Christine Soong, MD, MSc

From the University of Toronto (Dr. Basuita, Corey L. Kamen, and Dr. Soong) and Sinai Health System (Corey L. Kamen, Cheryl Ethier, and Dr. Soong), Toronto, Ontario, Canada. Co-first authors are Manpreet Basuita, MD, and Corey L. Kamen, BSc.

Abstract

• Objective: Routine laboratory testing is common among medical inpatients; however, when ordered inappropriately testing can represent low-value care. We examined the impact of an evidence-based intervention bundle on utilization.
• Participants/setting: This prospective cohort study took place at a tertiary academic medical center and included 6424 patients admitted to the general internal medicine service between April 2016 and March 2018.
• Intervention: An intervention bundle, whose first components were implemented in July 2016, included computer order entry restrictions on repetitive laboratory testing, education, and audit-feedback.
• Measures: Data were extracted from the hospital electronic health record. The primary outcome was the number of routine blood tests (complete blood count, creatinine, and electrolytes) ordered per inpatient day.
• Analysis: Descriptive statistics were calculated for demographic variables. We used statistical process control charts to compare the baseline period (April 2016-June 2017) and the intervention period (July 2017-March 2018) for the primary outcome.
• Results: The mean number of combined routine laboratory tests ordered per inpatient day decreased from 1.19 (SD, 0.21) tests to 1.11 (SD, 0.05), a relative reduction of 6.7% (P < 0.0001). Mean cost per case related to laboratory tests decreased from $17.24 in the pre-intervention period to $16.17 in the post-intervention period (relative reduction of 6.2%). This resulted in savings of $26,851 in the intervention year.
• Conclusion: A laboratory intervention bundle was associated with small reductions in testing and costs. A routine test performed less than once per inpatient day may not be clinically appropriate or possible.

Keywords: utilization; clinical costs; quality improvement; QI intervention; internal medicine; inpatient.

Routine laboratory blood testing is a commonly used diagnostic tool that physicians rely on to provide patient care. Although routine blood testing represents less than 5% of most hospital budgets, routine use and over-reliance on testing among physicians makes it a target of cost-reduction efforts.^1-3 A variety of interventions have been proposed to reduce inappropriate laboratory tests, with varying results.^1,4-6 Successful interventions include providing physicians with fee data associated with ordered laboratory tests, unbundling panels of tests, and multicomponent interventions.⁶ We conducted a multifaceted quality improvement study to promote and develop interventions to adopt appropriate blood test ordering practices.

Methods

Setting

This prospective cohort study took place at Mount Sinai Hospital, a 443-bed academic hospital affiliated with the University of Toronto, where more than 2400 learners rotate through annually. The study was approved by the Mount Sinai Hospital Research Ethics Board.

Participants

We included all inpatient admissions to the general internal medicine service between April 2016 and March 2018. Exclusion criteria included a length of stay (LOS) longer than 365 days and admission to a critical care unit. Patients with more than 1 admission were counted as separate hospital inpatient visits.

Intervention

Based on internal data, we targeted the top 3 most frequently ordered routine blood tests: complete blood count (CBC), creatinine, and electrolytes. Trainee interviews revealed that habit, bundled order sets, and fear of “missing something” contributed to inappropriate routine blood test ordering. Based on these root causes, we used the Model for Improvement to iteratively develop a multimodal intervention that began in July 2016.^7,8 This included a change to the computerized provider order entry (CPOE) to nudge clinicians to a restrictive ordering strategy by substituting the “Daily x3” frequency of blood test ordering with a “Daily x1” option on a pick list of order options. Clinicians could still order daily routine blood tests for any specified duration, but would have to do so by manually changing the default setting within the CPOE.

From July 2017 to March 2018, the research team educated residents on appropriate laboratory test ordering and provided audit and feedback data to the clinicians. Diagnostic uncertainty was addressed in teaching sessions. Attending physicians were surveyed on appropriate indications for daily laboratory testing for each of CBC, electrolytes, and creatinine. Appropriate indications (Figure 1) were displayed in visible clinical areas and incorporated into teaching sessions.⁹

Clinician teams received real-time performance data on their routine blood test ordering patterns compared with an institutional benchmark. Bar graphs of blood work ordering rates (sum of CBCs, creatinine, and electrolytes ordered for all patients on a given team divided by the total LOS for all patients) were distributed to each internal medicine team via email every 2 weeks (Figure 2).^1,10-12

Data Collection and Analysis

Data were extracted from the hospital electronic health record (EHR). The primary outcome was the number of routine blood tests (CBC, creatinine, and electrolytes) ordered per inpatient day. Descriptive statistics were calculated for demographic variables. We used statistical process control (SPC) charts to compare the baseline period (April 2016-June 2017) and the intervention period (July 2017-March 2018) for the primary outcome. SPC charts display process changes over time. Data are plotted in chronological order, with the central line representing the outcome mean, an upper line representing the upper control limit, and a lower line representing the lower control limit. The upper and lower limits were set at 3δ, which correspond to 3 standard deviations above and below the mean. Six successive points above or beyond the mean suggests “special cause variation,” indicating that observed results are unlikely due to secular trends. SPC charts are commonly used quality tools for process improvement as well as research.^13-16 These charts were created using QI Macros SPC software for Excel V. 2012.07 (KnowWare International, Denver, CO).

The direct cost of each laboratory test was acquired from the hospital laboratory department. The cost of each laboratory test (CBC = $7.54/test, electrolytes = $2.04/test, creatinine = $1.28/test, in Canadian dollars) was subsequently added together and multiplied by the pre- and post-intervention difference of total blood tests saved per inpatient day and then multiplied by 365 to arrive at an estimated cost savings per year.

Results

Over the study period, there were 6424 unique patient admissions on the general internal medicine service, with a median LOS of 3.5 days (Table).

The majority of inpatient visits had at least 1 test of CBC (80%; mean, 3.6 tests/visit), creatinine (79.3%; mean, 3.5 tests/visit), or electrolytes (81.6%; mean, 3.9 tests/visit) completed. In total, 56,767 laboratory tests were ordered.

Following the intervention, there was a reduction in both rates of routine blood test orders and their associated costs, with a shift below the mean. The mean number of tests ordered (combined CBC, creatinine, and electrolytes) per inpatient day decreased from 1.19 (SD, 0.21) in the pre-intervention period to 1.11 (SD, 0.05) in the post-intervention period (P < 0.0001), representing a 6.7% relative reduction (Figure 3). We observed a 6.2% relative reduction in costs per inpatient day, translating to a total savings of $26,851 over 1 year for the intervention period.

Discussion

Our study suggests that a multimodal intervention, including CPOE restrictions, resident education with posters, and audit and feedback strategies, can reduce lab test ordering on general internal medicine wards. This finding is similar to those of previous studies using a similar intervention, although different laboratory tests were targeted.^{1,2,5,6,10,17}

Our study found lower test result reductions than those reported by a previous study, which reported a relative reduction of 17% to 30%,¹⁸ and by another investigation that was conducted recently in a similar setting.¹⁷ In the latter study, reductions in laboratory testing were mostly found in nonroutine tests, and no significant improvements were noted in CBC, electrolytes, and creatine, the 3 tests we studied over the same duration.¹⁷ This may represent a ceiling effect to reducing laboratory testing, and efforts to reduce CBC, electrolytes, and creatinine testing beyond 0.3 to 0.4 tests per inpatient day (or combined 1.16 tests per inpatient day) may not be clinically appropriate or possible. This information can guide institutions to include other areas of overuse based on rates of utilization in order to maximize the benefits from a resource intensive intervention.

There are a number of limitations that merit discussion. First, observational studies do not demonstrate causation; however, to our knowledge, there were no other co-interventions that were being conducted during the study duration. One important note is that our project’s intervention began in July, at which point there are new internal medicine residents beginning their training. As the concept of resource allocation becomes more important, medical schools are spending more time educating students about Choosing Wisely, and, therefore, newer cohorts of residents may be more cognizant of appropriate blood testing. Second, this is a single-center study, limiting generalizability; however, we note that many other centers have reported similar findings. Another limitation is that we do not know whether there were any adverse clinical events associated with blood work ordering that was too restrictive, although informal tracking of STAT laboratory testing remained stable throughout the study period. It is important to ensure that blood work is ordered in moderation and tailored to patients using one’s clinical judgment.

Future Directions

We observed modest reductions in the quantity and costs associated with a quality improvement intervention aimed at reducing routine blood testing. A baseline rate of laboratory testing of less than 1 test per inpatient day may require including other target tests to drive down absolute utilization.

Corresponding author: Christine Soong, MD, MSc, 433-600 University Avenue, Toronto, Ontario, Canada M5G 1X5; Christine.soong@utoronto.ca.

Financial disclosures: None.

From the University of Toronto (Dr. Basuita, Corey L. Kamen, and Dr. Soong) and Sinai Health System (Corey L. Kamen, Cheryl Ethier, and Dr. Soong), Toronto, Ontario, Canada. Co-first authors are Manpreet Basuita, MD, and Corey L. Kamen, BSc.

Abstract

• Objective: Routine laboratory testing is common among medical inpatients; however, when ordered inappropriately testing can represent low-value care. We examined the impact of an evidence-based intervention bundle on utilization.
• Participants/setting: This prospective cohort study took place at a tertiary academic medical center and included 6424 patients admitted to the general internal medicine service between April 2016 and March 2018.
• Intervention: An intervention bundle, whose first components were implemented in July 2016, included computer order entry restrictions on repetitive laboratory testing, education, and audit-feedback.
• Measures: Data were extracted from the hospital electronic health record. The primary outcome was the number of routine blood tests (complete blood count, creatinine, and electrolytes) ordered per inpatient day.
• Analysis: Descriptive statistics were calculated for demographic variables. We used statistical process control charts to compare the baseline period (April 2016-June 2017) and the intervention period (July 2017-March 2018) for the primary outcome.
• Results: The mean number of combined routine laboratory tests ordered per inpatient day decreased from 1.19 (SD, 0.21) tests to 1.11 (SD, 0.05), a relative reduction of 6.7% (P < 0.0001). Mean cost per case related to laboratory tests decreased from $17.24 in the pre-intervention period to $16.17 in the post-intervention period (relative reduction of 6.2%). This resulted in savings of $26,851 in the intervention year.
• Conclusion: A laboratory intervention bundle was associated with small reductions in testing and costs. A routine test performed less than once per inpatient day may not be clinically appropriate or possible.

Keywords: utilization; clinical costs; quality improvement; QI intervention; internal medicine; inpatient.

Routine laboratory blood testing is a commonly used diagnostic tool that physicians rely on to provide patient care. Although routine blood testing represents less than 5% of most hospital budgets, routine use and over-reliance on testing among physicians makes it a target of cost-reduction efforts.^1-3 A variety of interventions have been proposed to reduce inappropriate laboratory tests, with varying results.^1,4-6 Successful interventions include providing physicians with fee data associated with ordered laboratory tests, unbundling panels of tests, and multicomponent interventions.⁶ We conducted a multifaceted quality improvement study to promote and develop interventions to adopt appropriate blood test ordering practices.

Methods

Setting

This prospective cohort study took place at Mount Sinai Hospital, a 443-bed academic hospital affiliated with the University of Toronto, where more than 2400 learners rotate through annually. The study was approved by the Mount Sinai Hospital Research Ethics Board.

Participants

We included all inpatient admissions to the general internal medicine service between April 2016 and March 2018. Exclusion criteria included a length of stay (LOS) longer than 365 days and admission to a critical care unit. Patients with more than 1 admission were counted as separate hospital inpatient visits.

Intervention

Based on internal data, we targeted the top 3 most frequently ordered routine blood tests: complete blood count (CBC), creatinine, and electrolytes. Trainee interviews revealed that habit, bundled order sets, and fear of “missing something” contributed to inappropriate routine blood test ordering. Based on these root causes, we used the Model for Improvement to iteratively develop a multimodal intervention that began in July 2016.^7,8 This included a change to the computerized provider order entry (CPOE) to nudge clinicians to a restrictive ordering strategy by substituting the “Daily x3” frequency of blood test ordering with a “Daily x1” option on a pick list of order options. Clinicians could still order daily routine blood tests for any specified duration, but would have to do so by manually changing the default setting within the CPOE.

From July 2017 to March 2018, the research team educated residents on appropriate laboratory test ordering and provided audit and feedback data to the clinicians. Diagnostic uncertainty was addressed in teaching sessions. Attending physicians were surveyed on appropriate indications for daily laboratory testing for each of CBC, electrolytes, and creatinine. Appropriate indications (Figure 1) were displayed in visible clinical areas and incorporated into teaching sessions.⁹

Clinician teams received real-time performance data on their routine blood test ordering patterns compared with an institutional benchmark. Bar graphs of blood work ordering rates (sum of CBCs, creatinine, and electrolytes ordered for all patients on a given team divided by the total LOS for all patients) were distributed to each internal medicine team via email every 2 weeks (Figure 2).^1,10-12

Data Collection and Analysis

Data were extracted from the hospital electronic health record (EHR). The primary outcome was the number of routine blood tests (CBC, creatinine, and electrolytes) ordered per inpatient day. Descriptive statistics were calculated for demographic variables. We used statistical process control (SPC) charts to compare the baseline period (April 2016-June 2017) and the intervention period (July 2017-March 2018) for the primary outcome. SPC charts display process changes over time. Data are plotted in chronological order, with the central line representing the outcome mean, an upper line representing the upper control limit, and a lower line representing the lower control limit. The upper and lower limits were set at 3δ, which correspond to 3 standard deviations above and below the mean. Six successive points above or beyond the mean suggests “special cause variation,” indicating that observed results are unlikely due to secular trends. SPC charts are commonly used quality tools for process improvement as well as research.^13-16 These charts were created using QI Macros SPC software for Excel V. 2012.07 (KnowWare International, Denver, CO).

The direct cost of each laboratory test was acquired from the hospital laboratory department. The cost of each laboratory test (CBC = $7.54/test, electrolytes = $2.04/test, creatinine = $1.28/test, in Canadian dollars) was subsequently added together and multiplied by the pre- and post-intervention difference of total blood tests saved per inpatient day and then multiplied by 365 to arrive at an estimated cost savings per year.

Results

Over the study period, there were 6424 unique patient admissions on the general internal medicine service, with a median LOS of 3.5 days (Table).

The majority of inpatient visits had at least 1 test of CBC (80%; mean, 3.6 tests/visit), creatinine (79.3%; mean, 3.5 tests/visit), or electrolytes (81.6%; mean, 3.9 tests/visit) completed. In total, 56,767 laboratory tests were ordered.

Following the intervention, there was a reduction in both rates of routine blood test orders and their associated costs, with a shift below the mean. The mean number of tests ordered (combined CBC, creatinine, and electrolytes) per inpatient day decreased from 1.19 (SD, 0.21) in the pre-intervention period to 1.11 (SD, 0.05) in the post-intervention period (P < 0.0001), representing a 6.7% relative reduction (Figure 3). We observed a 6.2% relative reduction in costs per inpatient day, translating to a total savings of $26,851 over 1 year for the intervention period.

Discussion

Our study suggests that a multimodal intervention, including CPOE restrictions, resident education with posters, and audit and feedback strategies, can reduce lab test ordering on general internal medicine wards. This finding is similar to those of previous studies using a similar intervention, although different laboratory tests were targeted.^{1,2,5,6,10,17}

Our study found lower test result reductions than those reported by a previous study, which reported a relative reduction of 17% to 30%,¹⁸ and by another investigation that was conducted recently in a similar setting.¹⁷ In the latter study, reductions in laboratory testing were mostly found in nonroutine tests, and no significant improvements were noted in CBC, electrolytes, and creatine, the 3 tests we studied over the same duration.¹⁷ This may represent a ceiling effect to reducing laboratory testing, and efforts to reduce CBC, electrolytes, and creatinine testing beyond 0.3 to 0.4 tests per inpatient day (or combined 1.16 tests per inpatient day) may not be clinically appropriate or possible. This information can guide institutions to include other areas of overuse based on rates of utilization in order to maximize the benefits from a resource intensive intervention.

There are a number of limitations that merit discussion. First, observational studies do not demonstrate causation; however, to our knowledge, there were no other co-interventions that were being conducted during the study duration. One important note is that our project’s intervention began in July, at which point there are new internal medicine residents beginning their training. As the concept of resource allocation becomes more important, medical schools are spending more time educating students about Choosing Wisely, and, therefore, newer cohorts of residents may be more cognizant of appropriate blood testing. Second, this is a single-center study, limiting generalizability; however, we note that many other centers have reported similar findings. Another limitation is that we do not know whether there were any adverse clinical events associated with blood work ordering that was too restrictive, although informal tracking of STAT laboratory testing remained stable throughout the study period. It is important to ensure that blood work is ordered in moderation and tailored to patients using one’s clinical judgment.

Future Directions

We observed modest reductions in the quantity and costs associated with a quality improvement intervention aimed at reducing routine blood testing. A baseline rate of laboratory testing of less than 1 test per inpatient day may require including other target tests to drive down absolute utilization.

Corresponding author: Christine Soong, MD, MSc, 433-600 University Avenue, Toronto, Ontario, Canada M5G 1X5; Christine.soong@utoronto.ca.

Financial disclosures: None.

From the University of Toronto (Dr. Basuita, Corey L. Kamen, and Dr. Soong) and Sinai Health System (Corey L. Kamen, Cheryl Ethier, and Dr. Soong), Toronto, Ontario, Canada. Co-first authors are Manpreet Basuita, MD, and Corey L. Kamen, BSc.

Abstract

• Objective: Routine laboratory testing is common among medical inpatients; however, when ordered inappropriately testing can represent low-value care. We examined the impact of an evidence-based intervention bundle on utilization.
• Participants/setting: This prospective cohort study took place at a tertiary academic medical center and included 6424 patients admitted to the general internal medicine service between April 2016 and March 2018.
• Intervention: An intervention bundle, whose first components were implemented in July 2016, included computer order entry restrictions on repetitive laboratory testing, education, and audit-feedback.
• Measures: Data were extracted from the hospital electronic health record. The primary outcome was the number of routine blood tests (complete blood count, creatinine, and electrolytes) ordered per inpatient day.
• Analysis: Descriptive statistics were calculated for demographic variables. We used statistical process control charts to compare the baseline period (April 2016-June 2017) and the intervention period (July 2017-March 2018) for the primary outcome.
• Results: The mean number of combined routine laboratory tests ordered per inpatient day decreased from 1.19 (SD, 0.21) tests to 1.11 (SD, 0.05), a relative reduction of 6.7% (P < 0.0001). Mean cost per case related to laboratory tests decreased from $17.24 in the pre-intervention period to $16.17 in the post-intervention period (relative reduction of 6.2%). This resulted in savings of $26,851 in the intervention year.
• Conclusion: A laboratory intervention bundle was associated with small reductions in testing and costs. A routine test performed less than once per inpatient day may not be clinically appropriate or possible.

Keywords: utilization; clinical costs; quality improvement; QI intervention; internal medicine; inpatient.

Routine laboratory blood testing is a commonly used diagnostic tool that physicians rely on to provide patient care. Although routine blood testing represents less than 5% of most hospital budgets, routine use and over-reliance on testing among physicians makes it a target of cost-reduction efforts.^1-3 A variety of interventions have been proposed to reduce inappropriate laboratory tests, with varying results.^1,4-6 Successful interventions include providing physicians with fee data associated with ordered laboratory tests, unbundling panels of tests, and multicomponent interventions.⁶ We conducted a multifaceted quality improvement study to promote and develop interventions to adopt appropriate blood test ordering practices.

Methods

Setting

This prospective cohort study took place at Mount Sinai Hospital, a 443-bed academic hospital affiliated with the University of Toronto, where more than 2400 learners rotate through annually. The study was approved by the Mount Sinai Hospital Research Ethics Board.

Participants

We included all inpatient admissions to the general internal medicine service between April 2016 and March 2018. Exclusion criteria included a length of stay (LOS) longer than 365 days and admission to a critical care unit. Patients with more than 1 admission were counted as separate hospital inpatient visits.

Intervention

Based on internal data, we targeted the top 3 most frequently ordered routine blood tests: complete blood count (CBC), creatinine, and electrolytes. Trainee interviews revealed that habit, bundled order sets, and fear of “missing something” contributed to inappropriate routine blood test ordering. Based on these root causes, we used the Model for Improvement to iteratively develop a multimodal intervention that began in July 2016.^7,8 This included a change to the computerized provider order entry (CPOE) to nudge clinicians to a restrictive ordering strategy by substituting the “Daily x3” frequency of blood test ordering with a “Daily x1” option on a pick list of order options. Clinicians could still order daily routine blood tests for any specified duration, but would have to do so by manually changing the default setting within the CPOE.

From July 2017 to March 2018, the research team educated residents on appropriate laboratory test ordering and provided audit and feedback data to the clinicians. Diagnostic uncertainty was addressed in teaching sessions. Attending physicians were surveyed on appropriate indications for daily laboratory testing for each of CBC, electrolytes, and creatinine. Appropriate indications (Figure 1) were displayed in visible clinical areas and incorporated into teaching sessions.⁹

Clinician teams received real-time performance data on their routine blood test ordering patterns compared with an institutional benchmark. Bar graphs of blood work ordering rates (sum of CBCs, creatinine, and electrolytes ordered for all patients on a given team divided by the total LOS for all patients) were distributed to each internal medicine team via email every 2 weeks (Figure 2).^1,10-12

Data Collection and Analysis

Data were extracted from the hospital electronic health record (EHR). The primary outcome was the number of routine blood tests (CBC, creatinine, and electrolytes) ordered per inpatient day. Descriptive statistics were calculated for demographic variables. We used statistical process control (SPC) charts to compare the baseline period (April 2016-June 2017) and the intervention period (July 2017-March 2018) for the primary outcome. SPC charts display process changes over time. Data are plotted in chronological order, with the central line representing the outcome mean, an upper line representing the upper control limit, and a lower line representing the lower control limit. The upper and lower limits were set at 3δ, which correspond to 3 standard deviations above and below the mean. Six successive points above or beyond the mean suggests “special cause variation,” indicating that observed results are unlikely due to secular trends. SPC charts are commonly used quality tools for process improvement as well as research.^13-16 These charts were created using QI Macros SPC software for Excel V. 2012.07 (KnowWare International, Denver, CO).

The direct cost of each laboratory test was acquired from the hospital laboratory department. The cost of each laboratory test (CBC = $7.54/test, electrolytes = $2.04/test, creatinine = $1.28/test, in Canadian dollars) was subsequently added together and multiplied by the pre- and post-intervention difference of total blood tests saved per inpatient day and then multiplied by 365 to arrive at an estimated cost savings per year.

Results

Over the study period, there were 6424 unique patient admissions on the general internal medicine service, with a median LOS of 3.5 days (Table).

The majority of inpatient visits had at least 1 test of CBC (80%; mean, 3.6 tests/visit), creatinine (79.3%; mean, 3.5 tests/visit), or electrolytes (81.6%; mean, 3.9 tests/visit) completed. In total, 56,767 laboratory tests were ordered.

Following the intervention, there was a reduction in both rates of routine blood test orders and their associated costs, with a shift below the mean. The mean number of tests ordered (combined CBC, creatinine, and electrolytes) per inpatient day decreased from 1.19 (SD, 0.21) in the pre-intervention period to 1.11 (SD, 0.05) in the post-intervention period (P < 0.0001), representing a 6.7% relative reduction (Figure 3). We observed a 6.2% relative reduction in costs per inpatient day, translating to a total savings of $26,851 over 1 year for the intervention period.

Discussion

Our study suggests that a multimodal intervention, including CPOE restrictions, resident education with posters, and audit and feedback strategies, can reduce lab test ordering on general internal medicine wards. This finding is similar to those of previous studies using a similar intervention, although different laboratory tests were targeted.^{1,2,5,6,10,17}

Our study found lower test result reductions than those reported by a previous study, which reported a relative reduction of 17% to 30%,¹⁸ and by another investigation that was conducted recently in a similar setting.¹⁷ In the latter study, reductions in laboratory testing were mostly found in nonroutine tests, and no significant improvements were noted in CBC, electrolytes, and creatine, the 3 tests we studied over the same duration.¹⁷ This may represent a ceiling effect to reducing laboratory testing, and efforts to reduce CBC, electrolytes, and creatinine testing beyond 0.3 to 0.4 tests per inpatient day (or combined 1.16 tests per inpatient day) may not be clinically appropriate or possible. This information can guide institutions to include other areas of overuse based on rates of utilization in order to maximize the benefits from a resource intensive intervention.

There are a number of limitations that merit discussion. First, observational studies do not demonstrate causation; however, to our knowledge, there were no other co-interventions that were being conducted during the study duration. One important note is that our project’s intervention began in July, at which point there are new internal medicine residents beginning their training. As the concept of resource allocation becomes more important, medical schools are spending more time educating students about Choosing Wisely, and, therefore, newer cohorts of residents may be more cognizant of appropriate blood testing. Second, this is a single-center study, limiting generalizability; however, we note that many other centers have reported similar findings. Another limitation is that we do not know whether there were any adverse clinical events associated with blood work ordering that was too restrictive, although informal tracking of STAT laboratory testing remained stable throughout the study period. It is important to ensure that blood work is ordered in moderation and tailored to patients using one’s clinical judgment.

Future Directions

We observed modest reductions in the quantity and costs associated with a quality improvement intervention aimed at reducing routine blood testing. A baseline rate of laboratory testing of less than 1 test per inpatient day may require including other target tests to drive down absolute utilization.

Corresponding author: Christine Soong, MD, MSc, 433-600 University Avenue, Toronto, Ontario, Canada M5G 1X5; Christine.soong@utoronto.ca.

Financial disclosures: None.

Cardiac biomarker testing, along with a thorough patient history, physical exam, and an electrocardiogram, is required for the diagnosis of patients with suspected acute coronary syndrome (ACS). For nearly 3 decades, 2 cardiac biomarkers, troponin (I or T) and creatine kinase-MB fraction (CK-MB), have been ordered together to evaluate ACS patients out of concern that utilizing a single biomarker might be less diagnostically accurate than using 2 biomarkers. However, subsequent studies have shown that troponin is far more sensitive and specific for myocardial injury than CK-MB.^1,2 Troponin testing offers important prognostic information irrespective of whether the CK-MB is normal or abnormal.^3,4 In 2015, the American Society of Clinical Pathology released a Choosing Wisely^® recommendation against ordering CK-MB (or myoglobin) for the diagnosis of acute myocardial infarction (AMI).⁵ This reflects an emerging consensus that CK-MB testing represents low-value care while troponin testing alone is the appropriate diagnostic strategy for ACS patients.

Remarkably, we know very little about patterns of cardiac biomarker utilization in clinical practice. In this issue of the Journal of Hospital Medicine, Prochaska et al.⁶ provide a valuable snapshot of troponin and CK-MB utilization at 91 U.S. academic medical centers (AMCs) for 18 months prior to and following the release of the 2015 Choosing Wisely^® recommendation. From a retrospective review of 106,954 inpatient discharges with a principal diagnosis of AMI, they report a 29.2% rate of troponin-only testing in 2013 with a gradual increase over 3 years to 53.5% in 2016. Interestingly, the study’s baseline troponin-only utilization rate is consistent with a 2013 College of American Pathologists survey, which estimated that 23% of U.S. clinical laboratories no longer process CK-MB (and therefore run troponins alone).⁷

Did the 2015 Choosing Wisely^® recommendation have an impact on providers choosing cardiac biomarkers wisely? The authors answer this question in a novel way by stratifying hospitals into performance tertiles for each study quarter and then further classifying them into groups that were consistently high, middle, and low performers throughout the study period. Using an interrupted time series design, they identify 26 hospitals who improved their troponin-only testing performance tertile during the study period and examine their average quarterly rate of change. As illustrated in Figure 3, they report a sharp increase in the rate of change of troponin-only testing shortly after the release of the 2015 Choosing Wisely^® recommendation. The authors reasonably conclude that the Choosing Wisely^® campaign “appeared to facilitate accelerated adoption of troponin-only testing” among these hospitals.

However, we should interpret these results with caution. The authors highlight several limitations, including the absence of causality common in observational studies and insufficient time to follow-up to capture the full (or transient) impact of the intervention. There are factors external to the Choosing Wisely^® campaign that may have influenced cardiac biomarker testing patterns observed. Examples include variation in hospital leadership, financial drivers, and local culture that promote high-value care. We also note that (1) there are several published interventions to improve troponin-only ordering that predate the Choosing Wisely^® campaign^8,9; (2) a prominent cardiology guideline endorsed the use of troponin as a preferred cardiac biomarker in 2012¹⁰; and (3) a widely cited opinion by prominent researchers called for the elimination of CK-MB from clinical practice in 2008.¹¹ These publications suggest there was already an awareness of and efforts underway to improve cardiac enzyme testing contributing to the results described by Prochaska et al.

Limitations notwithstanding, we commend Prochaska et al. for conducting the first-known description of patient-level trend rates of troponin and CK-MB testing. Finally, it is worth noting that where there is accomplishment, there is also opportunity. At the end of the study period, nearly 50% of institutions had yet to adopt a troponin-only strategy. While there has been an overall trend towards improvement, this number remains high. We may conjecture as to possible explanations: Providers may be unconvinced that a single troponin is sufficient in the diagnosis of ACS (ie, lack of knowledge or debate over the interpretation of available science), stakeholders may be slow to de-adopt practices using appropriate systems levers (eg, laboratories delisting CK-MB processing), and incentives may be lacking to motivate AMCs. The results of this study should be used as a burning platform to those who wish to “test wisely” in cardiac biomarker use.

Disclosure

The authors report no conflicts of interest or financial disclosures.

Cardiac biomarker testing, along with a thorough patient history, physical exam, and an electrocardiogram, is required for the diagnosis of patients with suspected acute coronary syndrome (ACS). For nearly 3 decades, 2 cardiac biomarkers, troponin (I or T) and creatine kinase-MB fraction (CK-MB), have been ordered together to evaluate ACS patients out of concern that utilizing a single biomarker might be less diagnostically accurate than using 2 biomarkers. However, subsequent studies have shown that troponin is far more sensitive and specific for myocardial injury than CK-MB.^1,2 Troponin testing offers important prognostic information irrespective of whether the CK-MB is normal or abnormal.^3,4 In 2015, the American Society of Clinical Pathology released a Choosing Wisely^® recommendation against ordering CK-MB (or myoglobin) for the diagnosis of acute myocardial infarction (AMI).⁵ This reflects an emerging consensus that CK-MB testing represents low-value care while troponin testing alone is the appropriate diagnostic strategy for ACS patients.

Remarkably, we know very little about patterns of cardiac biomarker utilization in clinical practice. In this issue of the Journal of Hospital Medicine, Prochaska et al.⁶ provide a valuable snapshot of troponin and CK-MB utilization at 91 U.S. academic medical centers (AMCs) for 18 months prior to and following the release of the 2015 Choosing Wisely^® recommendation. From a retrospective review of 106,954 inpatient discharges with a principal diagnosis of AMI, they report a 29.2% rate of troponin-only testing in 2013 with a gradual increase over 3 years to 53.5% in 2016. Interestingly, the study’s baseline troponin-only utilization rate is consistent with a 2013 College of American Pathologists survey, which estimated that 23% of U.S. clinical laboratories no longer process CK-MB (and therefore run troponins alone).⁷

Did the 2015 Choosing Wisely^® recommendation have an impact on providers choosing cardiac biomarkers wisely? The authors answer this question in a novel way by stratifying hospitals into performance tertiles for each study quarter and then further classifying them into groups that were consistently high, middle, and low performers throughout the study period. Using an interrupted time series design, they identify 26 hospitals who improved their troponin-only testing performance tertile during the study period and examine their average quarterly rate of change. As illustrated in Figure 3, they report a sharp increase in the rate of change of troponin-only testing shortly after the release of the 2015 Choosing Wisely^® recommendation. The authors reasonably conclude that the Choosing Wisely^® campaign “appeared to facilitate accelerated adoption of troponin-only testing” among these hospitals.

However, we should interpret these results with caution. The authors highlight several limitations, including the absence of causality common in observational studies and insufficient time to follow-up to capture the full (or transient) impact of the intervention. There are factors external to the Choosing Wisely^® campaign that may have influenced cardiac biomarker testing patterns observed. Examples include variation in hospital leadership, financial drivers, and local culture that promote high-value care. We also note that (1) there are several published interventions to improve troponin-only ordering that predate the Choosing Wisely^® campaign^8,9; (2) a prominent cardiology guideline endorsed the use of troponin as a preferred cardiac biomarker in 2012¹⁰; and (3) a widely cited opinion by prominent researchers called for the elimination of CK-MB from clinical practice in 2008.¹¹ These publications suggest there was already an awareness of and efforts underway to improve cardiac enzyme testing contributing to the results described by Prochaska et al.

Limitations notwithstanding, we commend Prochaska et al. for conducting the first-known description of patient-level trend rates of troponin and CK-MB testing. Finally, it is worth noting that where there is accomplishment, there is also opportunity. At the end of the study period, nearly 50% of institutions had yet to adopt a troponin-only strategy. While there has been an overall trend towards improvement, this number remains high. We may conjecture as to possible explanations: Providers may be unconvinced that a single troponin is sufficient in the diagnosis of ACS (ie, lack of knowledge or debate over the interpretation of available science), stakeholders may be slow to de-adopt practices using appropriate systems levers (eg, laboratories delisting CK-MB processing), and incentives may be lacking to motivate AMCs. The results of this study should be used as a burning platform to those who wish to “test wisely” in cardiac biomarker use.

Disclosure

The authors report no conflicts of interest or financial disclosures.

Cardiac biomarker testing, along with a thorough patient history, physical exam, and an electrocardiogram, is required for the diagnosis of patients with suspected acute coronary syndrome (ACS). For nearly 3 decades, 2 cardiac biomarkers, troponin (I or T) and creatine kinase-MB fraction (CK-MB), have been ordered together to evaluate ACS patients out of concern that utilizing a single biomarker might be less diagnostically accurate than using 2 biomarkers. However, subsequent studies have shown that troponin is far more sensitive and specific for myocardial injury than CK-MB.^1,2 Troponin testing offers important prognostic information irrespective of whether the CK-MB is normal or abnormal.^3,4 In 2015, the American Society of Clinical Pathology released a Choosing Wisely^® recommendation against ordering CK-MB (or myoglobin) for the diagnosis of acute myocardial infarction (AMI).⁵ This reflects an emerging consensus that CK-MB testing represents low-value care while troponin testing alone is the appropriate diagnostic strategy for ACS patients.

Remarkably, we know very little about patterns of cardiac biomarker utilization in clinical practice. In this issue of the Journal of Hospital Medicine, Prochaska et al.⁶ provide a valuable snapshot of troponin and CK-MB utilization at 91 U.S. academic medical centers (AMCs) for 18 months prior to and following the release of the 2015 Choosing Wisely^® recommendation. From a retrospective review of 106,954 inpatient discharges with a principal diagnosis of AMI, they report a 29.2% rate of troponin-only testing in 2013 with a gradual increase over 3 years to 53.5% in 2016. Interestingly, the study’s baseline troponin-only utilization rate is consistent with a 2013 College of American Pathologists survey, which estimated that 23% of U.S. clinical laboratories no longer process CK-MB (and therefore run troponins alone).⁷

Did the 2015 Choosing Wisely^® recommendation have an impact on providers choosing cardiac biomarkers wisely? The authors answer this question in a novel way by stratifying hospitals into performance tertiles for each study quarter and then further classifying them into groups that were consistently high, middle, and low performers throughout the study period. Using an interrupted time series design, they identify 26 hospitals who improved their troponin-only testing performance tertile during the study period and examine their average quarterly rate of change. As illustrated in Figure 3, they report a sharp increase in the rate of change of troponin-only testing shortly after the release of the 2015 Choosing Wisely^® recommendation. The authors reasonably conclude that the Choosing Wisely^® campaign “appeared to facilitate accelerated adoption of troponin-only testing” among these hospitals.

However, we should interpret these results with caution. The authors highlight several limitations, including the absence of causality common in observational studies and insufficient time to follow-up to capture the full (or transient) impact of the intervention. There are factors external to the Choosing Wisely^® campaign that may have influenced cardiac biomarker testing patterns observed. Examples include variation in hospital leadership, financial drivers, and local culture that promote high-value care. We also note that (1) there are several published interventions to improve troponin-only ordering that predate the Choosing Wisely^® campaign^8,9; (2) a prominent cardiology guideline endorsed the use of troponin as a preferred cardiac biomarker in 2012¹⁰; and (3) a widely cited opinion by prominent researchers called for the elimination of CK-MB from clinical practice in 2008.¹¹ These publications suggest there was already an awareness of and efforts underway to improve cardiac enzyme testing contributing to the results described by Prochaska et al.

Limitations notwithstanding, we commend Prochaska et al. for conducting the first-known description of patient-level trend rates of troponin and CK-MB testing. Finally, it is worth noting that where there is accomplishment, there is also opportunity. At the end of the study period, nearly 50% of institutions had yet to adopt a troponin-only strategy. While there has been an overall trend towards improvement, this number remains high. We may conjecture as to possible explanations: Providers may be unconvinced that a single troponin is sufficient in the diagnosis of ACS (ie, lack of knowledge or debate over the interpretation of available science), stakeholders may be slow to de-adopt practices using appropriate systems levers (eg, laboratories delisting CK-MB processing), and incentives may be lacking to motivate AMCs. The results of this study should be used as a burning platform to those who wish to “test wisely” in cardiac biomarker use.

Disclosure

The authors report no conflicts of interest or financial disclosures.

Older adults commonly experience insomnia and agitation during hospitalization. Unfortunately, the use of benzodiazepines and sedative hypnotics (BSH) to treat these conditions can be ineffective and expose patients to significant adverse effects.^1,2 Choosing Wisely^® is a campaign that promotes dialogue to reduce unnecessary medical tests, procedures, or treatments. This international campaign has highlighted BSHs as potentially harmful and has recommended against their use as first-line treatment of insomnia and agitation.^3-5 Examples of harm with benzodiazepine use include cognitive impairment, impaired postural stability, and an increased incidence of falls and hip fractures in both community and acute care settings.^6-8 In addition, prescriptions initiated in hospital appear to be associated with a higher risk of falls and unplanned readmission.^9,10 The newer nonbenzodiazepine sedative hypnotics, commonly referred to as “z-drugs”, were initially marketed as a safer alternative in older adults due to their more favorable pharmacokinetics. Evidence has emerged that they carry similar risks.^6,11,12 A study comparing benzodiazepines and zolpidem found relatively greater risk of fractures requiring hospitalization with the use of zolpidem compared to lorazepam.¹³

The use of benzodiazepines in the acute care setting has been evaluated in a number of studies and ranges from 20% to 45%.^14-16 Few studies focus on the initiation of these medications in BSH-naïve hospitalized patients; however, reports range from 18% to 29%.^17,18 Factors found to be associated with potentially inappropriate prescriptions (PIP) include Hispanic ethnicity, residing in an assisted care setting, and a greater number of BSH prescriptions prior to admission.^16,19 Additionally, Cumbler et al.¹⁵ found that the presence of dementia was associated with fewer prescriptions for sleep aids in hospital. To our knowledge, there are no published studies that have investigated prescriber factors associated with the use of BSH.

The purpose of our study was to determine the frequency of PIPs of BSH in our academic hospital. Additionally, we aimed to identify patient and prescriber factors that were associated with increased likelihood of prescriptions to help guide future quality improvement initiatives.

Study Design and Setting

This was a retrospective observational study conducted at Mount Sinai Hospital (MSH) in Toronto over a 4-month period from January 2013 to April 2013. The hospital is a 442-bed acute care academic health science center affiliated with the University of Toronto. The MSH electronic health record contains demographic data, medications and allergies, nursing documentation, and medical histories from prior encounters. It also includes computerized physician order entry (CPOE) and a detailed medication administration record. This system is integrated with an electronic pharmacy database used to monitor and dispense medications for each patient.

Patient and Medication Selection

We included inpatients over the age of 65 who were prescribed a BSH during the study period from the following services: general internal medicine, cardiology, general surgery, orthopedic surgery, and otolaryngology. To identify new exposure to BSHs, we excluded patients who were regularly prescribed a BSH prior to admission to hospital. The medications of interest included all benzodiazepines and the nonbenzodiazepine sedative hypnotic, zopiclone. Zopiclone is the most commonly used nonbenzodiazepine sedative hypnotic in Canada and the only 1 available on our hospital formulary. These were selected based on the strength of evidence to recommend against their use as first-line agents in older adults and in consultation with our geriatric medicine consultation team pharmacist.²⁰

Data Collection

The hospital administrative database provided patient demographic information, admission service, admitting diagnosis, length of stay, and the total number of patients discharged from the study units over the study period. We then searched the pharmacy electronic database for all benzodiazepines and zopiclone prescribed during the study period for patients who met the inclusion criteria. Manual review of paper and electronic health records for this cohort of patients was conducted to extract additional variables. We used a standardized form to record data elements. Dr. Pek collected all data elements. Dr. Remfry reviewed a random sample of patient records (10%) to ensure accuracy. The agreement between reviewers was 100%.

In compliance with hospital accreditation standards, a clinical pharmacist documents a best possible medication history (BPMH) on every inpatient on admission. We used the BPMH to identify and exclude patients who were prescribed a BSH prior to hospitalization. Because all medications were ordered through the CPOE system, as-needed medication prescriptions required the selection of a specified indication. Available options included ‘agitation/anxiety’ and necessitated combining these 2 indications into 1 category. Indications were primarily extracted through electronic order entry reviews. Paper charts were reviewed when further clarification was needed.

We identified ordering physicians’ training level and familiarity with the service from administrative records obtained from medical education offices, hospital records, and relevant call schedules. Fellows were defined as trainees with a minimum of 6 years of postgraduate training.

Our primary outcome of interest was the proportion of eligible patients age 65 and older who received a PIP for a BSH. Patient variables of interest included age, sex, comorbid conditions, and a pre-admission diagnosis of dementia. Comorbid conditions and age were used to calculate the Carlson Comorbidity Index for each patient.²¹ Prescription variables included the medication prescribed, time of first prescription (“overnight hours” refer to prescriptions ordered after 7:00 PM and before 7:00 AM), and whether the medication was ordered as part of an admission or postoperative order set. To determine whether patients were discharged home with a prescription for a BSH, we reviewed electronic discharge prescriptions of BSH-naïve patients who received a sedative in hospital. Only medical and cardiology inpatients receive electronic discharge prescriptions, and these were available for 189 patients in our cohort. Provider variables included training level, service, and familiarity with patients. We used the provider’s training program or department of appointment to define the ‘physician on-service’ variable. As an example, a resident registered in internal medicine is defined as ‘on-service’ when prescribing sedatives for a medical inpatient. In contrast, a psychiatry resident would be considered “off-service” if he prescribed a sedative for a surgical inpatient. The familiarity of a provider was categorized as ‘regular’ if they were responsible for a patient’s care on a day-to-day basis and ‘covering’ if they were only covering on call. Other variables included admitting service and hospital length of stay.

Appropriateness Criteria

Criteria for potentially inappropriate use were modified from the American and Canadian Geriatrics Societies’ Choosing Wisely recommendations,^4,5 and included insomnia and agitation. These recommendations are in line with other evidence based guidelines for safe prescribing in older adults.²⁰ For the purposes of our study, prescriptions for “agitation/anxiety”, “agitation”, or “insomnia/sleep” were considered potentially inappropriate. Appropriate indications included alcohol withdrawal, end-of-life symptom control, preprocedural sedation, and seizure.⁵ Patients who were already using a BSH prior to admission for any indication, including a psychiatric diagnosis, were excluded.

Statistical Analyses

We determined the proportion of patients with at least one PIP, as well as the proportion of all prescribing events that were potentially inappropriate. We used the Chi-square statistic and 2-sample t tests to compare the unadjusted associations between patient-level characteristics and receipt of at least 1 inappropriate prescription and prescribing event-level factors with inappropriate prescriptions. Given that first-year residents are more likely to be working overnight when most PIPs are prescribed, we performed a simple logistic regression of potentially inappropriate prescribing by level of training stratified by time of prescription. A multivariable random-intercept logistic regression model was used to assess the adjusted association between patient- and prescribing event-level characteristics with inappropriate prescribing, adjusting for clustering of prescribing events within patients. Characteristics of interest were identified a priori and those with significant bivariate associations with potentially inappropriate were selected for inclusion in the model. Additionally, we included time of prescription in our model to control for potential confounding. All statistical analyses were performed using SAS 9.4 (SAS Institute Inc, Cary, North Carolina). The MSH Research Ethics Board approved the study.

Description of Patients Prescribed a Benzodiazepine Sedative Hypnotic

There were 1540 patients over the age of 65 discharged during the 4-month study period. We excluded the 232 patients who had been prescribed a BSH prior to admission. Of the remaining eligible 1308 BSH-naïve patients, 251 (19.2%) were prescribed a new BSH in hospital and were included in the study. Of this cohort of 251 patients, 193 (76.9%) patients were prescribed a single BSH during their admission while 58 (23.1%) received 2 or more. Of all eligible patients, 208 (15.9%) were prescribed at least 1 PIP. Approximately half of the cohort was admitted to the general internal medicine service, and the most common reason for admission was cardiovascular disease (Table 1).

Description of Prescriptions of Benzodiazepine Sedative Hypnotic

We reviewed 328 prescriptions for BSH during the study period. The majority of these, 254 (77.4%) were potentially inappropriate (Table 2). The most common PIPs were zopiclone (167; 65.7%) and lorazepam (82; 32.3%). The PIPs were most frequently ordered on an as-needed basis (219; 86%), followed by one-time orders (30; 12%), and standing orders (5; 2%). The majority of PIPs (222; 87.4%) was prescribed for insomnia with a minority (32; 12.6%) prescribed for agitation and/or anxiety.

Most PIP were prescribed during overnight hours (159; 62.6%) and when an in-house pharmacist was unavailable (211; 83.1%). These variables were highly correlated with prescription of sleep aid, which was defined in our criteria as potentially inappropriate. Copies of discharge prescriptions were available for 189 patients. Of these 189 patients, 19 (10.1%) were sent home with a prescription for a new sedative.

Association Between Patient/Provider Variables and Prescriptions

Patient factors associated with fewer PIPs in our bivariate analyses included older age and dementia (Table 1). A greater proportion of nighttime prescriptions were PIPs; however, this finding was not statistically significant (P = 0.067). The majority of all prescriptions was prescribed by residents in their first year of training (64.9%; Table 2), and there was a significant difference in rates of PIP across level of training (P = 0.0007). When stratified by time of prescription, there was no significant difference by level of training for nighttime prescriptions. Among daytime prescriptions, second-year residents and staff (attending physicians and fellows) were less likely to prescribe a PIP than first-year residents (odds ratio [OR], 0.24; 95% confidence interval [CI], 0.09-0.66 and OR, 0.39; 95% CI, 0.14-1.13, respectively; Table 3); however, the association between staff and first-years only approached statistical significance (P = 0.08). Interestingly, 20.4% of all PIPs were ordered routinely as part of an admission or postoperative order set.

In our regression model, admission to a specialty or surgical service, compared to the general internal medicine service, was associated with a significantly higher likelihood of a PIP (OR, 6.61; 95% CI, 2.70-16.17; Table 4). Additionally, compared to cardiovascular admission diagnoses, neoplastic admitting diagnoses were associated with a higher likelihood of a PIP (OR, 4.43; 95% CI, 1.23-15.95). Time of prescription was a significant predictor in our multivariable regression model with nighttime prescriptions having increased odds of a PIP (OR, 4.48; 95% CI, 2.21-9.06,). When comparing prescribers at the extremes of training, attending physicians and fellows were much less likely to prescribe a PIP compared to first-year residents (OR, 0.23; 95% CI, 0.08-0.69; Table 4). However, there were no other significant differences across training levels after adjusting for patient and prescribing event characteristics.

We found that the majority of newly prescribed BSH in hospital was for the potentially inappropriate indications of insomnia and agitation/anxiety. Medications for insomnia were primarily initiated during overnight hours. Training level of prescribers and admitting service were found to be associated with appropriateness of prescriptions.

Our study showed that 15.9% of hospitalized older adults were newly prescribed a PIP during their admission. Of all new in hospital prescriptions, 77% were deemed potentially inappropriate. These numbers are similar to those reported by other centers; however, wide ranges exist.^16,19 This is likely the result of differences in appropriate use and inclusion criteria. Gillis et al.¹⁷ focused their investigation on sleep aids and showed that 26% of all admitted patients and 18% of BSH naïve patients received a prescription for insomnia. While this is similar to our findings, more than half of these patients were under the age of 65, and additional medications, such as trazodone, antihistamines, and antipsychotics were included.¹⁷ Other studies did not exclude patients who used a BSH regularly prior to admission. For example, 21% of veterans admitted to an acute care facility received a prescription for potentially inappropriate indications, but this included continuation of prior home medications.¹⁹ In contrast, we chose to focus on older adults in whom BSH pose a greater risk of harm. Exclusion of patients who regularly used a BSH prior to admission allowed us to better understand the circumstances surrounding the initiation of these medications in hospital. Furthermore, abrupt cessation of benzodiazepines can cause withdrawal and worsen confusion.²²

We found that 10% of patients newly prescribed a BSH in hospital were discharged with a prescription for a BSH. The accuracy of this is limited by the lack of availability of electronic discharge prescriptions on our surgical wards; however, it is likely an underrepresentation of the true effect given the high rates of PIPs on these wards. Our study highlights the concerning practice of continuing newly prescribed BSH following discharge from hospital.

Sleep disruption and poor quality sleep in hospital is a common issue that leads to significant use of BSH.¹⁵ Nonpharmacologic interventions in older adults can be effective in improving sleep quality and reducing the need for BSH; however, they can be time-consuming to implement.²³ With the exception of preventative strategies used on our Acute Care for Elders unit, formal nonpharmacologic interventions for sleep are not practiced in our hospital. We found that the majority of PIPs were prescribed as sleep aids in the overnight hours. This suggests that disruptions in sleep are leading patients and nursing staff to request pharmacologic treatments and highlights an area with significant room for improvement. Work is underway to implement and evaluate safe sleep protocols for older adults.

To our knowledge, we are the first to report an association between training level and PIP of BSH in older adults. The highest rates of PIPs were found among the first-year residents and, after controlling for patient and prescribing event characteristics, such as time of prescription, first-year residents were significantly more likely to prescribe a PIP. First-year residents are more likely to respond first to issues on the wards. There may be pressure on first-year trainees to prescribe sleep aids, as many patients and nurses may seek pharmacologic solutions for symptom management. Knowledge gaps may also be a contributing factor early in their training. A survey of physicians found that residents were more likely than attending physicians to list lack of formal education as a barrier to appropriate prescribing.²⁴

Similarities are seen in a study of antibiotic appropriateness, where residents demonstrated gaps in knowledge of treatment of asymptomatic bacteriuria that seemed to vary by specialty.²⁵ Interestingly, we found that patients admitted to general internal medicine were prescribed fewer PIPs. This service includes our Acute Care for Elders unit, which is staffed by trained geriatric nurses and other allied health professionals. Residents who rotated on internal medicine are also likely to have received informal teaching about medication safety in older adults. Educational interventions highlighting adverse effects of BSH and promoting nonpharmacologic solutions should be targeted at first-year residents. However, an interprofessional team approach to sleep disturbance in hospital, in combination with decision support for appropriate BSH use will achieve greater impact than education alone.

Several limitations of this study merit discussion. First, findings from a single academic center may lack generalizability. However, the demographics of our patient population and our rates of BSH use were similar to those reported in previous studies. Second, our study may be subject to observer bias, as the data collectors were not blinded. To minimize this, a strict template and clear appropriateness criteria were developed. Additionally, a second reviewer independently conducted data validation with 100% agreement among reviewers. Third, we studied prescribing patterns rather than medication administration and lacked data on filling of new BSH prescriptions in the postdischarge period. However, our primary goal is to determine risk of exposure to a BSH to minimize it. Fourth, although BSH are discouraged as “first choice for insomnia, anxiety or delirium,”⁴ they may be appropriate in limited situations where all nonpharmacologic strategies have failed and patient or staff safety is at risk. In our chart reviews, we were unable to determine whether all nonpharmacologic strategies were exhausted prior to prescription initiation. However, more than 20% of all PIP were routinely prescribed as part of an admission or postoperative order set, suggesting a reflexive rather than reflective approach to sedative use. Furthermore, the indications of anxiety and agitation were combined as they appear in the CPOE as a combination indication, thus leaving us unable to determine the true proportion for each indication. However, more than 87% of all PIPs were for insomnia, reflecting a clear opportunity to improve sleep management in hospital. Last, the lack of a power calculation may have resulted in the study being underpowered and thus affected the ability to detect a significant effect of covariates that have real differences on the likelihood of sedative prescriptions. For example, the low number of prescribing events by second-year residents and staff may have resulted in a type II error when comparing PIP rates with first-year residents.

We found that the majority of newly prescribed BSH among older adults in hospital were potentially inappropriate. They were most frequently prescribed by first-year residents overnight in response to insomnia. Our findings demonstrate BSH overuse remains prevalent and is associated with poor sleep in hospital. Future work will focus on implementing and evaluating safe sleep protocols and educational interventions aimed at first-year residents.

Acknowledgments

Elisabeth Pek had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. Ciara Pendrith conducted and is responsible for the statistical analysis.

Disclosure

The authors report no financial conflicts of interest.

Older adults commonly experience insomnia and agitation during hospitalization. Unfortunately, the use of benzodiazepines and sedative hypnotics (BSH) to treat these conditions can be ineffective and expose patients to significant adverse effects.^1,2 Choosing Wisely^® is a campaign that promotes dialogue to reduce unnecessary medical tests, procedures, or treatments. This international campaign has highlighted BSHs as potentially harmful and has recommended against their use as first-line treatment of insomnia and agitation.^3-5 Examples of harm with benzodiazepine use include cognitive impairment, impaired postural stability, and an increased incidence of falls and hip fractures in both community and acute care settings.^6-8 In addition, prescriptions initiated in hospital appear to be associated with a higher risk of falls and unplanned readmission.^9,10 The newer nonbenzodiazepine sedative hypnotics, commonly referred to as “z-drugs”, were initially marketed as a safer alternative in older adults due to their more favorable pharmacokinetics. Evidence has emerged that they carry similar risks.^6,11,12 A study comparing benzodiazepines and zolpidem found relatively greater risk of fractures requiring hospitalization with the use of zolpidem compared to lorazepam.¹³

The use of benzodiazepines in the acute care setting has been evaluated in a number of studies and ranges from 20% to 45%.^14-16 Few studies focus on the initiation of these medications in BSH-naïve hospitalized patients; however, reports range from 18% to 29%.^17,18 Factors found to be associated with potentially inappropriate prescriptions (PIP) include Hispanic ethnicity, residing in an assisted care setting, and a greater number of BSH prescriptions prior to admission.^16,19 Additionally, Cumbler et al.¹⁵ found that the presence of dementia was associated with fewer prescriptions for sleep aids in hospital. To our knowledge, there are no published studies that have investigated prescriber factors associated with the use of BSH.

The purpose of our study was to determine the frequency of PIPs of BSH in our academic hospital. Additionally, we aimed to identify patient and prescriber factors that were associated with increased likelihood of prescriptions to help guide future quality improvement initiatives.

Study Design and Setting

This was a retrospective observational study conducted at Mount Sinai Hospital (MSH) in Toronto over a 4-month period from January 2013 to April 2013. The hospital is a 442-bed acute care academic health science center affiliated with the University of Toronto. The MSH electronic health record contains demographic data, medications and allergies, nursing documentation, and medical histories from prior encounters. It also includes computerized physician order entry (CPOE) and a detailed medication administration record. This system is integrated with an electronic pharmacy database used to monitor and dispense medications for each patient.

Patient and Medication Selection

We included inpatients over the age of 65 who were prescribed a BSH during the study period from the following services: general internal medicine, cardiology, general surgery, orthopedic surgery, and otolaryngology. To identify new exposure to BSHs, we excluded patients who were regularly prescribed a BSH prior to admission to hospital. The medications of interest included all benzodiazepines and the nonbenzodiazepine sedative hypnotic, zopiclone. Zopiclone is the most commonly used nonbenzodiazepine sedative hypnotic in Canada and the only 1 available on our hospital formulary. These were selected based on the strength of evidence to recommend against their use as first-line agents in older adults and in consultation with our geriatric medicine consultation team pharmacist.²⁰

Data Collection

The hospital administrative database provided patient demographic information, admission service, admitting diagnosis, length of stay, and the total number of patients discharged from the study units over the study period. We then searched the pharmacy electronic database for all benzodiazepines and zopiclone prescribed during the study period for patients who met the inclusion criteria. Manual review of paper and electronic health records for this cohort of patients was conducted to extract additional variables. We used a standardized form to record data elements. Dr. Pek collected all data elements. Dr. Remfry reviewed a random sample of patient records (10%) to ensure accuracy. The agreement between reviewers was 100%.

In compliance with hospital accreditation standards, a clinical pharmacist documents a best possible medication history (BPMH) on every inpatient on admission. We used the BPMH to identify and exclude patients who were prescribed a BSH prior to hospitalization. Because all medications were ordered through the CPOE system, as-needed medication prescriptions required the selection of a specified indication. Available options included ‘agitation/anxiety’ and necessitated combining these 2 indications into 1 category. Indications were primarily extracted through electronic order entry reviews. Paper charts were reviewed when further clarification was needed.

We identified ordering physicians’ training level and familiarity with the service from administrative records obtained from medical education offices, hospital records, and relevant call schedules. Fellows were defined as trainees with a minimum of 6 years of postgraduate training.

Our primary outcome of interest was the proportion of eligible patients age 65 and older who received a PIP for a BSH. Patient variables of interest included age, sex, comorbid conditions, and a pre-admission diagnosis of dementia. Comorbid conditions and age were used to calculate the Carlson Comorbidity Index for each patient.²¹ Prescription variables included the medication prescribed, time of first prescription (“overnight hours” refer to prescriptions ordered after 7:00 PM and before 7:00 AM), and whether the medication was ordered as part of an admission or postoperative order set. To determine whether patients were discharged home with a prescription for a BSH, we reviewed electronic discharge prescriptions of BSH-naïve patients who received a sedative in hospital. Only medical and cardiology inpatients receive electronic discharge prescriptions, and these were available for 189 patients in our cohort. Provider variables included training level, service, and familiarity with patients. We used the provider’s training program or department of appointment to define the ‘physician on-service’ variable. As an example, a resident registered in internal medicine is defined as ‘on-service’ when prescribing sedatives for a medical inpatient. In contrast, a psychiatry resident would be considered “off-service” if he prescribed a sedative for a surgical inpatient. The familiarity of a provider was categorized as ‘regular’ if they were responsible for a patient’s care on a day-to-day basis and ‘covering’ if they were only covering on call. Other variables included admitting service and hospital length of stay.

Appropriateness Criteria

Criteria for potentially inappropriate use were modified from the American and Canadian Geriatrics Societies’ Choosing Wisely recommendations,^4,5 and included insomnia and agitation. These recommendations are in line with other evidence based guidelines for safe prescribing in older adults.²⁰ For the purposes of our study, prescriptions for “agitation/anxiety”, “agitation”, or “insomnia/sleep” were considered potentially inappropriate. Appropriate indications included alcohol withdrawal, end-of-life symptom control, preprocedural sedation, and seizure.⁵ Patients who were already using a BSH prior to admission for any indication, including a psychiatric diagnosis, were excluded.

Statistical Analyses

We determined the proportion of patients with at least one PIP, as well as the proportion of all prescribing events that were potentially inappropriate. We used the Chi-square statistic and 2-sample t tests to compare the unadjusted associations between patient-level characteristics and receipt of at least 1 inappropriate prescription and prescribing event-level factors with inappropriate prescriptions. Given that first-year residents are more likely to be working overnight when most PIPs are prescribed, we performed a simple logistic regression of potentially inappropriate prescribing by level of training stratified by time of prescription. A multivariable random-intercept logistic regression model was used to assess the adjusted association between patient- and prescribing event-level characteristics with inappropriate prescribing, adjusting for clustering of prescribing events within patients. Characteristics of interest were identified a priori and those with significant bivariate associations with potentially inappropriate were selected for inclusion in the model. Additionally, we included time of prescription in our model to control for potential confounding. All statistical analyses were performed using SAS 9.4 (SAS Institute Inc, Cary, North Carolina). The MSH Research Ethics Board approved the study.

Description of Patients Prescribed a Benzodiazepine Sedative Hypnotic

There were 1540 patients over the age of 65 discharged during the 4-month study period. We excluded the 232 patients who had been prescribed a BSH prior to admission. Of the remaining eligible 1308 BSH-naïve patients, 251 (19.2%) were prescribed a new BSH in hospital and were included in the study. Of this cohort of 251 patients, 193 (76.9%) patients were prescribed a single BSH during their admission while 58 (23.1%) received 2 or more. Of all eligible patients, 208 (15.9%) were prescribed at least 1 PIP. Approximately half of the cohort was admitted to the general internal medicine service, and the most common reason for admission was cardiovascular disease (Table 1).

Description of Prescriptions of Benzodiazepine Sedative Hypnotic

We reviewed 328 prescriptions for BSH during the study period. The majority of these, 254 (77.4%) were potentially inappropriate (Table 2). The most common PIPs were zopiclone (167; 65.7%) and lorazepam (82; 32.3%). The PIPs were most frequently ordered on an as-needed basis (219; 86%), followed by one-time orders (30; 12%), and standing orders (5; 2%). The majority of PIPs (222; 87.4%) was prescribed for insomnia with a minority (32; 12.6%) prescribed for agitation and/or anxiety.

Most PIP were prescribed during overnight hours (159; 62.6%) and when an in-house pharmacist was unavailable (211; 83.1%). These variables were highly correlated with prescription of sleep aid, which was defined in our criteria as potentially inappropriate. Copies of discharge prescriptions were available for 189 patients. Of these 189 patients, 19 (10.1%) were sent home with a prescription for a new sedative.

Association Between Patient/Provider Variables and Prescriptions

Patient factors associated with fewer PIPs in our bivariate analyses included older age and dementia (Table 1). A greater proportion of nighttime prescriptions were PIPs; however, this finding was not statistically significant (P = 0.067). The majority of all prescriptions was prescribed by residents in their first year of training (64.9%; Table 2), and there was a significant difference in rates of PIP across level of training (P = 0.0007). When stratified by time of prescription, there was no significant difference by level of training for nighttime prescriptions. Among daytime prescriptions, second-year residents and staff (attending physicians and fellows) were less likely to prescribe a PIP than first-year residents (odds ratio [OR], 0.24; 95% confidence interval [CI], 0.09-0.66 and OR, 0.39; 95% CI, 0.14-1.13, respectively; Table 3); however, the association between staff and first-years only approached statistical significance (P = 0.08). Interestingly, 20.4% of all PIPs were ordered routinely as part of an admission or postoperative order set.

In our regression model, admission to a specialty or surgical service, compared to the general internal medicine service, was associated with a significantly higher likelihood of a PIP (OR, 6.61; 95% CI, 2.70-16.17; Table 4). Additionally, compared to cardiovascular admission diagnoses, neoplastic admitting diagnoses were associated with a higher likelihood of a PIP (OR, 4.43; 95% CI, 1.23-15.95). Time of prescription was a significant predictor in our multivariable regression model with nighttime prescriptions having increased odds of a PIP (OR, 4.48; 95% CI, 2.21-9.06,). When comparing prescribers at the extremes of training, attending physicians and fellows were much less likely to prescribe a PIP compared to first-year residents (OR, 0.23; 95% CI, 0.08-0.69; Table 4). However, there were no other significant differences across training levels after adjusting for patient and prescribing event characteristics.

We found that the majority of newly prescribed BSH in hospital was for the potentially inappropriate indications of insomnia and agitation/anxiety. Medications for insomnia were primarily initiated during overnight hours. Training level of prescribers and admitting service were found to be associated with appropriateness of prescriptions.

Our study showed that 15.9% of hospitalized older adults were newly prescribed a PIP during their admission. Of all new in hospital prescriptions, 77% were deemed potentially inappropriate. These numbers are similar to those reported by other centers; however, wide ranges exist.^16,19 This is likely the result of differences in appropriate use and inclusion criteria. Gillis et al.¹⁷ focused their investigation on sleep aids and showed that 26% of all admitted patients and 18% of BSH naïve patients received a prescription for insomnia. While this is similar to our findings, more than half of these patients were under the age of 65, and additional medications, such as trazodone, antihistamines, and antipsychotics were included.¹⁷ Other studies did not exclude patients who used a BSH regularly prior to admission. For example, 21% of veterans admitted to an acute care facility received a prescription for potentially inappropriate indications, but this included continuation of prior home medications.¹⁹ In contrast, we chose to focus on older adults in whom BSH pose a greater risk of harm. Exclusion of patients who regularly used a BSH prior to admission allowed us to better understand the circumstances surrounding the initiation of these medications in hospital. Furthermore, abrupt cessation of benzodiazepines can cause withdrawal and worsen confusion.²²

We found that 10% of patients newly prescribed a BSH in hospital were discharged with a prescription for a BSH. The accuracy of this is limited by the lack of availability of electronic discharge prescriptions on our surgical wards; however, it is likely an underrepresentation of the true effect given the high rates of PIPs on these wards. Our study highlights the concerning practice of continuing newly prescribed BSH following discharge from hospital.

Sleep disruption and poor quality sleep in hospital is a common issue that leads to significant use of BSH.¹⁵ Nonpharmacologic interventions in older adults can be effective in improving sleep quality and reducing the need for BSH; however, they can be time-consuming to implement.²³ With the exception of preventative strategies used on our Acute Care for Elders unit, formal nonpharmacologic interventions for sleep are not practiced in our hospital. We found that the majority of PIPs were prescribed as sleep aids in the overnight hours. This suggests that disruptions in sleep are leading patients and nursing staff to request pharmacologic treatments and highlights an area with significant room for improvement. Work is underway to implement and evaluate safe sleep protocols for older adults.

To our knowledge, we are the first to report an association between training level and PIP of BSH in older adults. The highest rates of PIPs were found among the first-year residents and, after controlling for patient and prescribing event characteristics, such as time of prescription, first-year residents were significantly more likely to prescribe a PIP. First-year residents are more likely to respond first to issues on the wards. There may be pressure on first-year trainees to prescribe sleep aids, as many patients and nurses may seek pharmacologic solutions for symptom management. Knowledge gaps may also be a contributing factor early in their training. A survey of physicians found that residents were more likely than attending physicians to list lack of formal education as a barrier to appropriate prescribing.²⁴

Similarities are seen in a study of antibiotic appropriateness, where residents demonstrated gaps in knowledge of treatment of asymptomatic bacteriuria that seemed to vary by specialty.²⁵ Interestingly, we found that patients admitted to general internal medicine were prescribed fewer PIPs. This service includes our Acute Care for Elders unit, which is staffed by trained geriatric nurses and other allied health professionals. Residents who rotated on internal medicine are also likely to have received informal teaching about medication safety in older adults. Educational interventions highlighting adverse effects of BSH and promoting nonpharmacologic solutions should be targeted at first-year residents. However, an interprofessional team approach to sleep disturbance in hospital, in combination with decision support for appropriate BSH use will achieve greater impact than education alone.

Several limitations of this study merit discussion. First, findings from a single academic center may lack generalizability. However, the demographics of our patient population and our rates of BSH use were similar to those reported in previous studies. Second, our study may be subject to observer bias, as the data collectors were not blinded. To minimize this, a strict template and clear appropriateness criteria were developed. Additionally, a second reviewer independently conducted data validation with 100% agreement among reviewers. Third, we studied prescribing patterns rather than medication administration and lacked data on filling of new BSH prescriptions in the postdischarge period. However, our primary goal is to determine risk of exposure to a BSH to minimize it. Fourth, although BSH are discouraged as “first choice for insomnia, anxiety or delirium,”⁴ they may be appropriate in limited situations where all nonpharmacologic strategies have failed and patient or staff safety is at risk. In our chart reviews, we were unable to determine whether all nonpharmacologic strategies were exhausted prior to prescription initiation. However, more than 20% of all PIP were routinely prescribed as part of an admission or postoperative order set, suggesting a reflexive rather than reflective approach to sedative use. Furthermore, the indications of anxiety and agitation were combined as they appear in the CPOE as a combination indication, thus leaving us unable to determine the true proportion for each indication. However, more than 87% of all PIPs were for insomnia, reflecting a clear opportunity to improve sleep management in hospital. Last, the lack of a power calculation may have resulted in the study being underpowered and thus affected the ability to detect a significant effect of covariates that have real differences on the likelihood of sedative prescriptions. For example, the low number of prescribing events by second-year residents and staff may have resulted in a type II error when comparing PIP rates with first-year residents.

We found that the majority of newly prescribed BSH among older adults in hospital were potentially inappropriate. They were most frequently prescribed by first-year residents overnight in response to insomnia. Our findings demonstrate BSH overuse remains prevalent and is associated with poor sleep in hospital. Future work will focus on implementing and evaluating safe sleep protocols and educational interventions aimed at first-year residents.

Acknowledgments

Elisabeth Pek had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. Ciara Pendrith conducted and is responsible for the statistical analysis.

Disclosure

The authors report no financial conflicts of interest.

Older adults commonly experience insomnia and agitation during hospitalization. Unfortunately, the use of benzodiazepines and sedative hypnotics (BSH) to treat these conditions can be ineffective and expose patients to significant adverse effects.^1,2 Choosing Wisely^® is a campaign that promotes dialogue to reduce unnecessary medical tests, procedures, or treatments. This international campaign has highlighted BSHs as potentially harmful and has recommended against their use as first-line treatment of insomnia and agitation.^3-5 Examples of harm with benzodiazepine use include cognitive impairment, impaired postural stability, and an increased incidence of falls and hip fractures in both community and acute care settings.^6-8 In addition, prescriptions initiated in hospital appear to be associated with a higher risk of falls and unplanned readmission.^9,10 The newer nonbenzodiazepine sedative hypnotics, commonly referred to as “z-drugs”, were initially marketed as a safer alternative in older adults due to their more favorable pharmacokinetics. Evidence has emerged that they carry similar risks.^6,11,12 A study comparing benzodiazepines and zolpidem found relatively greater risk of fractures requiring hospitalization with the use of zolpidem compared to lorazepam.¹³

The use of benzodiazepines in the acute care setting has been evaluated in a number of studies and ranges from 20% to 45%.^14-16 Few studies focus on the initiation of these medications in BSH-naïve hospitalized patients; however, reports range from 18% to 29%.^17,18 Factors found to be associated with potentially inappropriate prescriptions (PIP) include Hispanic ethnicity, residing in an assisted care setting, and a greater number of BSH prescriptions prior to admission.^16,19 Additionally, Cumbler et al.¹⁵ found that the presence of dementia was associated with fewer prescriptions for sleep aids in hospital. To our knowledge, there are no published studies that have investigated prescriber factors associated with the use of BSH.

The purpose of our study was to determine the frequency of PIPs of BSH in our academic hospital. Additionally, we aimed to identify patient and prescriber factors that were associated with increased likelihood of prescriptions to help guide future quality improvement initiatives.

Study Design and Setting

This was a retrospective observational study conducted at Mount Sinai Hospital (MSH) in Toronto over a 4-month period from January 2013 to April 2013. The hospital is a 442-bed acute care academic health science center affiliated with the University of Toronto. The MSH electronic health record contains demographic data, medications and allergies, nursing documentation, and medical histories from prior encounters. It also includes computerized physician order entry (CPOE) and a detailed medication administration record. This system is integrated with an electronic pharmacy database used to monitor and dispense medications for each patient.

Patient and Medication Selection

We included inpatients over the age of 65 who were prescribed a BSH during the study period from the following services: general internal medicine, cardiology, general surgery, orthopedic surgery, and otolaryngology. To identify new exposure to BSHs, we excluded patients who were regularly prescribed a BSH prior to admission to hospital. The medications of interest included all benzodiazepines and the nonbenzodiazepine sedative hypnotic, zopiclone. Zopiclone is the most commonly used nonbenzodiazepine sedative hypnotic in Canada and the only 1 available on our hospital formulary. These were selected based on the strength of evidence to recommend against their use as first-line agents in older adults and in consultation with our geriatric medicine consultation team pharmacist.²⁰

Data Collection

The hospital administrative database provided patient demographic information, admission service, admitting diagnosis, length of stay, and the total number of patients discharged from the study units over the study period. We then searched the pharmacy electronic database for all benzodiazepines and zopiclone prescribed during the study period for patients who met the inclusion criteria. Manual review of paper and electronic health records for this cohort of patients was conducted to extract additional variables. We used a standardized form to record data elements. Dr. Pek collected all data elements. Dr. Remfry reviewed a random sample of patient records (10%) to ensure accuracy. The agreement between reviewers was 100%.

In compliance with hospital accreditation standards, a clinical pharmacist documents a best possible medication history (BPMH) on every inpatient on admission. We used the BPMH to identify and exclude patients who were prescribed a BSH prior to hospitalization. Because all medications were ordered through the CPOE system, as-needed medication prescriptions required the selection of a specified indication. Available options included ‘agitation/anxiety’ and necessitated combining these 2 indications into 1 category. Indications were primarily extracted through electronic order entry reviews. Paper charts were reviewed when further clarification was needed.

We identified ordering physicians’ training level and familiarity with the service from administrative records obtained from medical education offices, hospital records, and relevant call schedules. Fellows were defined as trainees with a minimum of 6 years of postgraduate training.

Our primary outcome of interest was the proportion of eligible patients age 65 and older who received a PIP for a BSH. Patient variables of interest included age, sex, comorbid conditions, and a pre-admission diagnosis of dementia. Comorbid conditions and age were used to calculate the Carlson Comorbidity Index for each patient.²¹ Prescription variables included the medication prescribed, time of first prescription (“overnight hours” refer to prescriptions ordered after 7:00 PM and before 7:00 AM), and whether the medication was ordered as part of an admission or postoperative order set. To determine whether patients were discharged home with a prescription for a BSH, we reviewed electronic discharge prescriptions of BSH-naïve patients who received a sedative in hospital. Only medical and cardiology inpatients receive electronic discharge prescriptions, and these were available for 189 patients in our cohort. Provider variables included training level, service, and familiarity with patients. We used the provider’s training program or department of appointment to define the ‘physician on-service’ variable. As an example, a resident registered in internal medicine is defined as ‘on-service’ when prescribing sedatives for a medical inpatient. In contrast, a psychiatry resident would be considered “off-service” if he prescribed a sedative for a surgical inpatient. The familiarity of a provider was categorized as ‘regular’ if they were responsible for a patient’s care on a day-to-day basis and ‘covering’ if they were only covering on call. Other variables included admitting service and hospital length of stay.

Appropriateness Criteria

Criteria for potentially inappropriate use were modified from the American and Canadian Geriatrics Societies’ Choosing Wisely recommendations,^4,5 and included insomnia and agitation. These recommendations are in line with other evidence based guidelines for safe prescribing in older adults.²⁰ For the purposes of our study, prescriptions for “agitation/anxiety”, “agitation”, or “insomnia/sleep” were considered potentially inappropriate. Appropriate indications included alcohol withdrawal, end-of-life symptom control, preprocedural sedation, and seizure.⁵ Patients who were already using a BSH prior to admission for any indication, including a psychiatric diagnosis, were excluded.

Statistical Analyses

We determined the proportion of patients with at least one PIP, as well as the proportion of all prescribing events that were potentially inappropriate. We used the Chi-square statistic and 2-sample t tests to compare the unadjusted associations between patient-level characteristics and receipt of at least 1 inappropriate prescription and prescribing event-level factors with inappropriate prescriptions. Given that first-year residents are more likely to be working overnight when most PIPs are prescribed, we performed a simple logistic regression of potentially inappropriate prescribing by level of training stratified by time of prescription. A multivariable random-intercept logistic regression model was used to assess the adjusted association between patient- and prescribing event-level characteristics with inappropriate prescribing, adjusting for clustering of prescribing events within patients. Characteristics of interest were identified a priori and those with significant bivariate associations with potentially inappropriate were selected for inclusion in the model. Additionally, we included time of prescription in our model to control for potential confounding. All statistical analyses were performed using SAS 9.4 (SAS Institute Inc, Cary, North Carolina). The MSH Research Ethics Board approved the study.

Description of Patients Prescribed a Benzodiazepine Sedative Hypnotic

There were 1540 patients over the age of 65 discharged during the 4-month study period. We excluded the 232 patients who had been prescribed a BSH prior to admission. Of the remaining eligible 1308 BSH-naïve patients, 251 (19.2%) were prescribed a new BSH in hospital and were included in the study. Of this cohort of 251 patients, 193 (76.9%) patients were prescribed a single BSH during their admission while 58 (23.1%) received 2 or more. Of all eligible patients, 208 (15.9%) were prescribed at least 1 PIP. Approximately half of the cohort was admitted to the general internal medicine service, and the most common reason for admission was cardiovascular disease (Table 1).

Description of Prescriptions of Benzodiazepine Sedative Hypnotic

We reviewed 328 prescriptions for BSH during the study period. The majority of these, 254 (77.4%) were potentially inappropriate (Table 2). The most common PIPs were zopiclone (167; 65.7%) and lorazepam (82; 32.3%). The PIPs were most frequently ordered on an as-needed basis (219; 86%), followed by one-time orders (30; 12%), and standing orders (5; 2%). The majority of PIPs (222; 87.4%) was prescribed for insomnia with a minority (32; 12.6%) prescribed for agitation and/or anxiety.

Most PIP were prescribed during overnight hours (159; 62.6%) and when an in-house pharmacist was unavailable (211; 83.1%). These variables were highly correlated with prescription of sleep aid, which was defined in our criteria as potentially inappropriate. Copies of discharge prescriptions were available for 189 patients. Of these 189 patients, 19 (10.1%) were sent home with a prescription for a new sedative.

Association Between Patient/Provider Variables and Prescriptions

Patient factors associated with fewer PIPs in our bivariate analyses included older age and dementia (Table 1). A greater proportion of nighttime prescriptions were PIPs; however, this finding was not statistically significant (P = 0.067). The majority of all prescriptions was prescribed by residents in their first year of training (64.9%; Table 2), and there was a significant difference in rates of PIP across level of training (P = 0.0007). When stratified by time of prescription, there was no significant difference by level of training for nighttime prescriptions. Among daytime prescriptions, second-year residents and staff (attending physicians and fellows) were less likely to prescribe a PIP than first-year residents (odds ratio [OR], 0.24; 95% confidence interval [CI], 0.09-0.66 and OR, 0.39; 95% CI, 0.14-1.13, respectively; Table 3); however, the association between staff and first-years only approached statistical significance (P = 0.08). Interestingly, 20.4% of all PIPs were ordered routinely as part of an admission or postoperative order set.

In our regression model, admission to a specialty or surgical service, compared to the general internal medicine service, was associated with a significantly higher likelihood of a PIP (OR, 6.61; 95% CI, 2.70-16.17; Table 4). Additionally, compared to cardiovascular admission diagnoses, neoplastic admitting diagnoses were associated with a higher likelihood of a PIP (OR, 4.43; 95% CI, 1.23-15.95). Time of prescription was a significant predictor in our multivariable regression model with nighttime prescriptions having increased odds of a PIP (OR, 4.48; 95% CI, 2.21-9.06,). When comparing prescribers at the extremes of training, attending physicians and fellows were much less likely to prescribe a PIP compared to first-year residents (OR, 0.23; 95% CI, 0.08-0.69; Table 4). However, there were no other significant differences across training levels after adjusting for patient and prescribing event characteristics.

We found that the majority of newly prescribed BSH in hospital was for the potentially inappropriate indications of insomnia and agitation/anxiety. Medications for insomnia were primarily initiated during overnight hours. Training level of prescribers and admitting service were found to be associated with appropriateness of prescriptions.

Our study showed that 15.9% of hospitalized older adults were newly prescribed a PIP during their admission. Of all new in hospital prescriptions, 77% were deemed potentially inappropriate. These numbers are similar to those reported by other centers; however, wide ranges exist.^16,19 This is likely the result of differences in appropriate use and inclusion criteria. Gillis et al.¹⁷ focused their investigation on sleep aids and showed that 26% of all admitted patients and 18% of BSH naïve patients received a prescription for insomnia. While this is similar to our findings, more than half of these patients were under the age of 65, and additional medications, such as trazodone, antihistamines, and antipsychotics were included.¹⁷ Other studies did not exclude patients who used a BSH regularly prior to admission. For example, 21% of veterans admitted to an acute care facility received a prescription for potentially inappropriate indications, but this included continuation of prior home medications.¹⁹ In contrast, we chose to focus on older adults in whom BSH pose a greater risk of harm. Exclusion of patients who regularly used a BSH prior to admission allowed us to better understand the circumstances surrounding the initiation of these medications in hospital. Furthermore, abrupt cessation of benzodiazepines can cause withdrawal and worsen confusion.²²

We found that 10% of patients newly prescribed a BSH in hospital were discharged with a prescription for a BSH. The accuracy of this is limited by the lack of availability of electronic discharge prescriptions on our surgical wards; however, it is likely an underrepresentation of the true effect given the high rates of PIPs on these wards. Our study highlights the concerning practice of continuing newly prescribed BSH following discharge from hospital.

Sleep disruption and poor quality sleep in hospital is a common issue that leads to significant use of BSH.¹⁵ Nonpharmacologic interventions in older adults can be effective in improving sleep quality and reducing the need for BSH; however, they can be time-consuming to implement.²³ With the exception of preventative strategies used on our Acute Care for Elders unit, formal nonpharmacologic interventions for sleep are not practiced in our hospital. We found that the majority of PIPs were prescribed as sleep aids in the overnight hours. This suggests that disruptions in sleep are leading patients and nursing staff to request pharmacologic treatments and highlights an area with significant room for improvement. Work is underway to implement and evaluate safe sleep protocols for older adults.

To our knowledge, we are the first to report an association between training level and PIP of BSH in older adults. The highest rates of PIPs were found among the first-year residents and, after controlling for patient and prescribing event characteristics, such as time of prescription, first-year residents were significantly more likely to prescribe a PIP. First-year residents are more likely to respond first to issues on the wards. There may be pressure on first-year trainees to prescribe sleep aids, as many patients and nurses may seek pharmacologic solutions for symptom management. Knowledge gaps may also be a contributing factor early in their training. A survey of physicians found that residents were more likely than attending physicians to list lack of formal education as a barrier to appropriate prescribing.²⁴

Similarities are seen in a study of antibiotic appropriateness, where residents demonstrated gaps in knowledge of treatment of asymptomatic bacteriuria that seemed to vary by specialty.²⁵ Interestingly, we found that patients admitted to general internal medicine were prescribed fewer PIPs. This service includes our Acute Care for Elders unit, which is staffed by trained geriatric nurses and other allied health professionals. Residents who rotated on internal medicine are also likely to have received informal teaching about medication safety in older adults. Educational interventions highlighting adverse effects of BSH and promoting nonpharmacologic solutions should be targeted at first-year residents. However, an interprofessional team approach to sleep disturbance in hospital, in combination with decision support for appropriate BSH use will achieve greater impact than education alone.

Several limitations of this study merit discussion. First, findings from a single academic center may lack generalizability. However, the demographics of our patient population and our rates of BSH use were similar to those reported in previous studies. Second, our study may be subject to observer bias, as the data collectors were not blinded. To minimize this, a strict template and clear appropriateness criteria were developed. Additionally, a second reviewer independently conducted data validation with 100% agreement among reviewers. Third, we studied prescribing patterns rather than medication administration and lacked data on filling of new BSH prescriptions in the postdischarge period. However, our primary goal is to determine risk of exposure to a BSH to minimize it. Fourth, although BSH are discouraged as “first choice for insomnia, anxiety or delirium,”⁴ they may be appropriate in limited situations where all nonpharmacologic strategies have failed and patient or staff safety is at risk. In our chart reviews, we were unable to determine whether all nonpharmacologic strategies were exhausted prior to prescription initiation. However, more than 20% of all PIP were routinely prescribed as part of an admission or postoperative order set, suggesting a reflexive rather than reflective approach to sedative use. Furthermore, the indications of anxiety and agitation were combined as they appear in the CPOE as a combination indication, thus leaving us unable to determine the true proportion for each indication. However, more than 87% of all PIPs were for insomnia, reflecting a clear opportunity to improve sleep management in hospital. Last, the lack of a power calculation may have resulted in the study being underpowered and thus affected the ability to detect a significant effect of covariates that have real differences on the likelihood of sedative prescriptions. For example, the low number of prescribing events by second-year residents and staff may have resulted in a type II error when comparing PIP rates with first-year residents.

We found that the majority of newly prescribed BSH among older adults in hospital were potentially inappropriate. They were most frequently prescribed by first-year residents overnight in response to insomnia. Our findings demonstrate BSH overuse remains prevalent and is associated with poor sleep in hospital. Future work will focus on implementing and evaluating safe sleep protocols and educational interventions aimed at first-year residents.

Acknowledgments

Elisabeth Pek had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. Ciara Pendrith conducted and is responsible for the statistical analysis.

Disclosure

The authors report no financial conflicts of interest.