rituximab were updated to include a 90-minute option. This created a more standardized process that allowed HCPs to screen potential patients on their own. The expectation is that HCPs will be more likely to order 90-minute infusions for eligible patients in the future with this efficient and safer process.

Limitations

The small sample size in this study was a limitation. Retrospective data related to the management of infusion reactions and length of infusions were collected from nursing notes. The prospective use of a standardized evaluation tool for adverse drug reactions as well as bar code medication administration technology would improve the data available for this study. Additional studies also would be useful to validate the results.

Conclusions

The proactive measures that were used to implement the rapid infusion rituximab protocol improved HCP prescribing rates, nursing satisfaction, and the management of IRRs. Potential time savings with each infusion was significant. This study confirmed appropriateness of rapid administration of rituximab in this veteran population and has increased interest in implementing other rapid infusion protocols. Protocols, education, and order sets are being developed for daratumumab and infliximab.

Rituximab is a genetically engineered chimeric immunoglobulin G1 monoclonal antibody. It functions by binding to the CD20 antigen on the surface of B-cell lymphocytes, leading to complement-dependent cytotoxicity and antibody-dependent cellular cytotoxicity.¹ The US Food and Drug Administration approved this therapy to treat patients with B-cell non-Hodgkin lymphoma and chronic lymphocytic leukemia, along with other nonmalignant indications, including pemphigus vulgaris and rheumatoid arthritis (RA). Historically, a significant amount of time and labor on behalf of medical personnel has been required to administer rituximab according to the original manufacturer’s labeling due to the boxed warning associated with infusion-related reactions (IRRs).²

Originally, the elongated infusion times that were recommended for rituximab were largely due to the perceived risk of serious infusion-related adverse drug reactions. Slower infusion times should reduce the risk of a reaction and are considered to be a good option for those patients who are at a high risk of having a severe IRRs to rituximab. Examples of high-risk patients from previous studies include those with significant cardiovascular disease, a circulating lymphocyte count ≤ 5,000/µL at the start of infusion, and those who have previously had a reaction to rituximab.^3-5 In appropriate patients, research has shown a decreasing incidence of all-grade IRRs for patients who are prescribed rituximab as they receive more doses of the drug.^2,6 The ability to identify suitable patients for 90-minute infusions of rituximab and the prospect of better health system resource utilization has led investigators to study the effects of shortened infusion times.

The RATE trial addressed this subject with a phase 3 safety study on the effects of a 90-minute rituximab infusion for patients with previously untreated diffuse large B-cell and follicular lymphoma.³ The patients in this study received their first dose of rituximab using the traditional infusion approach. If it was well-tolerated, they received subsequent rituximab infusions using a 90-minute protocol. Only 1.1% of patients who had previously received a rituximab infusion developed a grade 3 or 4 IRR when receiving a faster infusion of the drug for the first time.³ This result led to the addition of instructions for a 90-minute infusion to the package insert.²

In contrast to the RATE trial, the RATE-RA trial evaluated the incidence of IRRs in patients who received rituximab for nonmalignant indications. This study assessed patients with RA receiving rituximab for > 120 minutes. The authors reported 0.6% of the patients in the study developed a grade 3 or 4 IRR associated with the first 120-minute infusion of the medication.⁵ The researchers concluded that rituximab can be administered at a faster rate during second and subsequent infusions in patients who have been shown to tolerate traditional infusions without increasing the risk or severity of IRRs.⁵

The US Department of Veterans Affairs (VA) Richard L. Roudebush VA Medical Center (RLRVAMC) in Indianapolis, Indiana, uses traditional directions for the infusion of rituximab due to perceived tolerability and safety concerns specifically in a veteran population—even while other VA medical centers have implemented shortened infusion protocols. This also is despite the fact that available research shows rapid infusions of the drug are well tolerated in a variety of community settings.^7,8 Anticipated benefits of implementing a protocol include savings in chair time at the institution’s infusion clinic along with increased nursing and patient satisfaction. This project was conducted to prepare, implement, and assess the safety of a 90-minute rituximab protocol at the RLRVAMC.

Methods

Proactive measures were required before and during the implementation of the 90-minute protocol to ensure patient safety and staff satisfaction. Updates to the RLRVAMC policy for the management of medical emergencies within the infusion center were reviewed and approved by the acute care committee and nursing leadership. A protocol was developed to identify eligible patients, outline the hypersensitivity protocol, instruct pharmacy personnel on admixture preparation, and provide a titration schedule based on dose. Order sets also were created to assist health care providers (HCPs) with the prescribing of rituximab for nonantineoplastic indications. Educational materials were crafted to assist with order verification, product preparation, labeling, and programming of infusion pumps. Live education was provided for physicians, pharmacists, and nurses to ensure smooth implementation of the protocol and appropriate management of medical emergencies based on the updated policy.

Study Design

Nursing staff in the infusion clinic were surveyed once before a live education session and again after the conclusion of the study. The purpose of the survey was to assess the prior experience and current comfort level of the nursing staff with administering rituximab over 90 minutes. Nurses were asked the following questions: (1) Do you have prior experience administering rituximab via 90-minute infusion; and (2) do you feel comfortable administering rituximab via 90-minute infusion?

A weekly report of patients who received rituximab between November 1, 2018 through April 1, 2019 at the RLRVAMC was generated. HCPs were alerted to eligible patients based on protocol requirements. The HCPs then made the final determination and entered orders accordingly.

This study was a retrospective chart review of all who patients received a rapid infusion of rituximab. Patients who were included if they were aged ≥ 18 years, received rituximab infusions in the RLRVAMC infusion clinic, had an absolute lymphocyte count ≤ 5,000/mm³ at the time of their rapid infusions, had no significant baseline cardiovascular disease or respiratory compromise, and had no prior grade 3 or 4 rituximab IRRs as defined by Common Terminology Criteria for Adverse Events (CTCAE) Version 5.0.⁹ This study was a quality improvement initiative and considered exempt by the institutional review board. All data were deidentified and secured to ensure patient privacy.

The primary endpoint for this study was the incidence of grade 3 or 4 IRRs associated with the rapid infusion of rituximab. Secondary endpoints included the proportion of patients who experienced a grade 3 or 4 infusion reaction, who received proper treatment according to the institution’s hypersensitivity protocol, savings in infusion clinic chair time, and nursing satisfaction with education and implementation of the rapid infusion rituximab protocol.

The following data were collected for all included patients: demographics, lactic acid dehydrogenase level, white blood cell count, and absolute lymphocyte count prior to rituximab infusion, indication for treatment, dose of rituximab for 90-minute infusion, date of infusion, starting time, ending time, number of previous rituximab infusions within the past 3 months, symptoms of infusion reactions during rituximab infusion, and grade of any infusion reactions that occurred.

Estimated savings in infusion clinic chair time was calculated by taking the difference in time between each completed rapid infusion and the estimated amount of time it would have taken for each patient to receive a traditional infusion. The estimated amount of time for traditional infusion was determined by following the institution’s protocol for administering rituximab to patients who previously tolerated their first dose of the drug (eg, 100 mg/h starting rate and increasing by 100 mg/h every 30 minutes to a maximum infusion rate of 400 mg/h). All endpoints were analyzed using descriptive statistics.

Results

Between November 1, 2018 and April 1, 2019, 11 patients received a total of 24 rapid infusions of rituximab. The majority of patients included in the study were older males, and the most common indication for rapid infusion was follicular lymphoma (Table 1).

Primary Endpoint

All patients who received a rapid infusion of rituximab were reviewed in the analysis of the primary and secondary endpoints. Among the 24 rapid infusions of rituximab, 1 infusion was stopped due to the patient experiencing a grade 3 IRR according to criteria from CTCAE Version 5.0. The patient was found to have dysphagia at baseline and experienced severe symptoms in the days following the first infusion that put the patient at high risk for subsequent infusion related concerns. Eligibility criteria for the 90-minute protocol were updated based on these findings. No patient experienced a grade 4 or 5 IRR. The remaining 23 infusions were well tolerated by the patients with no clinically significant events.

Secondary Endpoints

The patient who experienced a grade 3 IRR to rituximab received proper treatment by infusion clinic nurses according to the RLRVAMC hypersensitivity protocol. Patients who received rapid infusions of rituximab had a mean length of infusion of 95.0 minutes. This was in contrast to the mean time of each patient’s previous nonrapid infusion of 134.3 minutes. The difference between the 2 values equated to a savings in infusion clinic chair mean time of 39.3 minutes per patient.

Nurses were asked whether they had prior experience administering rituximab via 90-minute infusion and whether they felt comfortable administering a 90-minute rituximab infusion. Before the live education session, none of the nurses surveyed had prior experience or felt comfortable administering rituximab over 90 minutes. When the nurses were surveyed poststudy, all reported that they were experienced administering rituximab and felt comfortable with the process (Table 2).

Discussion

The infusion of rituximab has been associated with significant challenges related to the time and labor required. Although a vast number of institutions across the country now infuse the medication over an abbreviated time, HCP concerns for patient safety and appropriate use of hypersensitivity protocol in a veteran population delayed implementation at RLRVAMC. The results from this quality improvement initiative highlight the positive impact of the proactive measures that were used to implement the rapid infusion protocol for rituximab on improving HCP prescribing rates, nursing satisfaction, and appropriate management of IRRs.

Rapid infusion saved on average 39.3 minutes per patient in infusion clinic chair time. Each successful rapid infusion of rituximab potentially opened additional time in clinic for ≥ 1 patients to receive an infusion therapy. The RLRVAMC usually operated at maximum capacity, so the ability to accommodate more patients helped decrease hospital admittances for time-sensitive infusions.

The initial criteria used to screen patients to determine whether a rapid infusion of rituximab would be appropriate was based on inclusion and exclusion criteria for past studies on the same subject.^3-5 The incidence of hypersensitivity reactions associated with study participants who received rapid rituximab infusions also resembles past research done on the subject, which is important to note due to prior misconceptions of staff at the institution of a higher risk of reaction in this specific veteran population. One patient with RA experienced a grade 3 IRR in this study. Although this patient met the original inclusion criteria, the patient had baseline dysphagia, and following the first infusion, reported to the emergency department (ED) with symptoms of delayed anaphylaxis. In this case, the order for rapid infusion was placed in advance and the prescriber was unaware of the ED visit. Based on this event, eligibility criteria for 90-minute rituximab infusions were updated to include additional information specifying that candidates for a rapid infusion also may have no baseline airway compromise. This hypersensitivity reaction also highlighted the need for decision support technology to assist HCPs in patient selection as well as empowering nursing and pharmacy staff to identify concerns once they place orders.

Over the course of the study, investigators assisted the HCPs with preparation of orders for the rapid infusion of rituximab for antineoplastic indications. Due to feasibility issues with this practice moving forward, order sets containing rituximab were updated to include a 90-minute option. This created a more standardized process that allowed HCPs to screen potential patients on their own. The expectation is that HCPs will be more likely to order 90-minute infusions for eligible patients in the future with this efficient and safer process.

Limitations

The small sample size in this study was a limitation. Retrospective data related to the management of infusion reactions and length of infusions were collected from nursing notes. The prospective use of a standardized evaluation tool for adverse drug reactions as well as bar code medication administration technology would improve the data available for this study. Additional studies also would be useful to validate the results.

Conclusions

The proactive measures that were used to implement the rapid infusion rituximab protocol improved HCP prescribing rates, nursing satisfaction, and the management of IRRs. Potential time savings with each infusion was significant. This study confirmed appropriateness of rapid administration of rituximab in this veteran population and has increased interest in implementing other rapid infusion protocols. Protocols, education, and order sets are being developed for daratumumab and infliximab.

Rituximab is a genetically engineered chimeric immunoglobulin G1 monoclonal antibody. It functions by binding to the CD20 antigen on the surface of B-cell lymphocytes, leading to complement-dependent cytotoxicity and antibody-dependent cellular cytotoxicity.¹ The US Food and Drug Administration approved this therapy to treat patients with B-cell non-Hodgkin lymphoma and chronic lymphocytic leukemia, along with other nonmalignant indications, including pemphigus vulgaris and rheumatoid arthritis (RA). Historically, a significant amount of time and labor on behalf of medical personnel has been required to administer rituximab according to the original manufacturer’s labeling due to the boxed warning associated with infusion-related reactions (IRRs).²

Originally, the elongated infusion times that were recommended for rituximab were largely due to the perceived risk of serious infusion-related adverse drug reactions. Slower infusion times should reduce the risk of a reaction and are considered to be a good option for those patients who are at a high risk of having a severe IRRs to rituximab. Examples of high-risk patients from previous studies include those with significant cardiovascular disease, a circulating lymphocyte count ≤ 5,000/µL at the start of infusion, and those who have previously had a reaction to rituximab.^3-5 In appropriate patients, research has shown a decreasing incidence of all-grade IRRs for patients who are prescribed rituximab as they receive more doses of the drug.^2,6 The ability to identify suitable patients for 90-minute infusions of rituximab and the prospect of better health system resource utilization has led investigators to study the effects of shortened infusion times.

The RATE trial addressed this subject with a phase 3 safety study on the effects of a 90-minute rituximab infusion for patients with previously untreated diffuse large B-cell and follicular lymphoma.³ The patients in this study received their first dose of rituximab using the traditional infusion approach. If it was well-tolerated, they received subsequent rituximab infusions using a 90-minute protocol. Only 1.1% of patients who had previously received a rituximab infusion developed a grade 3 or 4 IRR when receiving a faster infusion of the drug for the first time.³ This result led to the addition of instructions for a 90-minute infusion to the package insert.²

In contrast to the RATE trial, the RATE-RA trial evaluated the incidence of IRRs in patients who received rituximab for nonmalignant indications. This study assessed patients with RA receiving rituximab for > 120 minutes. The authors reported 0.6% of the patients in the study developed a grade 3 or 4 IRR associated with the first 120-minute infusion of the medication.⁵ The researchers concluded that rituximab can be administered at a faster rate during second and subsequent infusions in patients who have been shown to tolerate traditional infusions without increasing the risk or severity of IRRs.⁵

The US Department of Veterans Affairs (VA) Richard L. Roudebush VA Medical Center (RLRVAMC) in Indianapolis, Indiana, uses traditional directions for the infusion of rituximab due to perceived tolerability and safety concerns specifically in a veteran population—even while other VA medical centers have implemented shortened infusion protocols. This also is despite the fact that available research shows rapid infusions of the drug are well tolerated in a variety of community settings.^7,8 Anticipated benefits of implementing a protocol include savings in chair time at the institution’s infusion clinic along with increased nursing and patient satisfaction. This project was conducted to prepare, implement, and assess the safety of a 90-minute rituximab protocol at the RLRVAMC.

Methods

Proactive measures were required before and during the implementation of the 90-minute protocol to ensure patient safety and staff satisfaction. Updates to the RLRVAMC policy for the management of medical emergencies within the infusion center were reviewed and approved by the acute care committee and nursing leadership. A protocol was developed to identify eligible patients, outline the hypersensitivity protocol, instruct pharmacy personnel on admixture preparation, and provide a titration schedule based on dose. Order sets also were created to assist health care providers (HCPs) with the prescribing of rituximab for nonantineoplastic indications. Educational materials were crafted to assist with order verification, product preparation, labeling, and programming of infusion pumps. Live education was provided for physicians, pharmacists, and nurses to ensure smooth implementation of the protocol and appropriate management of medical emergencies based on the updated policy.

Study Design

Nursing staff in the infusion clinic were surveyed once before a live education session and again after the conclusion of the study. The purpose of the survey was to assess the prior experience and current comfort level of the nursing staff with administering rituximab over 90 minutes. Nurses were asked the following questions: (1) Do you have prior experience administering rituximab via 90-minute infusion; and (2) do you feel comfortable administering rituximab via 90-minute infusion?

A weekly report of patients who received rituximab between November 1, 2018 through April 1, 2019 at the RLRVAMC was generated. HCPs were alerted to eligible patients based on protocol requirements. The HCPs then made the final determination and entered orders accordingly.

This study was a retrospective chart review of all who patients received a rapid infusion of rituximab. Patients who were included if they were aged ≥ 18 years, received rituximab infusions in the RLRVAMC infusion clinic, had an absolute lymphocyte count ≤ 5,000/mm³ at the time of their rapid infusions, had no significant baseline cardiovascular disease or respiratory compromise, and had no prior grade 3 or 4 rituximab IRRs as defined by Common Terminology Criteria for Adverse Events (CTCAE) Version 5.0.⁹ This study was a quality improvement initiative and considered exempt by the institutional review board. All data were deidentified and secured to ensure patient privacy.

The primary endpoint for this study was the incidence of grade 3 or 4 IRRs associated with the rapid infusion of rituximab. Secondary endpoints included the proportion of patients who experienced a grade 3 or 4 infusion reaction, who received proper treatment according to the institution’s hypersensitivity protocol, savings in infusion clinic chair time, and nursing satisfaction with education and implementation of the rapid infusion rituximab protocol.

The following data were collected for all included patients: demographics, lactic acid dehydrogenase level, white blood cell count, and absolute lymphocyte count prior to rituximab infusion, indication for treatment, dose of rituximab for 90-minute infusion, date of infusion, starting time, ending time, number of previous rituximab infusions within the past 3 months, symptoms of infusion reactions during rituximab infusion, and grade of any infusion reactions that occurred.

Estimated savings in infusion clinic chair time was calculated by taking the difference in time between each completed rapid infusion and the estimated amount of time it would have taken for each patient to receive a traditional infusion. The estimated amount of time for traditional infusion was determined by following the institution’s protocol for administering rituximab to patients who previously tolerated their first dose of the drug (eg, 100 mg/h starting rate and increasing by 100 mg/h every 30 minutes to a maximum infusion rate of 400 mg/h). All endpoints were analyzed using descriptive statistics.

Results

Between November 1, 2018 and April 1, 2019, 11 patients received a total of 24 rapid infusions of rituximab. The majority of patients included in the study were older males, and the most common indication for rapid infusion was follicular lymphoma (Table 1).

Primary Endpoint

All patients who received a rapid infusion of rituximab were reviewed in the analysis of the primary and secondary endpoints. Among the 24 rapid infusions of rituximab, 1 infusion was stopped due to the patient experiencing a grade 3 IRR according to criteria from CTCAE Version 5.0. The patient was found to have dysphagia at baseline and experienced severe symptoms in the days following the first infusion that put the patient at high risk for subsequent infusion related concerns. Eligibility criteria for the 90-minute protocol were updated based on these findings. No patient experienced a grade 4 or 5 IRR. The remaining 23 infusions were well tolerated by the patients with no clinically significant events.

Secondary Endpoints

The patient who experienced a grade 3 IRR to rituximab received proper treatment by infusion clinic nurses according to the RLRVAMC hypersensitivity protocol. Patients who received rapid infusions of rituximab had a mean length of infusion of 95.0 minutes. This was in contrast to the mean time of each patient’s previous nonrapid infusion of 134.3 minutes. The difference between the 2 values equated to a savings in infusion clinic chair mean time of 39.3 minutes per patient.

Nurses were asked whether they had prior experience administering rituximab via 90-minute infusion and whether they felt comfortable administering a 90-minute rituximab infusion. Before the live education session, none of the nurses surveyed had prior experience or felt comfortable administering rituximab over 90 minutes. When the nurses were surveyed poststudy, all reported that they were experienced administering rituximab and felt comfortable with the process (Table 2).

Discussion

The infusion of rituximab has been associated with significant challenges related to the time and labor required. Although a vast number of institutions across the country now infuse the medication over an abbreviated time, HCP concerns for patient safety and appropriate use of hypersensitivity protocol in a veteran population delayed implementation at RLRVAMC. The results from this quality improvement initiative highlight the positive impact of the proactive measures that were used to implement the rapid infusion protocol for rituximab on improving HCP prescribing rates, nursing satisfaction, and appropriate management of IRRs.

Rapid infusion saved on average 39.3 minutes per patient in infusion clinic chair time. Each successful rapid infusion of rituximab potentially opened additional time in clinic for ≥ 1 patients to receive an infusion therapy. The RLRVAMC usually operated at maximum capacity, so the ability to accommodate more patients helped decrease hospital admittances for time-sensitive infusions.

The initial criteria used to screen patients to determine whether a rapid infusion of rituximab would be appropriate was based on inclusion and exclusion criteria for past studies on the same subject.^3-5 The incidence of hypersensitivity reactions associated with study participants who received rapid rituximab infusions also resembles past research done on the subject, which is important to note due to prior misconceptions of staff at the institution of a higher risk of reaction in this specific veteran population. One patient with RA experienced a grade 3 IRR in this study. Although this patient met the original inclusion criteria, the patient had baseline dysphagia, and following the first infusion, reported to the emergency department (ED) with symptoms of delayed anaphylaxis. In this case, the order for rapid infusion was placed in advance and the prescriber was unaware of the ED visit. Based on this event, eligibility criteria for 90-minute rituximab infusions were updated to include additional information specifying that candidates for a rapid infusion also may have no baseline airway compromise. This hypersensitivity reaction also highlighted the need for decision support technology to assist HCPs in patient selection as well as empowering nursing and pharmacy staff to identify concerns once they place orders.

Over the course of the study, investigators assisted the HCPs with preparation of orders for the rapid infusion of rituximab for antineoplastic indications. Due to feasibility issues with this practice moving forward, order sets containing rituximab were updated to include a 90-minute option. This created a more standardized process that allowed HCPs to screen potential patients on their own. The expectation is that HCPs will be more likely to order 90-minute infusions for eligible patients in the future with this efficient and safer process.

Limitations

The small sample size in this study was a limitation. Retrospective data related to the management of infusion reactions and length of infusions were collected from nursing notes. The prospective use of a standardized evaluation tool for adverse drug reactions as well as bar code medication administration technology would improve the data available for this study. Additional studies also would be useful to validate the results.

Conclusions

The proactive measures that were used to implement the rapid infusion rituximab protocol improved HCP prescribing rates, nursing satisfaction, and the management of IRRs. Potential time savings with each infusion was significant. This study confirmed appropriateness of rapid administration of rituximab in this veteran population and has increased interest in implementing other rapid infusion protocols. Protocols, education, and order sets are being developed for daratumumab and infliximab.

Consolidated mail outpatient pharmacy (CMOP) is an automated prescription order processing and delivery system developed by the US Department of Veterans Affairs (VA) in 1994 to provide medications to VA patients.¹ In fiscal year (FY) 2016, CMOP filled about 80% of VA outpatient prescriptions.²

Formalized by the 2010 Memorandum of Understanding between Indian Health Service (IHS) and VA, CMOP is a partnership undertaken to improve the delivery of care to patients by both agencies.³ The number of prescriptions filled by CMOP for IHS patients increased from 1,972 in FY 2010 to 840,109 in FY 2018.⁴ In the fourth quarter of FY 2018, there were 94 CMOP-enrolled IHS federal and tribal sites.⁵ It is only appropriate that a growing number of IHS sites are adopting CMOP considering the evidence for mail-order pharmacy on better patient adherence, improved health outcomes, and potential cost savings.^6-9 Furthermore, using a centralized pharmacy operation, such as CMOP, can lead to better quality services.¹⁰

Crownpoint Health Care Facility (CHCF) serves > 30,000 American Indians and is in Crownpoint, New Mexico, a small community of about 3,000 people.¹¹ Most of the patients served by the facility live in distant places. Many of these underserved patients do not have a stable means of transportation.¹² Therefore, these patients may have difficulty traveling to the facility for their health care needs, including medication pickups. More than 2.5 million American Indians and Alaska Natives IHS beneficiaries face similar challenges due to the rurality of their communities.¹³ CMOP can be a method to increase access to care for this vulnerable population. However, the utilization of CMOP varies significantly among IHS facilities. While some IHS facilities process large numbers of prescriptions through CMOP, other facilities process few, if any. There also are IHS facilities, such as CHCF, which are at the initial stage of implementing CMOP or trying to increase the volume of prescriptions processed through CMOP. Although the utilization of CMOP has grown exponentially among IHS facilities, there is currently no available resource that summarizes the relative advantages and disadvantages, the challenges and opportunities, and the strengths and weaknesses of implementing CMOP for IHS facilities

Methods

A questionnaire encompassing various aspects of CMOP prescription processing was developed and distributed to the primary CMOP contacts for IHS facilities. The questionnaire was first distributed by e-mail on December 19, 2018. It was e-mailed for a second time on January 16, 2019, and the questionnaire was open for responses until the end of January 2019 (Table).

Results

Forty-four of 94 CMOP-enrolled IHS sites responded to the questionnaire. Most sites train the majority of their pharmacists in CMOP prescription processing. Overall, 310 of 347 pharmacists (89%) in these 44 IHS sites can process prescriptions through CMOP. Thirty-one sites have all their pharmacists trained in CMOP prescription processing. Only 1 facility had less than half (2 of 17 pharmacists) of its pharmacists trained in CMOP prescription processing. More than half the total number of pharmacists, 185 out of 347 (53%), check electronic messages via Resource and Patient Management System (RPMS) MailMan to get information about prescriptions rejected by CMOP. Twenty sites have all their pharmacists check messages about CMOP rejections. However, 2 facilities reported that they do not check the rejection messages at all. Twenty-six of the 44 responding sites (59%) transmit prescriptions to CMOP manually in the electronic system. The rest (18 of 44) rely on the auto-transmission (AT) setup to transmit the CMOP-suspended prescriptions at specified times of the day.

Half the sites (8 of 16) that rely on patients asking for prescriptions to be mailed at the time of refill request do not use any method to designate a CMOP patient. Twenty-four sites use the narrative field on the patient’s profile in RPMS, the health information system used by most IHS facilities, to designate CMOP patients. Eighteen sites use pop-up messages on ScriptPro, a pharmacy automation system, as a designation method. Most of the sites (12 of 15) that use both RPMS and ScriptPro designation methods do not require patients to ask for prescriptions to be mailed at the time of refill request; prescriptions for these patients are routed through CMOP unless patients request otherwise. Only 3 of 44 sites use both methods and rely on patients asking for prescriptions to be mailed at the time of refill request. Some other reported designation methods were using the electronic health record (EHR) posting box, keeping a manual list of CMOP patients, and solely utilizing the Prescription Mail Delivery field in RPMS. Three sites also noted that they keep manual lists to auto-refill prescriptions through CMOP.

Thirty sites (68%) reported that they process every prescription through CMOP even if the patient had prescriptions with specified CMOP quantities. Only 8 sites (18%) said that they used the local mail-out program to keep the same days’ supply for all medication orders. For patients with CMOP-ineligible prescriptions, 34 of the 44 sites (77%) process the eligible prescriptions through CMOP and refill the rest of the prescriptions locally. Six sites (14%) process all medication orders locally for patients with any CMOP-ineligible prescriptions.

Only 12 of 44 sites (27%) involve pharmacy technicians in CMOP prescription processing. Five sites have technicians process prescription refills through CMOP. Two of these sites mentioned the strategy of technicians suspending the prescriptions to be sent to CMOP on the refill due date. Other technician roles included tracking CMOP packages, checking electronic messages for CMOP rejections, and signing up patients for CMOP.

Only 3 of the 44 sites (7%) have measured patient satisfaction with the CMOP program. One of these 3 sites reported that the overall satisfaction was high with CMOP. This site administered the survey to patients who came to the clinic for appointments. The second facility called patients and asked for their feedback. The third site conducted the survey by using student pharmacists. Two sites reported that they use the survey results from the CMOP-conducted patient satisfaction surveys, although they have not measured patient satisfaction at their specific facilities.

Most sites have not assessed CMOP’s impact on their insurance (point of sale) collections. However, 13 sites (30%) reported that they believe they are losing on collections by utilizing CMOP. The use of repackaged products by CMOP, which are usually nonreimbursable, is an issue that was mentioned multiple times. In contrast, 2 sites mentioned that CMOP has led to increased insurance collections for their facilities.

Discussion

The utility of CMOP among the responding IHS sites varies quite significantly. Some sites appreciate the convenience of CMOP while acknowledging its limitations, such as the possible decrease in insurance collections, lengthy prescription processing time, or medication backorders. However, some sites have reserved CMOP for special circumstances (eg, mailing refrigerated items to the patient’s street address) due to various complexities that may come with CMOP. One site reported that it compares IHS contract drug prices with VA contract drug prices quarterly to determine which prescriptions should be sent through CMOP.

Most of the IHS pharmacists (89%) are trained in CMOP prescription processing. If an IHS site wants to increase its volume of CMOP prescriptions, it is sensible to train as many pharmacists as possible so that the responsibility does not fall on a few pharmacists. Newly hired pharmacists can receive guidance from trained pharmacists. Designation methods for CMOP patients can be beneficial for these pharmacists to identify CMOP-enrolled patients, especially if the site does not require patients to ask for prescriptions to be mailed at the time of refill request. Only 3 sites (7%) use multiple designation methods in addition to relying on patients to ask for prescriptions to be mailed. Proper implementation of designation methods can remove this extra burden on patients. Conversely, requiring patients to ask for prescriptions to be sent through CMOP can prevent spontaneous mail-outs if a CMOP-designated patient wants to pick up prescriptions locally. Overall, 16 sites (36%) rely on patients asking for prescriptions to be mailed.

One of the main benefits of CMOP is the ability to mail refrigerated items. Local pharmacy mail-out programs may not have this ability. Patients at rural locations often use post office (PO) boxes because they are unable to receive postal services at their physical addresses; however, they may receive packages through United Parcel Service (UPS) at their physical addresses. CMOP uses UPS to send refrigerated items, but UPS does not deliver to PO boxes. Therefore, remotely located sites like CHCF have difficulty in fully optimizing this benefit. One solution is documenting both the physical and mailing addresses on the patient’s EHR, which enables CMOP to send refrigerated items to the patient’s home address via UPS and mail the rest of the prescriptions to the patient’s PO box address with the US Postal Service. The physical address must be listed above the PO box address to ensure that refrigerated items are not rejected by CMOP. Furthermore, both the physical address and the PO box address must be in the same city for this method to work. Two sites noted mailing refrigerated items as one of the major challenges in CMOP prescription processing.

CMOP-enrolled patients must be educated about requesting medications 7 to 10 days before they run out. There is no standard time line for prescriptions filled by CMOP. However, 1 site reported that it may take up to “10 days from time requested to mailbox.” This delay leads to pharmacies facing a dilemma as processing prescriptions too early can lead to insurance rejections, but processing them too late can lead to the patient not receiving the medication by the time they run out of their current supply. However, CMOP provides the ability to track prescriptions sent through CMOP. Pharmacists and technicians need to have access to BestWay Parcel Services Client Portal (genco-mms.bestwayparcel.com) to track CMOP packages. Tracking CMOP prescriptions is a way pharmacy technicians can be involved in CMOP prescription processing. Technicians seem to be underutilized, as only 27% of the responding sites utilize them to some degree in the CMOP process. One site delegated the responsibility of checking CMOP rejection messages to pharmacy technicians. Since 2 of the responding sites do not check CMOP rejection messages at all, this is an excellent opportunity to get pharmacy technicians involved.

A CMOP auto-refill program can potentially be utilized to avoid missed or late medications. In an auto-refill program, a pharmacist can refill prescriptions through CMOP on the due date without a patient request. They may get rejected by insurance the first time they are processed through CMOP for refilling too early if the processing time is taken into account. However, the subsequent refills do not have to consider the CMOP processing time as they would already be synchronized based on the last refill date. Though, if CMOP is out of stock on a medication and it is expected to be available soon, CMOP may take a few extra days to either fill the prescription or reject it if the drug stays unavailable. One of the sites reported “the amount of time [CMOP] holds medications if they are out of stock” as “the hardest thing to work around.” A couple of sites also mentioned the longer than usual delay in processing prescriptions by CMOP during the holidays as one of the major challenges.

CMOP use of repackaged products also may lead insurance companies to deny reimbursement. Repackaged products are usually cheaper to buy.¹⁴ However, most insurances do not reimburse for prescriptions filled with these products.¹⁵ The local drug file on RPMS may have a national drug code (NDC) that is reimbursable by insurance, but CMOP will change it to the repackaged NDC if they are filling the prescription with a repackaged product. One potential solution to this problem would be filling these prescriptions locally. Furthermore, insurance claims are processed when the prescriptions are filled by CMOP. Sites cannot return/cancel the prescription anymore at that point. Therefore, the inability to see real-time rejections as the medication orders are processed on-site makes it challenging to prevent avoidable insurance rejections, such as a refill too soon. One site calculated that it lost $26,386.45 by utilizing CMOP from January 9, 2018 to December 12, 2018. However, it is unclear whether this loss was representative of other sites. It is also worth noting that IHS sites can save a substantial amount of money on certain products by utilizing CMOP because VA buys these products at a reduced price.¹⁶

CMOP-transmitted prescriptions can be rejected for various reasons, such as CMOP manufacturer’s backorder, a different quantity from CMOP stock size, etc. Information about these rejected prescriptions is accessed through electronic messages on RPMS. CMOP does not dispense less than a full, unopened package for most over-the-counter (OTC) medications. The quantity on these prescriptions must be equal to or multiples of the package size for them to be filled by CMOP. This can lead to a patient having prescriptions with different days’ supplies, which results in various refill due dates. If a site has a local mail-out program available, it can potentially keep the same days’ supply for all prescriptions by mailing these OTC medications locally rather than utilizing CMOP. However, this can partially negate CMOP’s benefit of reduced workload.

CMOP also has specified quantities on some prescription medications. One survey respondent viewed “the quantity and day supply required by CMOP” as a negative influence on the site’s insurance collection. It is possible that CMOP does not carry all the medications that a CMOP-enrolled patient is prescribed. Most sites (77%) still send eligible prescriptions through CMOP for the patients who also have CMOP-ineligible prescriptions. There are a small number of sites (14%) that utilize local mail-out program for the patients with any CMOP-ineligible prescriptions, possibly to simplify the process. Schedule II controlled substances cannot be processed through CMOP either; however, facilities may have local policies that prohibit mailing any controlled substances.

Prescriptions can be manually transmitted to CMOP, or they can be automatically transmitted based on the run time and frequency of the auto-transmission setup. The prescriptions that are waiting to be transmitted to CMOP must be in the “suspended” status. The apparent advantage of relying on auto-transmission is that you do not have to complete the steps manually to transmit suspended CMOP prescriptions, thereby making the process more convenient. However, the manual transmission can be utilized as a checkpoint to verify that prescriptions were properly suspended for CMOP, as the prescription status changes from “S” (suspended) to “AT” once the transmission is completed. If a prescription is not properly suspended for CMOP, the status will remain as S even after manual transmission. More than half (59%) of the responding sites must find the manual transmission feature useful as they use it either over or in addition to the auto-transmission setup.

Despite the challenges, many IHS sites process thousands of monthly prescriptions through CMOP. Of the 94 CMOP-enrolled IHS sites, 17 processed > 1,000 prescriptions from March 27, 2019 to April 25, 2019.¹⁷ Five sites processed > 5,000 prescriptions.¹⁷ At the rate of > 5,000 prescriptions per month, the yearly CMOP prescription count will be > 60,000. That is more than one-third of the prescriptions processed by CHCF in 2018. By handling these prescriptions through CMOP, it can decrease pharmacy filling and dispensing workload, thereby freeing pharmacists to participate in other services.¹⁸ Furthermore, implementing CMOP does not incur any cost for the IHS site. There is a nondrug cost for each prescription that is filled through CMOP. This cost was $2.67 during FY 2016.¹⁹ The fee covers prescription vial, label, packaging for mail, postage, personnel, building overhead, and equipment capitalization.¹⁹ The nondrug cost of filling a prescription locally at the site can potentially exceed the cost charged by CMOP.¹⁹

A lack of objective data exists to assess the net impact of CMOP on patients. Different theoretical assumptions can be made, such as CMOP resulting in better patient adherence. However, there is no objective information about how much CMOP improves patient adherence if it does at all. Though J.D. Power US Pharmacy Study ranks CMOP as “among the best” mail-order pharmacies in customer satisfaction, only 3 of the 44 responding sites have measured patient satisfaction locally.²⁰ Only 1 site had objective data about CMOP’s impact on the point of sale. Therefore, it is currently difficult to perform a cost-benefit analysis of the CMOP program. There are opportunities for further studies on these topics.

Limitations

One limitation of this study is that < 50% of the CMOP-enrolled sites (44 of 94) responded to the questionnaire. It is possible that the facilities that had a significantly positive or negative experience with CMOP were more inclined to share their views. Therefore, it is difficult to conclude whether the responding sites are an accurate representative sample. Another limitation of the study was the questionnaire design and the reliance on free-text responses as opposed to structured data. The free-text responses had to be analyzed manually to determine whether they fall in the same category, thereby increasing the risk of interpretation error.

Conclusion

CMOP has its unique challenges but provides many benefits that local pharmacy mail-out programs may not possess, such as the abilities to mail refrigerated items and track packages. One must be familiar with CMOP’s various idiosyncrasies to make the best use of the program. Extensive staff education and orientation for new staff members must be done to familiarize them with the program. Nevertheless, the successful implementation of CMOP can lead to reduced pharmacy workload while increasing access to care for patients with transportation issues.

Acknowledgments
The authors thank LCDR Karsten Smith, PharmD, BCGP, the IHS CMOP Coordinator for providing the list of primary CMOP contacts and CDR Kendall Van Tyle, PharmD, BCPS, for proofreading the article.

Consolidated mail outpatient pharmacy (CMOP) is an automated prescription order processing and delivery system developed by the US Department of Veterans Affairs (VA) in 1994 to provide medications to VA patients.¹ In fiscal year (FY) 2016, CMOP filled about 80% of VA outpatient prescriptions.²

Formalized by the 2010 Memorandum of Understanding between Indian Health Service (IHS) and VA, CMOP is a partnership undertaken to improve the delivery of care to patients by both agencies.³ The number of prescriptions filled by CMOP for IHS patients increased from 1,972 in FY 2010 to 840,109 in FY 2018.⁴ In the fourth quarter of FY 2018, there were 94 CMOP-enrolled IHS federal and tribal sites.⁵ It is only appropriate that a growing number of IHS sites are adopting CMOP considering the evidence for mail-order pharmacy on better patient adherence, improved health outcomes, and potential cost savings.^6-9 Furthermore, using a centralized pharmacy operation, such as CMOP, can lead to better quality services.¹⁰

Crownpoint Health Care Facility (CHCF) serves > 30,000 American Indians and is in Crownpoint, New Mexico, a small community of about 3,000 people.¹¹ Most of the patients served by the facility live in distant places. Many of these underserved patients do not have a stable means of transportation.¹² Therefore, these patients may have difficulty traveling to the facility for their health care needs, including medication pickups. More than 2.5 million American Indians and Alaska Natives IHS beneficiaries face similar challenges due to the rurality of their communities.¹³ CMOP can be a method to increase access to care for this vulnerable population. However, the utilization of CMOP varies significantly among IHS facilities. While some IHS facilities process large numbers of prescriptions through CMOP, other facilities process few, if any. There also are IHS facilities, such as CHCF, which are at the initial stage of implementing CMOP or trying to increase the volume of prescriptions processed through CMOP. Although the utilization of CMOP has grown exponentially among IHS facilities, there is currently no available resource that summarizes the relative advantages and disadvantages, the challenges and opportunities, and the strengths and weaknesses of implementing CMOP for IHS facilities

Methods

A questionnaire encompassing various aspects of CMOP prescription processing was developed and distributed to the primary CMOP contacts for IHS facilities. The questionnaire was first distributed by e-mail on December 19, 2018. It was e-mailed for a second time on January 16, 2019, and the questionnaire was open for responses until the end of January 2019 (Table).

Results

Forty-four of 94 CMOP-enrolled IHS sites responded to the questionnaire. Most sites train the majority of their pharmacists in CMOP prescription processing. Overall, 310 of 347 pharmacists (89%) in these 44 IHS sites can process prescriptions through CMOP. Thirty-one sites have all their pharmacists trained in CMOP prescription processing. Only 1 facility had less than half (2 of 17 pharmacists) of its pharmacists trained in CMOP prescription processing. More than half the total number of pharmacists, 185 out of 347 (53%), check electronic messages via Resource and Patient Management System (RPMS) MailMan to get information about prescriptions rejected by CMOP. Twenty sites have all their pharmacists check messages about CMOP rejections. However, 2 facilities reported that they do not check the rejection messages at all. Twenty-six of the 44 responding sites (59%) transmit prescriptions to CMOP manually in the electronic system. The rest (18 of 44) rely on the auto-transmission (AT) setup to transmit the CMOP-suspended prescriptions at specified times of the day.

Half the sites (8 of 16) that rely on patients asking for prescriptions to be mailed at the time of refill request do not use any method to designate a CMOP patient. Twenty-four sites use the narrative field on the patient’s profile in RPMS, the health information system used by most IHS facilities, to designate CMOP patients. Eighteen sites use pop-up messages on ScriptPro, a pharmacy automation system, as a designation method. Most of the sites (12 of 15) that use both RPMS and ScriptPro designation methods do not require patients to ask for prescriptions to be mailed at the time of refill request; prescriptions for these patients are routed through CMOP unless patients request otherwise. Only 3 of 44 sites use both methods and rely on patients asking for prescriptions to be mailed at the time of refill request. Some other reported designation methods were using the electronic health record (EHR) posting box, keeping a manual list of CMOP patients, and solely utilizing the Prescription Mail Delivery field in RPMS. Three sites also noted that they keep manual lists to auto-refill prescriptions through CMOP.

Thirty sites (68%) reported that they process every prescription through CMOP even if the patient had prescriptions with specified CMOP quantities. Only 8 sites (18%) said that they used the local mail-out program to keep the same days’ supply for all medication orders. For patients with CMOP-ineligible prescriptions, 34 of the 44 sites (77%) process the eligible prescriptions through CMOP and refill the rest of the prescriptions locally. Six sites (14%) process all medication orders locally for patients with any CMOP-ineligible prescriptions.

Only 12 of 44 sites (27%) involve pharmacy technicians in CMOP prescription processing. Five sites have technicians process prescription refills through CMOP. Two of these sites mentioned the strategy of technicians suspending the prescriptions to be sent to CMOP on the refill due date. Other technician roles included tracking CMOP packages, checking electronic messages for CMOP rejections, and signing up patients for CMOP.

Only 3 of the 44 sites (7%) have measured patient satisfaction with the CMOP program. One of these 3 sites reported that the overall satisfaction was high with CMOP. This site administered the survey to patients who came to the clinic for appointments. The second facility called patients and asked for their feedback. The third site conducted the survey by using student pharmacists. Two sites reported that they use the survey results from the CMOP-conducted patient satisfaction surveys, although they have not measured patient satisfaction at their specific facilities.

Most sites have not assessed CMOP’s impact on their insurance (point of sale) collections. However, 13 sites (30%) reported that they believe they are losing on collections by utilizing CMOP. The use of repackaged products by CMOP, which are usually nonreimbursable, is an issue that was mentioned multiple times. In contrast, 2 sites mentioned that CMOP has led to increased insurance collections for their facilities.

Discussion

The utility of CMOP among the responding IHS sites varies quite significantly. Some sites appreciate the convenience of CMOP while acknowledging its limitations, such as the possible decrease in insurance collections, lengthy prescription processing time, or medication backorders. However, some sites have reserved CMOP for special circumstances (eg, mailing refrigerated items to the patient’s street address) due to various complexities that may come with CMOP. One site reported that it compares IHS contract drug prices with VA contract drug prices quarterly to determine which prescriptions should be sent through CMOP.

Most of the IHS pharmacists (89%) are trained in CMOP prescription processing. If an IHS site wants to increase its volume of CMOP prescriptions, it is sensible to train as many pharmacists as possible so that the responsibility does not fall on a few pharmacists. Newly hired pharmacists can receive guidance from trained pharmacists. Designation methods for CMOP patients can be beneficial for these pharmacists to identify CMOP-enrolled patients, especially if the site does not require patients to ask for prescriptions to be mailed at the time of refill request. Only 3 sites (7%) use multiple designation methods in addition to relying on patients to ask for prescriptions to be mailed. Proper implementation of designation methods can remove this extra burden on patients. Conversely, requiring patients to ask for prescriptions to be sent through CMOP can prevent spontaneous mail-outs if a CMOP-designated patient wants to pick up prescriptions locally. Overall, 16 sites (36%) rely on patients asking for prescriptions to be mailed.

One of the main benefits of CMOP is the ability to mail refrigerated items. Local pharmacy mail-out programs may not have this ability. Patients at rural locations often use post office (PO) boxes because they are unable to receive postal services at their physical addresses; however, they may receive packages through United Parcel Service (UPS) at their physical addresses. CMOP uses UPS to send refrigerated items, but UPS does not deliver to PO boxes. Therefore, remotely located sites like CHCF have difficulty in fully optimizing this benefit. One solution is documenting both the physical and mailing addresses on the patient’s EHR, which enables CMOP to send refrigerated items to the patient’s home address via UPS and mail the rest of the prescriptions to the patient’s PO box address with the US Postal Service. The physical address must be listed above the PO box address to ensure that refrigerated items are not rejected by CMOP. Furthermore, both the physical address and the PO box address must be in the same city for this method to work. Two sites noted mailing refrigerated items as one of the major challenges in CMOP prescription processing.

CMOP-enrolled patients must be educated about requesting medications 7 to 10 days before they run out. There is no standard time line for prescriptions filled by CMOP. However, 1 site reported that it may take up to “10 days from time requested to mailbox.” This delay leads to pharmacies facing a dilemma as processing prescriptions too early can lead to insurance rejections, but processing them too late can lead to the patient not receiving the medication by the time they run out of their current supply. However, CMOP provides the ability to track prescriptions sent through CMOP. Pharmacists and technicians need to have access to BestWay Parcel Services Client Portal (genco-mms.bestwayparcel.com) to track CMOP packages. Tracking CMOP prescriptions is a way pharmacy technicians can be involved in CMOP prescription processing. Technicians seem to be underutilized, as only 27% of the responding sites utilize them to some degree in the CMOP process. One site delegated the responsibility of checking CMOP rejection messages to pharmacy technicians. Since 2 of the responding sites do not check CMOP rejection messages at all, this is an excellent opportunity to get pharmacy technicians involved.

A CMOP auto-refill program can potentially be utilized to avoid missed or late medications. In an auto-refill program, a pharmacist can refill prescriptions through CMOP on the due date without a patient request. They may get rejected by insurance the first time they are processed through CMOP for refilling too early if the processing time is taken into account. However, the subsequent refills do not have to consider the CMOP processing time as they would already be synchronized based on the last refill date. Though, if CMOP is out of stock on a medication and it is expected to be available soon, CMOP may take a few extra days to either fill the prescription or reject it if the drug stays unavailable. One of the sites reported “the amount of time [CMOP] holds medications if they are out of stock” as “the hardest thing to work around.” A couple of sites also mentioned the longer than usual delay in processing prescriptions by CMOP during the holidays as one of the major challenges.

CMOP use of repackaged products also may lead insurance companies to deny reimbursement. Repackaged products are usually cheaper to buy.¹⁴ However, most insurances do not reimburse for prescriptions filled with these products.¹⁵ The local drug file on RPMS may have a national drug code (NDC) that is reimbursable by insurance, but CMOP will change it to the repackaged NDC if they are filling the prescription with a repackaged product. One potential solution to this problem would be filling these prescriptions locally. Furthermore, insurance claims are processed when the prescriptions are filled by CMOP. Sites cannot return/cancel the prescription anymore at that point. Therefore, the inability to see real-time rejections as the medication orders are processed on-site makes it challenging to prevent avoidable insurance rejections, such as a refill too soon. One site calculated that it lost $26,386.45 by utilizing CMOP from January 9, 2018 to December 12, 2018. However, it is unclear whether this loss was representative of other sites. It is also worth noting that IHS sites can save a substantial amount of money on certain products by utilizing CMOP because VA buys these products at a reduced price.¹⁶

CMOP-transmitted prescriptions can be rejected for various reasons, such as CMOP manufacturer’s backorder, a different quantity from CMOP stock size, etc. Information about these rejected prescriptions is accessed through electronic messages on RPMS. CMOP does not dispense less than a full, unopened package for most over-the-counter (OTC) medications. The quantity on these prescriptions must be equal to or multiples of the package size for them to be filled by CMOP. This can lead to a patient having prescriptions with different days’ supplies, which results in various refill due dates. If a site has a local mail-out program available, it can potentially keep the same days’ supply for all prescriptions by mailing these OTC medications locally rather than utilizing CMOP. However, this can partially negate CMOP’s benefit of reduced workload.

CMOP also has specified quantities on some prescription medications. One survey respondent viewed “the quantity and day supply required by CMOP” as a negative influence on the site’s insurance collection. It is possible that CMOP does not carry all the medications that a CMOP-enrolled patient is prescribed. Most sites (77%) still send eligible prescriptions through CMOP for the patients who also have CMOP-ineligible prescriptions. There are a small number of sites (14%) that utilize local mail-out program for the patients with any CMOP-ineligible prescriptions, possibly to simplify the process. Schedule II controlled substances cannot be processed through CMOP either; however, facilities may have local policies that prohibit mailing any controlled substances.

Prescriptions can be manually transmitted to CMOP, or they can be automatically transmitted based on the run time and frequency of the auto-transmission setup. The prescriptions that are waiting to be transmitted to CMOP must be in the “suspended” status. The apparent advantage of relying on auto-transmission is that you do not have to complete the steps manually to transmit suspended CMOP prescriptions, thereby making the process more convenient. However, the manual transmission can be utilized as a checkpoint to verify that prescriptions were properly suspended for CMOP, as the prescription status changes from “S” (suspended) to “AT” once the transmission is completed. If a prescription is not properly suspended for CMOP, the status will remain as S even after manual transmission. More than half (59%) of the responding sites must find the manual transmission feature useful as they use it either over or in addition to the auto-transmission setup.

Despite the challenges, many IHS sites process thousands of monthly prescriptions through CMOP. Of the 94 CMOP-enrolled IHS sites, 17 processed > 1,000 prescriptions from March 27, 2019 to April 25, 2019.¹⁷ Five sites processed > 5,000 prescriptions.¹⁷ At the rate of > 5,000 prescriptions per month, the yearly CMOP prescription count will be > 60,000. That is more than one-third of the prescriptions processed by CHCF in 2018. By handling these prescriptions through CMOP, it can decrease pharmacy filling and dispensing workload, thereby freeing pharmacists to participate in other services.¹⁸ Furthermore, implementing CMOP does not incur any cost for the IHS site. There is a nondrug cost for each prescription that is filled through CMOP. This cost was $2.67 during FY 2016.¹⁹ The fee covers prescription vial, label, packaging for mail, postage, personnel, building overhead, and equipment capitalization.¹⁹ The nondrug cost of filling a prescription locally at the site can potentially exceed the cost charged by CMOP.¹⁹

A lack of objective data exists to assess the net impact of CMOP on patients. Different theoretical assumptions can be made, such as CMOP resulting in better patient adherence. However, there is no objective information about how much CMOP improves patient adherence if it does at all. Though J.D. Power US Pharmacy Study ranks CMOP as “among the best” mail-order pharmacies in customer satisfaction, only 3 of the 44 responding sites have measured patient satisfaction locally.²⁰ Only 1 site had objective data about CMOP’s impact on the point of sale. Therefore, it is currently difficult to perform a cost-benefit analysis of the CMOP program. There are opportunities for further studies on these topics.

Limitations

One limitation of this study is that < 50% of the CMOP-enrolled sites (44 of 94) responded to the questionnaire. It is possible that the facilities that had a significantly positive or negative experience with CMOP were more inclined to share their views. Therefore, it is difficult to conclude whether the responding sites are an accurate representative sample. Another limitation of the study was the questionnaire design and the reliance on free-text responses as opposed to structured data. The free-text responses had to be analyzed manually to determine whether they fall in the same category, thereby increasing the risk of interpretation error.

Conclusion

CMOP has its unique challenges but provides many benefits that local pharmacy mail-out programs may not possess, such as the abilities to mail refrigerated items and track packages. One must be familiar with CMOP’s various idiosyncrasies to make the best use of the program. Extensive staff education and orientation for new staff members must be done to familiarize them with the program. Nevertheless, the successful implementation of CMOP can lead to reduced pharmacy workload while increasing access to care for patients with transportation issues.

Acknowledgments
The authors thank LCDR Karsten Smith, PharmD, BCGP, the IHS CMOP Coordinator for providing the list of primary CMOP contacts and CDR Kendall Van Tyle, PharmD, BCPS, for proofreading the article.

Consolidated mail outpatient pharmacy (CMOP) is an automated prescription order processing and delivery system developed by the US Department of Veterans Affairs (VA) in 1994 to provide medications to VA patients.¹ In fiscal year (FY) 2016, CMOP filled about 80% of VA outpatient prescriptions.²

Formalized by the 2010 Memorandum of Understanding between Indian Health Service (IHS) and VA, CMOP is a partnership undertaken to improve the delivery of care to patients by both agencies.³ The number of prescriptions filled by CMOP for IHS patients increased from 1,972 in FY 2010 to 840,109 in FY 2018.⁴ In the fourth quarter of FY 2018, there were 94 CMOP-enrolled IHS federal and tribal sites.⁵ It is only appropriate that a growing number of IHS sites are adopting CMOP considering the evidence for mail-order pharmacy on better patient adherence, improved health outcomes, and potential cost savings.^6-9 Furthermore, using a centralized pharmacy operation, such as CMOP, can lead to better quality services.¹⁰

Crownpoint Health Care Facility (CHCF) serves > 30,000 American Indians and is in Crownpoint, New Mexico, a small community of about 3,000 people.¹¹ Most of the patients served by the facility live in distant places. Many of these underserved patients do not have a stable means of transportation.¹² Therefore, these patients may have difficulty traveling to the facility for their health care needs, including medication pickups. More than 2.5 million American Indians and Alaska Natives IHS beneficiaries face similar challenges due to the rurality of their communities.¹³ CMOP can be a method to increase access to care for this vulnerable population. However, the utilization of CMOP varies significantly among IHS facilities. While some IHS facilities process large numbers of prescriptions through CMOP, other facilities process few, if any. There also are IHS facilities, such as CHCF, which are at the initial stage of implementing CMOP or trying to increase the volume of prescriptions processed through CMOP. Although the utilization of CMOP has grown exponentially among IHS facilities, there is currently no available resource that summarizes the relative advantages and disadvantages, the challenges and opportunities, and the strengths and weaknesses of implementing CMOP for IHS facilities

Methods

A questionnaire encompassing various aspects of CMOP prescription processing was developed and distributed to the primary CMOP contacts for IHS facilities. The questionnaire was first distributed by e-mail on December 19, 2018. It was e-mailed for a second time on January 16, 2019, and the questionnaire was open for responses until the end of January 2019 (Table).

Results

Forty-four of 94 CMOP-enrolled IHS sites responded to the questionnaire. Most sites train the majority of their pharmacists in CMOP prescription processing. Overall, 310 of 347 pharmacists (89%) in these 44 IHS sites can process prescriptions through CMOP. Thirty-one sites have all their pharmacists trained in CMOP prescription processing. Only 1 facility had less than half (2 of 17 pharmacists) of its pharmacists trained in CMOP prescription processing. More than half the total number of pharmacists, 185 out of 347 (53%), check electronic messages via Resource and Patient Management System (RPMS) MailMan to get information about prescriptions rejected by CMOP. Twenty sites have all their pharmacists check messages about CMOP rejections. However, 2 facilities reported that they do not check the rejection messages at all. Twenty-six of the 44 responding sites (59%) transmit prescriptions to CMOP manually in the electronic system. The rest (18 of 44) rely on the auto-transmission (AT) setup to transmit the CMOP-suspended prescriptions at specified times of the day.

Half the sites (8 of 16) that rely on patients asking for prescriptions to be mailed at the time of refill request do not use any method to designate a CMOP patient. Twenty-four sites use the narrative field on the patient’s profile in RPMS, the health information system used by most IHS facilities, to designate CMOP patients. Eighteen sites use pop-up messages on ScriptPro, a pharmacy automation system, as a designation method. Most of the sites (12 of 15) that use both RPMS and ScriptPro designation methods do not require patients to ask for prescriptions to be mailed at the time of refill request; prescriptions for these patients are routed through CMOP unless patients request otherwise. Only 3 of 44 sites use both methods and rely on patients asking for prescriptions to be mailed at the time of refill request. Some other reported designation methods were using the electronic health record (EHR) posting box, keeping a manual list of CMOP patients, and solely utilizing the Prescription Mail Delivery field in RPMS. Three sites also noted that they keep manual lists to auto-refill prescriptions through CMOP.

Thirty sites (68%) reported that they process every prescription through CMOP even if the patient had prescriptions with specified CMOP quantities. Only 8 sites (18%) said that they used the local mail-out program to keep the same days’ supply for all medication orders. For patients with CMOP-ineligible prescriptions, 34 of the 44 sites (77%) process the eligible prescriptions through CMOP and refill the rest of the prescriptions locally. Six sites (14%) process all medication orders locally for patients with any CMOP-ineligible prescriptions.

Only 12 of 44 sites (27%) involve pharmacy technicians in CMOP prescription processing. Five sites have technicians process prescription refills through CMOP. Two of these sites mentioned the strategy of technicians suspending the prescriptions to be sent to CMOP on the refill due date. Other technician roles included tracking CMOP packages, checking electronic messages for CMOP rejections, and signing up patients for CMOP.

Only 3 of the 44 sites (7%) have measured patient satisfaction with the CMOP program. One of these 3 sites reported that the overall satisfaction was high with CMOP. This site administered the survey to patients who came to the clinic for appointments. The second facility called patients and asked for their feedback. The third site conducted the survey by using student pharmacists. Two sites reported that they use the survey results from the CMOP-conducted patient satisfaction surveys, although they have not measured patient satisfaction at their specific facilities.

Most sites have not assessed CMOP’s impact on their insurance (point of sale) collections. However, 13 sites (30%) reported that they believe they are losing on collections by utilizing CMOP. The use of repackaged products by CMOP, which are usually nonreimbursable, is an issue that was mentioned multiple times. In contrast, 2 sites mentioned that CMOP has led to increased insurance collections for their facilities.

Discussion

The utility of CMOP among the responding IHS sites varies quite significantly. Some sites appreciate the convenience of CMOP while acknowledging its limitations, such as the possible decrease in insurance collections, lengthy prescription processing time, or medication backorders. However, some sites have reserved CMOP for special circumstances (eg, mailing refrigerated items to the patient’s street address) due to various complexities that may come with CMOP. One site reported that it compares IHS contract drug prices with VA contract drug prices quarterly to determine which prescriptions should be sent through CMOP.

Most of the IHS pharmacists (89%) are trained in CMOP prescription processing. If an IHS site wants to increase its volume of CMOP prescriptions, it is sensible to train as many pharmacists as possible so that the responsibility does not fall on a few pharmacists. Newly hired pharmacists can receive guidance from trained pharmacists. Designation methods for CMOP patients can be beneficial for these pharmacists to identify CMOP-enrolled patients, especially if the site does not require patients to ask for prescriptions to be mailed at the time of refill request. Only 3 sites (7%) use multiple designation methods in addition to relying on patients to ask for prescriptions to be mailed. Proper implementation of designation methods can remove this extra burden on patients. Conversely, requiring patients to ask for prescriptions to be sent through CMOP can prevent spontaneous mail-outs if a CMOP-designated patient wants to pick up prescriptions locally. Overall, 16 sites (36%) rely on patients asking for prescriptions to be mailed.

One of the main benefits of CMOP is the ability to mail refrigerated items. Local pharmacy mail-out programs may not have this ability. Patients at rural locations often use post office (PO) boxes because they are unable to receive postal services at their physical addresses; however, they may receive packages through United Parcel Service (UPS) at their physical addresses. CMOP uses UPS to send refrigerated items, but UPS does not deliver to PO boxes. Therefore, remotely located sites like CHCF have difficulty in fully optimizing this benefit. One solution is documenting both the physical and mailing addresses on the patient’s EHR, which enables CMOP to send refrigerated items to the patient’s home address via UPS and mail the rest of the prescriptions to the patient’s PO box address with the US Postal Service. The physical address must be listed above the PO box address to ensure that refrigerated items are not rejected by CMOP. Furthermore, both the physical address and the PO box address must be in the same city for this method to work. Two sites noted mailing refrigerated items as one of the major challenges in CMOP prescription processing.

CMOP-enrolled patients must be educated about requesting medications 7 to 10 days before they run out. There is no standard time line for prescriptions filled by CMOP. However, 1 site reported that it may take up to “10 days from time requested to mailbox.” This delay leads to pharmacies facing a dilemma as processing prescriptions too early can lead to insurance rejections, but processing them too late can lead to the patient not receiving the medication by the time they run out of their current supply. However, CMOP provides the ability to track prescriptions sent through CMOP. Pharmacists and technicians need to have access to BestWay Parcel Services Client Portal (genco-mms.bestwayparcel.com) to track CMOP packages. Tracking CMOP prescriptions is a way pharmacy technicians can be involved in CMOP prescription processing. Technicians seem to be underutilized, as only 27% of the responding sites utilize them to some degree in the CMOP process. One site delegated the responsibility of checking CMOP rejection messages to pharmacy technicians. Since 2 of the responding sites do not check CMOP rejection messages at all, this is an excellent opportunity to get pharmacy technicians involved.

A CMOP auto-refill program can potentially be utilized to avoid missed or late medications. In an auto-refill program, a pharmacist can refill prescriptions through CMOP on the due date without a patient request. They may get rejected by insurance the first time they are processed through CMOP for refilling too early if the processing time is taken into account. However, the subsequent refills do not have to consider the CMOP processing time as they would already be synchronized based on the last refill date. Though, if CMOP is out of stock on a medication and it is expected to be available soon, CMOP may take a few extra days to either fill the prescription or reject it if the drug stays unavailable. One of the sites reported “the amount of time [CMOP] holds medications if they are out of stock” as “the hardest thing to work around.” A couple of sites also mentioned the longer than usual delay in processing prescriptions by CMOP during the holidays as one of the major challenges.

CMOP use of repackaged products also may lead insurance companies to deny reimbursement. Repackaged products are usually cheaper to buy.¹⁴ However, most insurances do not reimburse for prescriptions filled with these products.¹⁵ The local drug file on RPMS may have a national drug code (NDC) that is reimbursable by insurance, but CMOP will change it to the repackaged NDC if they are filling the prescription with a repackaged product. One potential solution to this problem would be filling these prescriptions locally. Furthermore, insurance claims are processed when the prescriptions are filled by CMOP. Sites cannot return/cancel the prescription anymore at that point. Therefore, the inability to see real-time rejections as the medication orders are processed on-site makes it challenging to prevent avoidable insurance rejections, such as a refill too soon. One site calculated that it lost $26,386.45 by utilizing CMOP from January 9, 2018 to December 12, 2018. However, it is unclear whether this loss was representative of other sites. It is also worth noting that IHS sites can save a substantial amount of money on certain products by utilizing CMOP because VA buys these products at a reduced price.¹⁶

CMOP-transmitted prescriptions can be rejected for various reasons, such as CMOP manufacturer’s backorder, a different quantity from CMOP stock size, etc. Information about these rejected prescriptions is accessed through electronic messages on RPMS. CMOP does not dispense less than a full, unopened package for most over-the-counter (OTC) medications. The quantity on these prescriptions must be equal to or multiples of the package size for them to be filled by CMOP. This can lead to a patient having prescriptions with different days’ supplies, which results in various refill due dates. If a site has a local mail-out program available, it can potentially keep the same days’ supply for all prescriptions by mailing these OTC medications locally rather than utilizing CMOP. However, this can partially negate CMOP’s benefit of reduced workload.

CMOP also has specified quantities on some prescription medications. One survey respondent viewed “the quantity and day supply required by CMOP” as a negative influence on the site’s insurance collection. It is possible that CMOP does not carry all the medications that a CMOP-enrolled patient is prescribed. Most sites (77%) still send eligible prescriptions through CMOP for the patients who also have CMOP-ineligible prescriptions. There are a small number of sites (14%) that utilize local mail-out program for the patients with any CMOP-ineligible prescriptions, possibly to simplify the process. Schedule II controlled substances cannot be processed through CMOP either; however, facilities may have local policies that prohibit mailing any controlled substances.

Prescriptions can be manually transmitted to CMOP, or they can be automatically transmitted based on the run time and frequency of the auto-transmission setup. The prescriptions that are waiting to be transmitted to CMOP must be in the “suspended” status. The apparent advantage of relying on auto-transmission is that you do not have to complete the steps manually to transmit suspended CMOP prescriptions, thereby making the process more convenient. However, the manual transmission can be utilized as a checkpoint to verify that prescriptions were properly suspended for CMOP, as the prescription status changes from “S” (suspended) to “AT” once the transmission is completed. If a prescription is not properly suspended for CMOP, the status will remain as S even after manual transmission. More than half (59%) of the responding sites must find the manual transmission feature useful as they use it either over or in addition to the auto-transmission setup.

Despite the challenges, many IHS sites process thousands of monthly prescriptions through CMOP. Of the 94 CMOP-enrolled IHS sites, 17 processed > 1,000 prescriptions from March 27, 2019 to April 25, 2019.¹⁷ Five sites processed > 5,000 prescriptions.¹⁷ At the rate of > 5,000 prescriptions per month, the yearly CMOP prescription count will be > 60,000. That is more than one-third of the prescriptions processed by CHCF in 2018. By handling these prescriptions through CMOP, it can decrease pharmacy filling and dispensing workload, thereby freeing pharmacists to participate in other services.¹⁸ Furthermore, implementing CMOP does not incur any cost for the IHS site. There is a nondrug cost for each prescription that is filled through CMOP. This cost was $2.67 during FY 2016.¹⁹ The fee covers prescription vial, label, packaging for mail, postage, personnel, building overhead, and equipment capitalization.¹⁹ The nondrug cost of filling a prescription locally at the site can potentially exceed the cost charged by CMOP.¹⁹

A lack of objective data exists to assess the net impact of CMOP on patients. Different theoretical assumptions can be made, such as CMOP resulting in better patient adherence. However, there is no objective information about how much CMOP improves patient adherence if it does at all. Though J.D. Power US Pharmacy Study ranks CMOP as “among the best” mail-order pharmacies in customer satisfaction, only 3 of the 44 responding sites have measured patient satisfaction locally.²⁰ Only 1 site had objective data about CMOP’s impact on the point of sale. Therefore, it is currently difficult to perform a cost-benefit analysis of the CMOP program. There are opportunities for further studies on these topics.

Limitations

One limitation of this study is that < 50% of the CMOP-enrolled sites (44 of 94) responded to the questionnaire. It is possible that the facilities that had a significantly positive or negative experience with CMOP were more inclined to share their views. Therefore, it is difficult to conclude whether the responding sites are an accurate representative sample. Another limitation of the study was the questionnaire design and the reliance on free-text responses as opposed to structured data. The free-text responses had to be analyzed manually to determine whether they fall in the same category, thereby increasing the risk of interpretation error.

Conclusion

CMOP has its unique challenges but provides many benefits that local pharmacy mail-out programs may not possess, such as the abilities to mail refrigerated items and track packages. One must be familiar with CMOP’s various idiosyncrasies to make the best use of the program. Extensive staff education and orientation for new staff members must be done to familiarize them with the program. Nevertheless, the successful implementation of CMOP can lead to reduced pharmacy workload while increasing access to care for patients with transportation issues.

Acknowledgments
The authors thank LCDR Karsten Smith, PharmD, BCGP, the IHS CMOP Coordinator for providing the list of primary CMOP contacts and CDR Kendall Van Tyle, PharmD, BCPS, for proofreading the article.