Victoria Valencia, MPH

The COVID-19 pandemic posed an unprecedented challenge to our current healthcare system—how to efficiently develop and standardize care for a disease process yet to be fully characterized while continuing to deliver high-value care. In the United States, many local institutions developed their own practice patterns, resulting in wide variation.

The Society of Hospital Medicine’s Choosing Wisely^® recommendations include avoiding repetitive routine laboratory testing.¹In the setting of the early stages of the COVID-19 pandemic (particularly before vaccines were broadly available), the benefits of avoiding routine repetitive testing may have been more pronounced considering the need to limit unnecessary healthcare professional exposure to infected individuals and to conserve resources, including personal protective equipment (PPE) and laboratory resources.²

In April 2020, at Dell Seton Medical Center (DSMC) at the University of Texas at Austin, we created a Therapeutics and Informatics Committee to critically review evidence-based practices, reach consensus, and guide practice patterns, with the aim of delivering high-value care. This brief report aims to evaluate the effectiveness of standardized electronic health record (EHR) order sets in appropriately decreasing lab testing for non-critically-ill hospitalized COVID-19 patients.

Study Design and Setting

We followed SQUIRE guidelines for reporting this quality improvement intervention.³ Using retrospective chart review, we analyzed laboratory ordering patterns for COVID-positive patients at a single safety net academic medical center in Austin, Texas. Data were abstracted using a custom SQL query of our EHR and de-identified for this analysis. Our internal review board determined that this project is a quality improvement project and did not meet the criteria of human subjects research.

Study Population

All adult (age ≥18 years), non-intensive care unit (ICU), COVID-positive patients with an observation or inpatient status discharged between March 30, 2020, and March 7, 2021, were included in the analysis. Patients were excluded if they were ever transferred to an ICU. COVID-positive status was confirmed via a positive polymerase chain reaction (PCR) test for SARS-CoV-2.

Intervention

In April 2020, we created a Therapeutics and Informatics Committee, an interprofessional group including hospitalists, infectious disease, pulmonary and critical care, pharmacy, hospital leadership, and other subspecialists, to iteratively evaluate evidence and standardize inpatient care. This committee was created in response to the COVID-19 pandemic and has been uniquely focused on COVID-19-related care.

On April 30, 2020, the committee met to evaluate routine laboratory tests in patients with COVID-19. Prior to this meeting, there was a clinical order set (Cerner “powerplan”) in the EHR that included daily laboratory tests, and individual provider ordering practices were heterogeneous, with a strong predilection for ordering an array of inflammatory markers with unclear clinical benefit and high cost. The committee’s consensus recommendation at that meeting was that patients admitted to the floor did not require routine daily laboratory tests. Complete blood count (CBC), complete metabolic panel (CMP), D-dimer, and troponin were among the labs recommended to be obtained no more frequently than every other day. The committee believed that reducing unnecessary labs would improve value without compromising patient care. These lab ordering practices were incorporated into a customized COVID-19 EHR order set that could be shared among providers, but are not discoverable using the search feature until they are formally built by the informatics team. Changes to the order sets were communicated through multiple platforms and widely adopted by frontline providers.

The committee revisited laboratory ordering practices on June 25, 2020, making the recommendation to further discontinue trending troponin levels and reduce the amount of baseline labs, as they were contributing little to the clinical gestalt or changing management decisions. The customized EHR order sets were updated to reflect the new recommendations, and providers were encouraged to adopt them.

Although direct feedback on ordering practices can be an effective component of a multipronged intervention for decreasing lab usage,⁴ in this particular case we did not provide feedback to physicians related to their lab usage for COVID-19 care. We provided education to all physicians following each local COVID management consensus guideline change through email, handbook-style updates, and occasional conferences.

Measures and Analysis

The main process measure for this study was the mean hospitalization-level proportion of calendar hospital days with at least one laboratory result for each of four separate lab types: white blood cell count (WBC, as a marker for CBC), creatinine (as a marker for chemistry panels), troponin-I, and D-dimer. First, individual hospitalization-level proportions were calculated for each patient and each lab type. For example, if a patient with a length of stay of 5 calendar days had a WBC measured 2 of those days, their WBC proportion was 0.4. Then we calculated the mean of these proportions for all patients discharged in a given week during the study period for each lab type. Using this measure allowed us to understand the cadence of lab ordering and whether labs were checked daily.

Mean daily lab proportions were plotted separately for CBC, chemistry panel, troponin I, and D-dimer on statistical process control (SPC) charts. The baseline period used for all SPC charts included the calendar weeks March 30, 2020, through June 1, 2020. The Montgomery rules were used for determining periods of special cause variation.

A total of 1,402 non-ICU COVID-positive patients were discharged between March 30, 2020, and March 7, 2021, from our hospital, with a median length of stay of 3.00 days (weekly discharge data are shown in the Figure). The majority of patients were Hispanic men, with a mean age of 54 years (Appendix Table).

To assess intervention fidelity of the order sets, we performed two random spot checks (on May 15, 2020, and June 2, 2020) and found that 16/18 (89%) and 21/25 (84%) of COVID admissions had used the customized order set, supporting robust uptake of the order set intervention.

Mean daily lab proportions for each of the four lab types—chemistry panels, CBCs, D-dimer, and troponin—all demonstrated special cause variation starting mid June to early July 2020 (Figure). All four charts demonstrated periods of four points below 1-sigma and eight points below the center line, with troponin and D-dimer also demonstrating periods of two points below 2-sigma and one point below the lower control limit. These periods of special cause variation were sustained through February 2021. This represents a significant increase in the number of days that these hospitalized patients did not have these labs drawn.

We evaluated the proportion of all COVID-19 patients who spent time in the ICU over the entire study period, which remained consistent at approximately 25% of our hospitalized COVID-19 population. On a SPC chart, there was no evidence of change in ICU patients following our intervention.

Non-critically-ill COVID-19 patients at our hospital had more inpatient days where they did not receive specific laboratory tests following the introduction of locally developed, standardized recommendations and an electronic order set. These data show sustainability and endurance of this intervention through both our summer and winter surges, and the association did not correlate directly with significant changes in the number of COVID-19 patient discharges, supporting that its impact is independent of case volume.

Whereas Choosing Wisely^® recommendations have been traditionally based on well-established common areas of overuse, this example is unique in showing how these same underlying principles can be applied even in unclear situations, such as with the COVID-19 pandemic. Through multidisciplinary review of real-time evidence and accumulating local experience, the Therapeutics and Informatics Committee at our hospital was able to reach consensus and rapidly deploy an electronic order set that was widely adopted. Eventually, the order set was formally adopted into our EHR; however, the customized COVID-19 order set allowed rapid improvement and implementation of changes that could be shared among providers. As confirmed by our spot checks, this order set was widely used. The order set bolstered the effect of our Therapeutics and Informatics Committee, which served as our platform to disseminate consensus recommendations and build them into clinical workflows.

There are several limitations to this brief analysis. First, we were unable to assess patient outcomes in response to these changes, mostly due to multiple confounding variables throughout this time period with rapidly shifting census numbers, and the adoption of therapeutic interventions, such as the introduction of dexamethasone, which has shown a mortality benefit for patients with COVID-19. However, we have no reason to believe that this decrease in routine laboratory ordering was associated with adverse outcomes for our patients, and, in aggregate, the outcomes (eg, mortality, length of stay, readmissions) for COVID-19 patients at our hospital have been better than average across Vizient peer groups.⁶ Prior studies have shown that reduced inpatient labs do not have an adverse impact on patient outcomes.⁷ Furthermore, non-ICU COVID-19 is generally a single-organ disease (unlike patients with critical illness from COVID-19), making it more likely that daily labs are unnecessary in this specific patient population. There was no increase in the proportion of COVID-19 ICU patients following our intervention.

In conclusion, the principles of Choosing Wisely^® can be applied even within novel and quickly evolving situations, relying on rapid and critical review of evidence, clinician consensus-building, and leveraging available interventions to drive behavior change, such as shared order sets.

The COVID-19 pandemic posed an unprecedented challenge to our current healthcare system—how to efficiently develop and standardize care for a disease process yet to be fully characterized while continuing to deliver high-value care. In the United States, many local institutions developed their own practice patterns, resulting in wide variation.

The Society of Hospital Medicine’s Choosing Wisely^® recommendations include avoiding repetitive routine laboratory testing.¹In the setting of the early stages of the COVID-19 pandemic (particularly before vaccines were broadly available), the benefits of avoiding routine repetitive testing may have been more pronounced considering the need to limit unnecessary healthcare professional exposure to infected individuals and to conserve resources, including personal protective equipment (PPE) and laboratory resources.²

In April 2020, at Dell Seton Medical Center (DSMC) at the University of Texas at Austin, we created a Therapeutics and Informatics Committee to critically review evidence-based practices, reach consensus, and guide practice patterns, with the aim of delivering high-value care. This brief report aims to evaluate the effectiveness of standardized electronic health record (EHR) order sets in appropriately decreasing lab testing for non-critically-ill hospitalized COVID-19 patients.

Study Design and Setting

We followed SQUIRE guidelines for reporting this quality improvement intervention.³ Using retrospective chart review, we analyzed laboratory ordering patterns for COVID-positive patients at a single safety net academic medical center in Austin, Texas. Data were abstracted using a custom SQL query of our EHR and de-identified for this analysis. Our internal review board determined that this project is a quality improvement project and did not meet the criteria of human subjects research.

Study Population

All adult (age ≥18 years), non-intensive care unit (ICU), COVID-positive patients with an observation or inpatient status discharged between March 30, 2020, and March 7, 2021, were included in the analysis. Patients were excluded if they were ever transferred to an ICU. COVID-positive status was confirmed via a positive polymerase chain reaction (PCR) test for SARS-CoV-2.

Intervention

In April 2020, we created a Therapeutics and Informatics Committee, an interprofessional group including hospitalists, infectious disease, pulmonary and critical care, pharmacy, hospital leadership, and other subspecialists, to iteratively evaluate evidence and standardize inpatient care. This committee was created in response to the COVID-19 pandemic and has been uniquely focused on COVID-19-related care.

On April 30, 2020, the committee met to evaluate routine laboratory tests in patients with COVID-19. Prior to this meeting, there was a clinical order set (Cerner “powerplan”) in the EHR that included daily laboratory tests, and individual provider ordering practices were heterogeneous, with a strong predilection for ordering an array of inflammatory markers with unclear clinical benefit and high cost. The committee’s consensus recommendation at that meeting was that patients admitted to the floor did not require routine daily laboratory tests. Complete blood count (CBC), complete metabolic panel (CMP), D-dimer, and troponin were among the labs recommended to be obtained no more frequently than every other day. The committee believed that reducing unnecessary labs would improve value without compromising patient care. These lab ordering practices were incorporated into a customized COVID-19 EHR order set that could be shared among providers, but are not discoverable using the search feature until they are formally built by the informatics team. Changes to the order sets were communicated through multiple platforms and widely adopted by frontline providers.

The committee revisited laboratory ordering practices on June 25, 2020, making the recommendation to further discontinue trending troponin levels and reduce the amount of baseline labs, as they were contributing little to the clinical gestalt or changing management decisions. The customized EHR order sets were updated to reflect the new recommendations, and providers were encouraged to adopt them.

Although direct feedback on ordering practices can be an effective component of a multipronged intervention for decreasing lab usage,⁴ in this particular case we did not provide feedback to physicians related to their lab usage for COVID-19 care. We provided education to all physicians following each local COVID management consensus guideline change through email, handbook-style updates, and occasional conferences.

Measures and Analysis

The main process measure for this study was the mean hospitalization-level proportion of calendar hospital days with at least one laboratory result for each of four separate lab types: white blood cell count (WBC, as a marker for CBC), creatinine (as a marker for chemistry panels), troponin-I, and D-dimer. First, individual hospitalization-level proportions were calculated for each patient and each lab type. For example, if a patient with a length of stay of 5 calendar days had a WBC measured 2 of those days, their WBC proportion was 0.4. Then we calculated the mean of these proportions for all patients discharged in a given week during the study period for each lab type. Using this measure allowed us to understand the cadence of lab ordering and whether labs were checked daily.

Mean daily lab proportions were plotted separately for CBC, chemistry panel, troponin I, and D-dimer on statistical process control (SPC) charts. The baseline period used for all SPC charts included the calendar weeks March 30, 2020, through June 1, 2020. The Montgomery rules were used for determining periods of special cause variation.

A total of 1,402 non-ICU COVID-positive patients were discharged between March 30, 2020, and March 7, 2021, from our hospital, with a median length of stay of 3.00 days (weekly discharge data are shown in the Figure). The majority of patients were Hispanic men, with a mean age of 54 years (Appendix Table).

To assess intervention fidelity of the order sets, we performed two random spot checks (on May 15, 2020, and June 2, 2020) and found that 16/18 (89%) and 21/25 (84%) of COVID admissions had used the customized order set, supporting robust uptake of the order set intervention.

Mean daily lab proportions for each of the four lab types—chemistry panels, CBCs, D-dimer, and troponin—all demonstrated special cause variation starting mid June to early July 2020 (Figure). All four charts demonstrated periods of four points below 1-sigma and eight points below the center line, with troponin and D-dimer also demonstrating periods of two points below 2-sigma and one point below the lower control limit. These periods of special cause variation were sustained through February 2021. This represents a significant increase in the number of days that these hospitalized patients did not have these labs drawn.

We evaluated the proportion of all COVID-19 patients who spent time in the ICU over the entire study period, which remained consistent at approximately 25% of our hospitalized COVID-19 population. On a SPC chart, there was no evidence of change in ICU patients following our intervention.

Non-critically-ill COVID-19 patients at our hospital had more inpatient days where they did not receive specific laboratory tests following the introduction of locally developed, standardized recommendations and an electronic order set. These data show sustainability and endurance of this intervention through both our summer and winter surges, and the association did not correlate directly with significant changes in the number of COVID-19 patient discharges, supporting that its impact is independent of case volume.

Whereas Choosing Wisely^® recommendations have been traditionally based on well-established common areas of overuse, this example is unique in showing how these same underlying principles can be applied even in unclear situations, such as with the COVID-19 pandemic. Through multidisciplinary review of real-time evidence and accumulating local experience, the Therapeutics and Informatics Committee at our hospital was able to reach consensus and rapidly deploy an electronic order set that was widely adopted. Eventually, the order set was formally adopted into our EHR; however, the customized COVID-19 order set allowed rapid improvement and implementation of changes that could be shared among providers. As confirmed by our spot checks, this order set was widely used. The order set bolstered the effect of our Therapeutics and Informatics Committee, which served as our platform to disseminate consensus recommendations and build them into clinical workflows.

There are several limitations to this brief analysis. First, we were unable to assess patient outcomes in response to these changes, mostly due to multiple confounding variables throughout this time period with rapidly shifting census numbers, and the adoption of therapeutic interventions, such as the introduction of dexamethasone, which has shown a mortality benefit for patients with COVID-19. However, we have no reason to believe that this decrease in routine laboratory ordering was associated with adverse outcomes for our patients, and, in aggregate, the outcomes (eg, mortality, length of stay, readmissions) for COVID-19 patients at our hospital have been better than average across Vizient peer groups.⁶ Prior studies have shown that reduced inpatient labs do not have an adverse impact on patient outcomes.⁷ Furthermore, non-ICU COVID-19 is generally a single-organ disease (unlike patients with critical illness from COVID-19), making it more likely that daily labs are unnecessary in this specific patient population. There was no increase in the proportion of COVID-19 ICU patients following our intervention.

In conclusion, the principles of Choosing Wisely^® can be applied even within novel and quickly evolving situations, relying on rapid and critical review of evidence, clinician consensus-building, and leveraging available interventions to drive behavior change, such as shared order sets.

The COVID-19 pandemic posed an unprecedented challenge to our current healthcare system—how to efficiently develop and standardize care for a disease process yet to be fully characterized while continuing to deliver high-value care. In the United States, many local institutions developed their own practice patterns, resulting in wide variation.

The Society of Hospital Medicine’s Choosing Wisely^® recommendations include avoiding repetitive routine laboratory testing.¹In the setting of the early stages of the COVID-19 pandemic (particularly before vaccines were broadly available), the benefits of avoiding routine repetitive testing may have been more pronounced considering the need to limit unnecessary healthcare professional exposure to infected individuals and to conserve resources, including personal protective equipment (PPE) and laboratory resources.²

In April 2020, at Dell Seton Medical Center (DSMC) at the University of Texas at Austin, we created a Therapeutics and Informatics Committee to critically review evidence-based practices, reach consensus, and guide practice patterns, with the aim of delivering high-value care. This brief report aims to evaluate the effectiveness of standardized electronic health record (EHR) order sets in appropriately decreasing lab testing for non-critically-ill hospitalized COVID-19 patients.

Study Design and Setting

We followed SQUIRE guidelines for reporting this quality improvement intervention.³ Using retrospective chart review, we analyzed laboratory ordering patterns for COVID-positive patients at a single safety net academic medical center in Austin, Texas. Data were abstracted using a custom SQL query of our EHR and de-identified for this analysis. Our internal review board determined that this project is a quality improvement project and did not meet the criteria of human subjects research.

Study Population

All adult (age ≥18 years), non-intensive care unit (ICU), COVID-positive patients with an observation or inpatient status discharged between March 30, 2020, and March 7, 2021, were included in the analysis. Patients were excluded if they were ever transferred to an ICU. COVID-positive status was confirmed via a positive polymerase chain reaction (PCR) test for SARS-CoV-2.

Intervention

In April 2020, we created a Therapeutics and Informatics Committee, an interprofessional group including hospitalists, infectious disease, pulmonary and critical care, pharmacy, hospital leadership, and other subspecialists, to iteratively evaluate evidence and standardize inpatient care. This committee was created in response to the COVID-19 pandemic and has been uniquely focused on COVID-19-related care.

On April 30, 2020, the committee met to evaluate routine laboratory tests in patients with COVID-19. Prior to this meeting, there was a clinical order set (Cerner “powerplan”) in the EHR that included daily laboratory tests, and individual provider ordering practices were heterogeneous, with a strong predilection for ordering an array of inflammatory markers with unclear clinical benefit and high cost. The committee’s consensus recommendation at that meeting was that patients admitted to the floor did not require routine daily laboratory tests. Complete blood count (CBC), complete metabolic panel (CMP), D-dimer, and troponin were among the labs recommended to be obtained no more frequently than every other day. The committee believed that reducing unnecessary labs would improve value without compromising patient care. These lab ordering practices were incorporated into a customized COVID-19 EHR order set that could be shared among providers, but are not discoverable using the search feature until they are formally built by the informatics team. Changes to the order sets were communicated through multiple platforms and widely adopted by frontline providers.

The committee revisited laboratory ordering practices on June 25, 2020, making the recommendation to further discontinue trending troponin levels and reduce the amount of baseline labs, as they were contributing little to the clinical gestalt or changing management decisions. The customized EHR order sets were updated to reflect the new recommendations, and providers were encouraged to adopt them.

Although direct feedback on ordering practices can be an effective component of a multipronged intervention for decreasing lab usage,⁴ in this particular case we did not provide feedback to physicians related to their lab usage for COVID-19 care. We provided education to all physicians following each local COVID management consensus guideline change through email, handbook-style updates, and occasional conferences.

Measures and Analysis

The main process measure for this study was the mean hospitalization-level proportion of calendar hospital days with at least one laboratory result for each of four separate lab types: white blood cell count (WBC, as a marker for CBC), creatinine (as a marker for chemistry panels), troponin-I, and D-dimer. First, individual hospitalization-level proportions were calculated for each patient and each lab type. For example, if a patient with a length of stay of 5 calendar days had a WBC measured 2 of those days, their WBC proportion was 0.4. Then we calculated the mean of these proportions for all patients discharged in a given week during the study period for each lab type. Using this measure allowed us to understand the cadence of lab ordering and whether labs were checked daily.

Mean daily lab proportions were plotted separately for CBC, chemistry panel, troponin I, and D-dimer on statistical process control (SPC) charts. The baseline period used for all SPC charts included the calendar weeks March 30, 2020, through June 1, 2020. The Montgomery rules were used for determining periods of special cause variation.

A total of 1,402 non-ICU COVID-positive patients were discharged between March 30, 2020, and March 7, 2021, from our hospital, with a median length of stay of 3.00 days (weekly discharge data are shown in the Figure). The majority of patients were Hispanic men, with a mean age of 54 years (Appendix Table).

To assess intervention fidelity of the order sets, we performed two random spot checks (on May 15, 2020, and June 2, 2020) and found that 16/18 (89%) and 21/25 (84%) of COVID admissions had used the customized order set, supporting robust uptake of the order set intervention.

Mean daily lab proportions for each of the four lab types—chemistry panels, CBCs, D-dimer, and troponin—all demonstrated special cause variation starting mid June to early July 2020 (Figure). All four charts demonstrated periods of four points below 1-sigma and eight points below the center line, with troponin and D-dimer also demonstrating periods of two points below 2-sigma and one point below the lower control limit. These periods of special cause variation were sustained through February 2021. This represents a significant increase in the number of days that these hospitalized patients did not have these labs drawn.

We evaluated the proportion of all COVID-19 patients who spent time in the ICU over the entire study period, which remained consistent at approximately 25% of our hospitalized COVID-19 population. On a SPC chart, there was no evidence of change in ICU patients following our intervention.

Non-critically-ill COVID-19 patients at our hospital had more inpatient days where they did not receive specific laboratory tests following the introduction of locally developed, standardized recommendations and an electronic order set. These data show sustainability and endurance of this intervention through both our summer and winter surges, and the association did not correlate directly with significant changes in the number of COVID-19 patient discharges, supporting that its impact is independent of case volume.

Whereas Choosing Wisely^® recommendations have been traditionally based on well-established common areas of overuse, this example is unique in showing how these same underlying principles can be applied even in unclear situations, such as with the COVID-19 pandemic. Through multidisciplinary review of real-time evidence and accumulating local experience, the Therapeutics and Informatics Committee at our hospital was able to reach consensus and rapidly deploy an electronic order set that was widely adopted. Eventually, the order set was formally adopted into our EHR; however, the customized COVID-19 order set allowed rapid improvement and implementation of changes that could be shared among providers. As confirmed by our spot checks, this order set was widely used. The order set bolstered the effect of our Therapeutics and Informatics Committee, which served as our platform to disseminate consensus recommendations and build them into clinical workflows.

There are several limitations to this brief analysis. First, we were unable to assess patient outcomes in response to these changes, mostly due to multiple confounding variables throughout this time period with rapidly shifting census numbers, and the adoption of therapeutic interventions, such as the introduction of dexamethasone, which has shown a mortality benefit for patients with COVID-19. However, we have no reason to believe that this decrease in routine laboratory ordering was associated with adverse outcomes for our patients, and, in aggregate, the outcomes (eg, mortality, length of stay, readmissions) for COVID-19 patients at our hospital have been better than average across Vizient peer groups.⁶ Prior studies have shown that reduced inpatient labs do not have an adverse impact on patient outcomes.⁷ Furthermore, non-ICU COVID-19 is generally a single-organ disease (unlike patients with critical illness from COVID-19), making it more likely that daily labs are unnecessary in this specific patient population. There was no increase in the proportion of COVID-19 ICU patients following our intervention.

In conclusion, the principles of Choosing Wisely^® can be applied even within novel and quickly evolving situations, relying on rapid and critical review of evidence, clinician consensus-building, and leveraging available interventions to drive behavior change, such as shared order sets.

Hospitalizations related to opioid use disorder (OUD) have increased and now account for up to 6% of hospital admissions in certain areas of the United States.¹ Patients with OUD who are started on buprenorphine during hospitalization are more likely to enter outpatient treatment, stay in treatment longer, and have more drug-free days compared with patients who only receive a referral for outpatient treatment.^2,3 Therefore, a crucial comprehensive strategy for OUD care should include hospital-based programs that support initiation of treatment in the inpatient setting and strong bridges to outpatient care. One of the common barriers to initiating treatment in the inpatient setting, however, is a lack of access to addiction medicine specialists.^4-6

In 2017, we created a hospitalist-led interprofessional team called the B-Team (Buprenorphine Team) to help primary care teams identify patients with OUD, initiate and maintain buprenorphine therapy during hospitalization, provide warm handoffs to outpatient treatment programs, and reduce institutional stigma related to people with substance use disorders.

Program Description

The B-Team is led by a hospital medicine physician assistant and includes physicians from internal medicine, consult-liaison psychiatry, and palliative care; advanced practice and bedside nurses; a social worker; a pharmacist; a chaplain; a peer-recovery specialist; and medical trainees. The B-Team is notified of potential candidates for buprenorphine through a secure texting platform, one that is accessible to any healthcare provider at the hospital. Patients who are referred to the B-Team either self-identify or are identified by their primary team as having an underlying OUD. One of the B-Team providers assesses the patient to determine if they are eligible to receive inpatient therapy. Patients are considered eligible for the program if they meet Diagnostic and Statistical Manual of Mental Disorders (5th edition) criteria for OUD, have a desire to cease opioid use, and receive medical clearance to take buprenorphine.

For eligible patients, the B-Team provider orders a nurse-driven protocol to initiate buprenorphine for OUD. The chaplain offers psychospiritual counseling, and the social worker provides counseling and coordination of care. The B-Team partners with a nonhospital-affiliated, publicly-funded, office-based opioid treatment (OBOT) program that combines primary care with behavioral health programming. A follow-up outpatient appointment is secured prior to hospital discharge, and a member of the B-Team who has Drug Addiction Treatment Act of 2000 (DATA 2000) X-waiver certification prescribes buprenorphine as a bridge until the follow-up appointment. The medication is dispensed from the hospital’s retail pharmacy, and the patient leaves the hospital with the medication in-hand.

Patients who are not eligible for buprenorphine therapy are offered a harm-reduction intervention or referral to the psychiatry consult liaison service to assess for alternative diagnoses or treatment. These patients are also offered psychospiritual counseling and a prescription for naloxone.

Prior to the creation of the B-Team at our hospital, there was no structure in place to facilitate initiation of buprenorphine therapy during hospitalization and no linkage to outpatient treatment after discharge; furthermore, none of the hospitalists or other providers (including consulting psychiatrists) had an X-waiver to prescribe buprenorphine for OUD.

Program Evaluation

Study data were collected using Research Electronic Data Capture software. Inpatient and outpatient data were entered by a B-Team provider or a researcher via chart review. Patients were considered to be engaged in care if they attended at least one outpatient appointment for buprenorphine therapy during each of the following time periods: (1) 0 to 27 days (initial follow-up), 28-89 days (1- to 3-month follow-up), 90-179 days (3- to 6-month follow-up), and 180 days or more (>6-month follow-up). Only visits specifically for buprenorphine maintenance therapy were counted. If multiple encounters occurred within one time frame, the encounter closest to 0, 30, 90, or 180 days from discharge was used. If a patient did not attend any encounters during a specified time frame, they were considered to no longer be engaged in care and were no longer tracked for purposes of the evaluation. Data for the percentage of patients engaged in outpatient care are presented as the number of patients who attended at least one appointment during each of the follow-up periods (1 to 3 months, 3 to 6 months, or after 6 months, as noted above) divided by the number of patients who had been discharged with coordinated follow-up.

The number of patients admitted per month for whom there was an order to initiate inpatient buprenorphine therapy was analyzed using a statistical process control chart, in addition to the number of OUD admissions based on the inclusion of the International Classification of Disease, Tenth Revision (ICD-10) F11 code (opioid-related disorders) in any position in the discharge diagnoses.

This program and study were considered quality improvement by The University of Texas Institutional Review Board and did not meet criteria for human subjects research.

RESULTS

During the first 2 years of the program (September 2018-September 2020), the B-Team received 260 patient referrals. Most of the patients were White (72%), male (62%), and between ages 25 and 44 years (53%) (Appendix Table). The team initiated buprenorphine therapy in 132 hospitalized patients. In the year prior to the creation of the B-Team program, the average number of hospitalized patients receiving buprenorphine for OUD per month was three; after the launch of the B-Team program, this number increased to 12 encounters per month (Figure 1A). The sudden decrease observed in August 2020 is likely related to a surge in COVID-19 admissions. The number of monthly admissions for OUD is also shown (Figure 1B).

The B-Team saw a total of 132 eligible patients; members of the team provided counseling, support, and resources regarding buprenorphine therapy. In addition, the B-Team’s chaplain provided emotional support and spiritual connection (if desired) to 40 of these patients (30%). In the study, no cases of precipitated withdrawal were identified. Of the 132 patients seen, 110 (83%) were accepted to an outpatient OUD program upon discharge from the hospital; 98 (89%) of these patients were accepted at our partner OBOT clinic. The remaining patients were not interested in continuing OUD treatment (13%) or were denied acceptance to an outpatient program based on administrative and/or financial eligibility guidelines (4%). Patients who would not be attending an outpatient program were discontinued on buprenorphine therapy prior to discharge, counseled about naloxone, and provided printed resources.

Outpatient appointment attendance was used to measure ongoing treatment engagement of the 110 patients who were discharged with coordinated follow-up care. A total of 65 patients (59%) attended their first outpatient appointment; the average time between discharge and the first outpatient appointment was 5.9 days. Forty-two patients (38%) attended at least one appointment between 1 and 3 months; 29 (26%) between 3 and 6 months; and 24 (22%) after 6 months (Figure 2).

Of the 128 patients who were not administered buprenorphine therapy, 64 (50%) were not interested in starting treatment and/or were not ready to engage in treatment; 36 (28%) did not meet criteria for OUD treatment; 28 (22%) were already receiving treatment or preferred another type of OUD treatment; and 13 (10%) had severe comorbid addiction and/or illness requiring treatment that contraindicates the use of buprenorphine.

A volunteer hospitalist-led interprofessional team providing evidence-based care for hospitalized patients with OUD was associated with a substantial increase in patients receiving buprenorphine therapy—both during hospitalization and after discharge. In the program, 59% of patients attended initial follow-up appointments, and 22% of patients were still engaged at 6 months. These outpatient follow-up rates appear to be similar to, or higher than, other programs described in the literature. For example, a buprenorphine OUD-treatment initiative led by the psychiatry consult service at a Boston academic medical center resulted in less than half of patients receiving buprenorphine treatment within 2 months of discharge.⁷ In another study wherein an addiction medicine consult service administered buprenorphine to patients with OUD during hospitalization, 39%, 27%, and 18% of patients were retained in outpatient treatment at 30, 90, and 180 days, respectively.⁸

The B-Team model is likely generalizable to other hospital medicine groups that may not otherwise have access to inpatient care for substance use disorder. The B-Team is not an addiction medicine consultation service; rather, it is a hospitalist-led quality improvement initiative seeking to improve the standard of care for hospitalized patients with OUD.

A significant barrier is ensuring ongoing support for patients with OUD after discharge. In the B-Team program, a parallel OBOT program was created by a local nonaffiliated federally qualified health center. Although 89% of patients received treatment at this OBOT clinic, the inpatient team also has relationships with other local treatment centers, including programs that provide methadone. Another important barrier to high-quality outpatient care for OUD is the requirement of an X-waiver. To help overcome this barrier, our inpatient program partnered with a regional medical society to offer periodic X-waiver training to outpatient providers. In less than a year, more than 100 regional prescribers participated in this program.

Our study has several limitations. There was likely some degree of selection bias among the hospitalized patients who received initial buprenorphine treatment. To our knowledge, there is no specific validated screening tool for OUD in the inpatient acute care setting; moreover, we have been unable to implement standardized screening for OUD into the electronic health record. As such, we rely on the totality of the clinical circumstances approach to identify patients with OUD.

Furthermore, we had neither a comparison group nor a prospective plan to follow patients who did not remain engaged in care after discharge. In addition, our analysis of OUD admissions included F11 ICD-10 codes, which are limited by clinical documentation.^9,10 Our program focuses exclusively on buprenorphine initiation due to insufficient immediate outpatient capacity for methadone initiated during hospitalization and lack of coverage for extended-release naltrexone. Limitations to outpatient data-sharing prevented the reporting of outpatient appointments external to the identified partner program; since these appointments were included in the analysis as “lost to follow-up,” actual engagement rates may be higher than those reported.

Moving forward, the B-Team is continuing to serve as a role model for appropriate, patient-centered, evidence-based care for hospitalized patients with OUD. Attending physicians and residents with an X-waiver are now encouraged to initiate buprenorphine treatment on their own. In June 2020, we added peer-recovery support services to the program, which has improved care for patients and increased adoption of hospital-initiated substance use disorder interventions.¹¹ Lessons learned from inpatient implementation are being applied to our hospital’s emergency department and to an inpatient obstetrics unit at a partner hospital; they are also being employed to further empower hospitalists to diagnose and treat other substance use disorders, such as alcohol use disorder.

Hospitalizations related to opioid use disorder (OUD) have increased and now account for up to 6% of hospital admissions in certain areas of the United States.¹ Patients with OUD who are started on buprenorphine during hospitalization are more likely to enter outpatient treatment, stay in treatment longer, and have more drug-free days compared with patients who only receive a referral for outpatient treatment.^2,3 Therefore, a crucial comprehensive strategy for OUD care should include hospital-based programs that support initiation of treatment in the inpatient setting and strong bridges to outpatient care. One of the common barriers to initiating treatment in the inpatient setting, however, is a lack of access to addiction medicine specialists.^4-6

In 2017, we created a hospitalist-led interprofessional team called the B-Team (Buprenorphine Team) to help primary care teams identify patients with OUD, initiate and maintain buprenorphine therapy during hospitalization, provide warm handoffs to outpatient treatment programs, and reduce institutional stigma related to people with substance use disorders.

Program Description

The B-Team is led by a hospital medicine physician assistant and includes physicians from internal medicine, consult-liaison psychiatry, and palliative care; advanced practice and bedside nurses; a social worker; a pharmacist; a chaplain; a peer-recovery specialist; and medical trainees. The B-Team is notified of potential candidates for buprenorphine through a secure texting platform, one that is accessible to any healthcare provider at the hospital. Patients who are referred to the B-Team either self-identify or are identified by their primary team as having an underlying OUD. One of the B-Team providers assesses the patient to determine if they are eligible to receive inpatient therapy. Patients are considered eligible for the program if they meet Diagnostic and Statistical Manual of Mental Disorders (5th edition) criteria for OUD, have a desire to cease opioid use, and receive medical clearance to take buprenorphine.

For eligible patients, the B-Team provider orders a nurse-driven protocol to initiate buprenorphine for OUD. The chaplain offers psychospiritual counseling, and the social worker provides counseling and coordination of care. The B-Team partners with a nonhospital-affiliated, publicly-funded, office-based opioid treatment (OBOT) program that combines primary care with behavioral health programming. A follow-up outpatient appointment is secured prior to hospital discharge, and a member of the B-Team who has Drug Addiction Treatment Act of 2000 (DATA 2000) X-waiver certification prescribes buprenorphine as a bridge until the follow-up appointment. The medication is dispensed from the hospital’s retail pharmacy, and the patient leaves the hospital with the medication in-hand.

Patients who are not eligible for buprenorphine therapy are offered a harm-reduction intervention or referral to the psychiatry consult liaison service to assess for alternative diagnoses or treatment. These patients are also offered psychospiritual counseling and a prescription for naloxone.

Prior to the creation of the B-Team at our hospital, there was no structure in place to facilitate initiation of buprenorphine therapy during hospitalization and no linkage to outpatient treatment after discharge; furthermore, none of the hospitalists or other providers (including consulting psychiatrists) had an X-waiver to prescribe buprenorphine for OUD.

Program Evaluation

Study data were collected using Research Electronic Data Capture software. Inpatient and outpatient data were entered by a B-Team provider or a researcher via chart review. Patients were considered to be engaged in care if they attended at least one outpatient appointment for buprenorphine therapy during each of the following time periods: (1) 0 to 27 days (initial follow-up), 28-89 days (1- to 3-month follow-up), 90-179 days (3- to 6-month follow-up), and 180 days or more (>6-month follow-up). Only visits specifically for buprenorphine maintenance therapy were counted. If multiple encounters occurred within one time frame, the encounter closest to 0, 30, 90, or 180 days from discharge was used. If a patient did not attend any encounters during a specified time frame, they were considered to no longer be engaged in care and were no longer tracked for purposes of the evaluation. Data for the percentage of patients engaged in outpatient care are presented as the number of patients who attended at least one appointment during each of the follow-up periods (1 to 3 months, 3 to 6 months, or after 6 months, as noted above) divided by the number of patients who had been discharged with coordinated follow-up.

The number of patients admitted per month for whom there was an order to initiate inpatient buprenorphine therapy was analyzed using a statistical process control chart, in addition to the number of OUD admissions based on the inclusion of the International Classification of Disease, Tenth Revision (ICD-10) F11 code (opioid-related disorders) in any position in the discharge diagnoses.

This program and study were considered quality improvement by The University of Texas Institutional Review Board and did not meet criteria for human subjects research.

RESULTS

During the first 2 years of the program (September 2018-September 2020), the B-Team received 260 patient referrals. Most of the patients were White (72%), male (62%), and between ages 25 and 44 years (53%) (Appendix Table). The team initiated buprenorphine therapy in 132 hospitalized patients. In the year prior to the creation of the B-Team program, the average number of hospitalized patients receiving buprenorphine for OUD per month was three; after the launch of the B-Team program, this number increased to 12 encounters per month (Figure 1A). The sudden decrease observed in August 2020 is likely related to a surge in COVID-19 admissions. The number of monthly admissions for OUD is also shown (Figure 1B).

The B-Team saw a total of 132 eligible patients; members of the team provided counseling, support, and resources regarding buprenorphine therapy. In addition, the B-Team’s chaplain provided emotional support and spiritual connection (if desired) to 40 of these patients (30%). In the study, no cases of precipitated withdrawal were identified. Of the 132 patients seen, 110 (83%) were accepted to an outpatient OUD program upon discharge from the hospital; 98 (89%) of these patients were accepted at our partner OBOT clinic. The remaining patients were not interested in continuing OUD treatment (13%) or were denied acceptance to an outpatient program based on administrative and/or financial eligibility guidelines (4%). Patients who would not be attending an outpatient program were discontinued on buprenorphine therapy prior to discharge, counseled about naloxone, and provided printed resources.

Outpatient appointment attendance was used to measure ongoing treatment engagement of the 110 patients who were discharged with coordinated follow-up care. A total of 65 patients (59%) attended their first outpatient appointment; the average time between discharge and the first outpatient appointment was 5.9 days. Forty-two patients (38%) attended at least one appointment between 1 and 3 months; 29 (26%) between 3 and 6 months; and 24 (22%) after 6 months (Figure 2).

Of the 128 patients who were not administered buprenorphine therapy, 64 (50%) were not interested in starting treatment and/or were not ready to engage in treatment; 36 (28%) did not meet criteria for OUD treatment; 28 (22%) were already receiving treatment or preferred another type of OUD treatment; and 13 (10%) had severe comorbid addiction and/or illness requiring treatment that contraindicates the use of buprenorphine.

A volunteer hospitalist-led interprofessional team providing evidence-based care for hospitalized patients with OUD was associated with a substantial increase in patients receiving buprenorphine therapy—both during hospitalization and after discharge. In the program, 59% of patients attended initial follow-up appointments, and 22% of patients were still engaged at 6 months. These outpatient follow-up rates appear to be similar to, or higher than, other programs described in the literature. For example, a buprenorphine OUD-treatment initiative led by the psychiatry consult service at a Boston academic medical center resulted in less than half of patients receiving buprenorphine treatment within 2 months of discharge.⁷ In another study wherein an addiction medicine consult service administered buprenorphine to patients with OUD during hospitalization, 39%, 27%, and 18% of patients were retained in outpatient treatment at 30, 90, and 180 days, respectively.⁸

The B-Team model is likely generalizable to other hospital medicine groups that may not otherwise have access to inpatient care for substance use disorder. The B-Team is not an addiction medicine consultation service; rather, it is a hospitalist-led quality improvement initiative seeking to improve the standard of care for hospitalized patients with OUD.

A significant barrier is ensuring ongoing support for patients with OUD after discharge. In the B-Team program, a parallel OBOT program was created by a local nonaffiliated federally qualified health center. Although 89% of patients received treatment at this OBOT clinic, the inpatient team also has relationships with other local treatment centers, including programs that provide methadone. Another important barrier to high-quality outpatient care for OUD is the requirement of an X-waiver. To help overcome this barrier, our inpatient program partnered with a regional medical society to offer periodic X-waiver training to outpatient providers. In less than a year, more than 100 regional prescribers participated in this program.

Our study has several limitations. There was likely some degree of selection bias among the hospitalized patients who received initial buprenorphine treatment. To our knowledge, there is no specific validated screening tool for OUD in the inpatient acute care setting; moreover, we have been unable to implement standardized screening for OUD into the electronic health record. As such, we rely on the totality of the clinical circumstances approach to identify patients with OUD.

Furthermore, we had neither a comparison group nor a prospective plan to follow patients who did not remain engaged in care after discharge. In addition, our analysis of OUD admissions included F11 ICD-10 codes, which are limited by clinical documentation.^9,10 Our program focuses exclusively on buprenorphine initiation due to insufficient immediate outpatient capacity for methadone initiated during hospitalization and lack of coverage for extended-release naltrexone. Limitations to outpatient data-sharing prevented the reporting of outpatient appointments external to the identified partner program; since these appointments were included in the analysis as “lost to follow-up,” actual engagement rates may be higher than those reported.

Moving forward, the B-Team is continuing to serve as a role model for appropriate, patient-centered, evidence-based care for hospitalized patients with OUD. Attending physicians and residents with an X-waiver are now encouraged to initiate buprenorphine treatment on their own. In June 2020, we added peer-recovery support services to the program, which has improved care for patients and increased adoption of hospital-initiated substance use disorder interventions.¹¹ Lessons learned from inpatient implementation are being applied to our hospital’s emergency department and to an inpatient obstetrics unit at a partner hospital; they are also being employed to further empower hospitalists to diagnose and treat other substance use disorders, such as alcohol use disorder.

Hospitalizations related to opioid use disorder (OUD) have increased and now account for up to 6% of hospital admissions in certain areas of the United States.¹ Patients with OUD who are started on buprenorphine during hospitalization are more likely to enter outpatient treatment, stay in treatment longer, and have more drug-free days compared with patients who only receive a referral for outpatient treatment.^2,3 Therefore, a crucial comprehensive strategy for OUD care should include hospital-based programs that support initiation of treatment in the inpatient setting and strong bridges to outpatient care. One of the common barriers to initiating treatment in the inpatient setting, however, is a lack of access to addiction medicine specialists.^4-6

In 2017, we created a hospitalist-led interprofessional team called the B-Team (Buprenorphine Team) to help primary care teams identify patients with OUD, initiate and maintain buprenorphine therapy during hospitalization, provide warm handoffs to outpatient treatment programs, and reduce institutional stigma related to people with substance use disorders.

Program Description

The B-Team is led by a hospital medicine physician assistant and includes physicians from internal medicine, consult-liaison psychiatry, and palliative care; advanced practice and bedside nurses; a social worker; a pharmacist; a chaplain; a peer-recovery specialist; and medical trainees. The B-Team is notified of potential candidates for buprenorphine through a secure texting platform, one that is accessible to any healthcare provider at the hospital. Patients who are referred to the B-Team either self-identify or are identified by their primary team as having an underlying OUD. One of the B-Team providers assesses the patient to determine if they are eligible to receive inpatient therapy. Patients are considered eligible for the program if they meet Diagnostic and Statistical Manual of Mental Disorders (5th edition) criteria for OUD, have a desire to cease opioid use, and receive medical clearance to take buprenorphine.

For eligible patients, the B-Team provider orders a nurse-driven protocol to initiate buprenorphine for OUD. The chaplain offers psychospiritual counseling, and the social worker provides counseling and coordination of care. The B-Team partners with a nonhospital-affiliated, publicly-funded, office-based opioid treatment (OBOT) program that combines primary care with behavioral health programming. A follow-up outpatient appointment is secured prior to hospital discharge, and a member of the B-Team who has Drug Addiction Treatment Act of 2000 (DATA 2000) X-waiver certification prescribes buprenorphine as a bridge until the follow-up appointment. The medication is dispensed from the hospital’s retail pharmacy, and the patient leaves the hospital with the medication in-hand.

Patients who are not eligible for buprenorphine therapy are offered a harm-reduction intervention or referral to the psychiatry consult liaison service to assess for alternative diagnoses or treatment. These patients are also offered psychospiritual counseling and a prescription for naloxone.

Prior to the creation of the B-Team at our hospital, there was no structure in place to facilitate initiation of buprenorphine therapy during hospitalization and no linkage to outpatient treatment after discharge; furthermore, none of the hospitalists or other providers (including consulting psychiatrists) had an X-waiver to prescribe buprenorphine for OUD.

Program Evaluation

Study data were collected using Research Electronic Data Capture software. Inpatient and outpatient data were entered by a B-Team provider or a researcher via chart review. Patients were considered to be engaged in care if they attended at least one outpatient appointment for buprenorphine therapy during each of the following time periods: (1) 0 to 27 days (initial follow-up), 28-89 days (1- to 3-month follow-up), 90-179 days (3- to 6-month follow-up), and 180 days or more (>6-month follow-up). Only visits specifically for buprenorphine maintenance therapy were counted. If multiple encounters occurred within one time frame, the encounter closest to 0, 30, 90, or 180 days from discharge was used. If a patient did not attend any encounters during a specified time frame, they were considered to no longer be engaged in care and were no longer tracked for purposes of the evaluation. Data for the percentage of patients engaged in outpatient care are presented as the number of patients who attended at least one appointment during each of the follow-up periods (1 to 3 months, 3 to 6 months, or after 6 months, as noted above) divided by the number of patients who had been discharged with coordinated follow-up.

The number of patients admitted per month for whom there was an order to initiate inpatient buprenorphine therapy was analyzed using a statistical process control chart, in addition to the number of OUD admissions based on the inclusion of the International Classification of Disease, Tenth Revision (ICD-10) F11 code (opioid-related disorders) in any position in the discharge diagnoses.

This program and study were considered quality improvement by The University of Texas Institutional Review Board and did not meet criteria for human subjects research.

RESULTS

During the first 2 years of the program (September 2018-September 2020), the B-Team received 260 patient referrals. Most of the patients were White (72%), male (62%), and between ages 25 and 44 years (53%) (Appendix Table). The team initiated buprenorphine therapy in 132 hospitalized patients. In the year prior to the creation of the B-Team program, the average number of hospitalized patients receiving buprenorphine for OUD per month was three; after the launch of the B-Team program, this number increased to 12 encounters per month (Figure 1A). The sudden decrease observed in August 2020 is likely related to a surge in COVID-19 admissions. The number of monthly admissions for OUD is also shown (Figure 1B).

The B-Team saw a total of 132 eligible patients; members of the team provided counseling, support, and resources regarding buprenorphine therapy. In addition, the B-Team’s chaplain provided emotional support and spiritual connection (if desired) to 40 of these patients (30%). In the study, no cases of precipitated withdrawal were identified. Of the 132 patients seen, 110 (83%) were accepted to an outpatient OUD program upon discharge from the hospital; 98 (89%) of these patients were accepted at our partner OBOT clinic. The remaining patients were not interested in continuing OUD treatment (13%) or were denied acceptance to an outpatient program based on administrative and/or financial eligibility guidelines (4%). Patients who would not be attending an outpatient program were discontinued on buprenorphine therapy prior to discharge, counseled about naloxone, and provided printed resources.

Outpatient appointment attendance was used to measure ongoing treatment engagement of the 110 patients who were discharged with coordinated follow-up care. A total of 65 patients (59%) attended their first outpatient appointment; the average time between discharge and the first outpatient appointment was 5.9 days. Forty-two patients (38%) attended at least one appointment between 1 and 3 months; 29 (26%) between 3 and 6 months; and 24 (22%) after 6 months (Figure 2).

Of the 128 patients who were not administered buprenorphine therapy, 64 (50%) were not interested in starting treatment and/or were not ready to engage in treatment; 36 (28%) did not meet criteria for OUD treatment; 28 (22%) were already receiving treatment or preferred another type of OUD treatment; and 13 (10%) had severe comorbid addiction and/or illness requiring treatment that contraindicates the use of buprenorphine.

A volunteer hospitalist-led interprofessional team providing evidence-based care for hospitalized patients with OUD was associated with a substantial increase in patients receiving buprenorphine therapy—both during hospitalization and after discharge. In the program, 59% of patients attended initial follow-up appointments, and 22% of patients were still engaged at 6 months. These outpatient follow-up rates appear to be similar to, or higher than, other programs described in the literature. For example, a buprenorphine OUD-treatment initiative led by the psychiatry consult service at a Boston academic medical center resulted in less than half of patients receiving buprenorphine treatment within 2 months of discharge.⁷ In another study wherein an addiction medicine consult service administered buprenorphine to patients with OUD during hospitalization, 39%, 27%, and 18% of patients were retained in outpatient treatment at 30, 90, and 180 days, respectively.⁸

The B-Team model is likely generalizable to other hospital medicine groups that may not otherwise have access to inpatient care for substance use disorder. The B-Team is not an addiction medicine consultation service; rather, it is a hospitalist-led quality improvement initiative seeking to improve the standard of care for hospitalized patients with OUD.

A significant barrier is ensuring ongoing support for patients with OUD after discharge. In the B-Team program, a parallel OBOT program was created by a local nonaffiliated federally qualified health center. Although 89% of patients received treatment at this OBOT clinic, the inpatient team also has relationships with other local treatment centers, including programs that provide methadone. Another important barrier to high-quality outpatient care for OUD is the requirement of an X-waiver. To help overcome this barrier, our inpatient program partnered with a regional medical society to offer periodic X-waiver training to outpatient providers. In less than a year, more than 100 regional prescribers participated in this program.

Our study has several limitations. There was likely some degree of selection bias among the hospitalized patients who received initial buprenorphine treatment. To our knowledge, there is no specific validated screening tool for OUD in the inpatient acute care setting; moreover, we have been unable to implement standardized screening for OUD into the electronic health record. As such, we rely on the totality of the clinical circumstances approach to identify patients with OUD.

Furthermore, we had neither a comparison group nor a prospective plan to follow patients who did not remain engaged in care after discharge. In addition, our analysis of OUD admissions included F11 ICD-10 codes, which are limited by clinical documentation.^9,10 Our program focuses exclusively on buprenorphine initiation due to insufficient immediate outpatient capacity for methadone initiated during hospitalization and lack of coverage for extended-release naltrexone. Limitations to outpatient data-sharing prevented the reporting of outpatient appointments external to the identified partner program; since these appointments were included in the analysis as “lost to follow-up,” actual engagement rates may be higher than those reported.

Moving forward, the B-Team is continuing to serve as a role model for appropriate, patient-centered, evidence-based care for hospitalized patients with OUD. Attending physicians and residents with an X-waiver are now encouraged to initiate buprenorphine treatment on their own. In June 2020, we added peer-recovery support services to the program, which has improved care for patients and increased adoption of hospital-initiated substance use disorder interventions.¹¹ Lessons learned from inpatient implementation are being applied to our hospital’s emergency department and to an inpatient obstetrics unit at a partner hospital; they are also being employed to further empower hospitalists to diagnose and treat other substance use disorders, such as alcohol use disorder.

© 2017 Society of Hospital Medicine

Strategies are needed to empower frontline clinicians to work with organizational leadership to reduce healthcare costs and improve high-value care. Caring Wisely^® is a program developed by the University of California, San Francisco’s (UCSF) Center for Healthcare Value (CHV), aimed at engaging frontline clinicians and staff, connecting them with implementation experts, and supporting the development of targeted interventions to improve value. Financial savings from the program more than cover program costs. Caring Wisely^® provides an institutional model for implementing robust interventions to address areas of low-value care.

Launched in 2013, the annual Caring Wisely^® program consists of 3 stages for identifying projects that meet the following criteria:

• Potential to measurably reduce UCSF Health’s costs of care without transferring costs to patients, insurers, or other providers
• Plan for ensuring that health outcomes are maintained or improved
• Envision disseminating the intervention within and beyond UCSF
• Demonstrate commitment and engagement of clinical leadership and frontline staff.

The first stage is the Ideas Contest, a UCSF Health-wide call (to learn more about UCSF Health: https://www.ucsf.edu/sites/default/files/052516_About_UCSF.pdf) to identify areas that may be targeted to reduce unnecessary services, inefficiencies, and healthcare costs. We use a crowdsourcing platform—Open Proposals—to solicit the best ideas from frontline clinicians and staff.¹ Open Proposals is a secure, web-based platform for transparent and collaborative proposal development that displays threads of comments, responses, and revisions, and allows submissions to be “liked.” Open Proposals is managed by the UCSF Clinical and Translational Science Institute, funded by the National Center for Advancing Translational Sciences (Grant Number UL1 TR000004) at the National Institutes of Health. Using institutional e-mail lists for faculty, staff and residents, as well as described at monthly managers and directors meetings, the Ideas Contest is announced each year by the Chief Medical Officer and the CHV leadership. The Caring Wisely^® Executive Steering Committee, which consists of CHV and senior UCSF Health system leaders, selects the top 5-10 ideas based on the above criteria. Each winning idea receives a $100 gift certificate for a popular restaurant in San Francisco, and the list of winners is announced to the entire UCSF community.

The second stage is the Request for Proposals. The Caring Wisely^® program solicits proposals that outline implementation plans to target specific areas identified through the Ideas Contest. Finalists from the Ideas Contest are encouraged to submit proposals that address the problem they identified, but anyone affiliated with UCSF Health may submit a proposal on a winning idea. There is an approximately 4-week open submission period during which applicants submit brief 2-page proposals on the Open Proposal platform. This is followed by a period of optimization that leverages the social media aspect of the Open Proposals platform in which the UCSF Health community asks clarifying questions, make suggestions, and modifications can be made to the proposals. All submissions receive written feedback from at least one Steering Committee member. In addition, the Caring Wisely^® Director directly invites relevant UCSF colleagues, administrators, or program leaders to comment on proposals and make suggestions for improvement. Plans for assessing financial and health care delivery impacts are developed in collaboration with the UCSF Health Finance department. UCSF Health managers and leaders who are stakeholders in project proposal areas are consulted to provide input and finalize proposal plans, including the identification of existing personnel who can support and drive the project forward. Proposers use this feedback to revise their applications throughout this stage.

The third stage is Project Implementation. The Caring Wisely^® Executive Steering Committee selects up to 3 winners from the submitted proposals. Using the program criteria above, each project is scored independently, discussed in committee, and rescored to identify the top proposals. Each selected project receives a maximum budget of $50,000 that can be used for project materials, activities, and salary support for project leaders or staff. In addition to funding, each project team receives input from the implementation science team to co-develop and implement the intervention with a goal of creating a first-test-of-change within 3-6 months. A key feature of Caring Wisely^® is the partnership between project teams and the Caring Wisely^® implementation team, which includes a director, program manager, data analysts, and implementation scientists (Table 1).

LIST OF ABBREVIATIONS

UCSF—University of California, San Francisco; PRECEDE—Predisposing, Reinforcing, and Enabling Constructs in Educational Diagnosis and Evaluation; PROCEED—Policy, Regulatory and Organizational Constructs in Educational and Environmental Development

Acknowledgments

Other participants in blood transfusion reduction project (D. Johnson, K. Curcione); IV-to-PO Switch (C. Tsourounis, A. Pollock); Surgical Supply Cost Reduction (C. Zygourakis); Perioperative Efficiency (L. Hampson); CT for PE Risk Prediction (E. Weber); ERAS Pathways (L. Chen); Neonatal Sepsis Risk Prediction (T. Newman); Post-Operative Debrief (S. Imershein). Caring Wisely Executive Steering Committee (J. Adler, S. Antrum, A Auerbach, J. Bennan, M. Blum, C. Ritchie, C. Tsourounis). This Center for Healthcare Value is funded in part by a grant from the Grove Foundation. We appreciate additional review and comments to the manuscript provided by George Sawaya and Adams Dudley.

Disclosures 

Christopher Moriates has accepted royalties from McGraw-Hill for textbook, Understanding Value-Based Healthcare. Alvin Rajkomar has received fees as a research adviser from Google, Inc.

© 2017 Society of Hospital Medicine

Strategies are needed to empower frontline clinicians to work with organizational leadership to reduce healthcare costs and improve high-value care. Caring Wisely^® is a program developed by the University of California, San Francisco’s (UCSF) Center for Healthcare Value (CHV), aimed at engaging frontline clinicians and staff, connecting them with implementation experts, and supporting the development of targeted interventions to improve value. Financial savings from the program more than cover program costs. Caring Wisely^® provides an institutional model for implementing robust interventions to address areas of low-value care.

Launched in 2013, the annual Caring Wisely^® program consists of 3 stages for identifying projects that meet the following criteria:

• Potential to measurably reduce UCSF Health’s costs of care without transferring costs to patients, insurers, or other providers
• Plan for ensuring that health outcomes are maintained or improved
• Envision disseminating the intervention within and beyond UCSF
• Demonstrate commitment and engagement of clinical leadership and frontline staff.

The first stage is the Ideas Contest, a UCSF Health-wide call (to learn more about UCSF Health: https://www.ucsf.edu/sites/default/files/052516_About_UCSF.pdf) to identify areas that may be targeted to reduce unnecessary services, inefficiencies, and healthcare costs. We use a crowdsourcing platform—Open Proposals—to solicit the best ideas from frontline clinicians and staff.¹ Open Proposals is a secure, web-based platform for transparent and collaborative proposal development that displays threads of comments, responses, and revisions, and allows submissions to be “liked.” Open Proposals is managed by the UCSF Clinical and Translational Science Institute, funded by the National Center for Advancing Translational Sciences (Grant Number UL1 TR000004) at the National Institutes of Health. Using institutional e-mail lists for faculty, staff and residents, as well as described at monthly managers and directors meetings, the Ideas Contest is announced each year by the Chief Medical Officer and the CHV leadership. The Caring Wisely^® Executive Steering Committee, which consists of CHV and senior UCSF Health system leaders, selects the top 5-10 ideas based on the above criteria. Each winning idea receives a $100 gift certificate for a popular restaurant in San Francisco, and the list of winners is announced to the entire UCSF community.

The second stage is the Request for Proposals. The Caring Wisely^® program solicits proposals that outline implementation plans to target specific areas identified through the Ideas Contest. Finalists from the Ideas Contest are encouraged to submit proposals that address the problem they identified, but anyone affiliated with UCSF Health may submit a proposal on a winning idea. There is an approximately 4-week open submission period during which applicants submit brief 2-page proposals on the Open Proposal platform. This is followed by a period of optimization that leverages the social media aspect of the Open Proposals platform in which the UCSF Health community asks clarifying questions, make suggestions, and modifications can be made to the proposals. All submissions receive written feedback from at least one Steering Committee member. In addition, the Caring Wisely^® Director directly invites relevant UCSF colleagues, administrators, or program leaders to comment on proposals and make suggestions for improvement. Plans for assessing financial and health care delivery impacts are developed in collaboration with the UCSF Health Finance department. UCSF Health managers and leaders who are stakeholders in project proposal areas are consulted to provide input and finalize proposal plans, including the identification of existing personnel who can support and drive the project forward. Proposers use this feedback to revise their applications throughout this stage.

The third stage is Project Implementation. The Caring Wisely^® Executive Steering Committee selects up to 3 winners from the submitted proposals. Using the program criteria above, each project is scored independently, discussed in committee, and rescored to identify the top proposals. Each selected project receives a maximum budget of $50,000 that can be used for project materials, activities, and salary support for project leaders or staff. In addition to funding, each project team receives input from the implementation science team to co-develop and implement the intervention with a goal of creating a first-test-of-change within 3-6 months. A key feature of Caring Wisely^® is the partnership between project teams and the Caring Wisely^® implementation team, which includes a director, program manager, data analysts, and implementation scientists (Table 1).

LIST OF ABBREVIATIONS

UCSF—University of California, San Francisco; PRECEDE—Predisposing, Reinforcing, and Enabling Constructs in Educational Diagnosis and Evaluation; PROCEED—Policy, Regulatory and Organizational Constructs in Educational and Environmental Development

Acknowledgments

Other participants in blood transfusion reduction project (D. Johnson, K. Curcione); IV-to-PO Switch (C. Tsourounis, A. Pollock); Surgical Supply Cost Reduction (C. Zygourakis); Perioperative Efficiency (L. Hampson); CT for PE Risk Prediction (E. Weber); ERAS Pathways (L. Chen); Neonatal Sepsis Risk Prediction (T. Newman); Post-Operative Debrief (S. Imershein). Caring Wisely Executive Steering Committee (J. Adler, S. Antrum, A Auerbach, J. Bennan, M. Blum, C. Ritchie, C. Tsourounis). This Center for Healthcare Value is funded in part by a grant from the Grove Foundation. We appreciate additional review and comments to the manuscript provided by George Sawaya and Adams Dudley.

Disclosures 

Christopher Moriates has accepted royalties from McGraw-Hill for textbook, Understanding Value-Based Healthcare. Alvin Rajkomar has received fees as a research adviser from Google, Inc.

© 2017 Society of Hospital Medicine

Strategies are needed to empower frontline clinicians to work with organizational leadership to reduce healthcare costs and improve high-value care. Caring Wisely^® is a program developed by the University of California, San Francisco’s (UCSF) Center for Healthcare Value (CHV), aimed at engaging frontline clinicians and staff, connecting them with implementation experts, and supporting the development of targeted interventions to improve value. Financial savings from the program more than cover program costs. Caring Wisely^® provides an institutional model for implementing robust interventions to address areas of low-value care.

Launched in 2013, the annual Caring Wisely^® program consists of 3 stages for identifying projects that meet the following criteria:

• Potential to measurably reduce UCSF Health’s costs of care without transferring costs to patients, insurers, or other providers
• Plan for ensuring that health outcomes are maintained or improved
• Envision disseminating the intervention within and beyond UCSF
• Demonstrate commitment and engagement of clinical leadership and frontline staff.

The first stage is the Ideas Contest, a UCSF Health-wide call (to learn more about UCSF Health: https://www.ucsf.edu/sites/default/files/052516_About_UCSF.pdf) to identify areas that may be targeted to reduce unnecessary services, inefficiencies, and healthcare costs. We use a crowdsourcing platform—Open Proposals—to solicit the best ideas from frontline clinicians and staff.¹ Open Proposals is a secure, web-based platform for transparent and collaborative proposal development that displays threads of comments, responses, and revisions, and allows submissions to be “liked.” Open Proposals is managed by the UCSF Clinical and Translational Science Institute, funded by the National Center for Advancing Translational Sciences (Grant Number UL1 TR000004) at the National Institutes of Health. Using institutional e-mail lists for faculty, staff and residents, as well as described at monthly managers and directors meetings, the Ideas Contest is announced each year by the Chief Medical Officer and the CHV leadership. The Caring Wisely^® Executive Steering Committee, which consists of CHV and senior UCSF Health system leaders, selects the top 5-10 ideas based on the above criteria. Each winning idea receives a $100 gift certificate for a popular restaurant in San Francisco, and the list of winners is announced to the entire UCSF community.

The second stage is the Request for Proposals. The Caring Wisely^® program solicits proposals that outline implementation plans to target specific areas identified through the Ideas Contest. Finalists from the Ideas Contest are encouraged to submit proposals that address the problem they identified, but anyone affiliated with UCSF Health may submit a proposal on a winning idea. There is an approximately 4-week open submission period during which applicants submit brief 2-page proposals on the Open Proposal platform. This is followed by a period of optimization that leverages the social media aspect of the Open Proposals platform in which the UCSF Health community asks clarifying questions, make suggestions, and modifications can be made to the proposals. All submissions receive written feedback from at least one Steering Committee member. In addition, the Caring Wisely^® Director directly invites relevant UCSF colleagues, administrators, or program leaders to comment on proposals and make suggestions for improvement. Plans for assessing financial and health care delivery impacts are developed in collaboration with the UCSF Health Finance department. UCSF Health managers and leaders who are stakeholders in project proposal areas are consulted to provide input and finalize proposal plans, including the identification of existing personnel who can support and drive the project forward. Proposers use this feedback to revise their applications throughout this stage.

The third stage is Project Implementation. The Caring Wisely^® Executive Steering Committee selects up to 3 winners from the submitted proposals. Using the program criteria above, each project is scored independently, discussed in committee, and rescored to identify the top proposals. Each selected project receives a maximum budget of $50,000 that can be used for project materials, activities, and salary support for project leaders or staff. In addition to funding, each project team receives input from the implementation science team to co-develop and implement the intervention with a goal of creating a first-test-of-change within 3-6 months. A key feature of Caring Wisely^® is the partnership between project teams and the Caring Wisely^® implementation team, which includes a director, program manager, data analysts, and implementation scientists (Table 1).

LIST OF ABBREVIATIONS

UCSF—University of California, San Francisco; PRECEDE—Predisposing, Reinforcing, and Enabling Constructs in Educational Diagnosis and Evaluation; PROCEED—Policy, Regulatory and Organizational Constructs in Educational and Environmental Development

Acknowledgments

Other participants in blood transfusion reduction project (D. Johnson, K. Curcione); IV-to-PO Switch (C. Tsourounis, A. Pollock); Surgical Supply Cost Reduction (C. Zygourakis); Perioperative Efficiency (L. Hampson); CT for PE Risk Prediction (E. Weber); ERAS Pathways (L. Chen); Neonatal Sepsis Risk Prediction (T. Newman); Post-Operative Debrief (S. Imershein). Caring Wisely Executive Steering Committee (J. Adler, S. Antrum, A Auerbach, J. Bennan, M. Blum, C. Ritchie, C. Tsourounis). This Center for Healthcare Value is funded in part by a grant from the Grove Foundation. We appreciate additional review and comments to the manuscript provided by George Sawaya and Adams Dudley.

Disclosures 

Christopher Moriates has accepted royalties from McGraw-Hill for textbook, Understanding Value-Based Healthcare. Alvin Rajkomar has received fees as a research adviser from Google, Inc.