Angela Keniston, MSPH

Studies continue to demonstrate persistent gaps in equity for women and underrepresented minorities (URMs)¹ throughout nearly all aspects of academic medicine, including rank,^2-4 tenure,⁵ authorship,^6,7 funding opportunities,^8,9 awards,¹⁰ speakership,¹¹ leadership,^12,13 and salaries.^2,14,15 Hospital medicine, despite being a newer field,¹⁶ has also seen these disparities^17,18; however, there are numerous efforts in place to actively change our specialty’s course.^19-22 Hospital medicine is a field known for being a change agent in healthcare delivery,²² and its novel approaches are well poised to fundamentally shatter the glass ceilings imposed on traditionally underrepresented groups in medicine. The importance of diversity, equity, and inclusion (DEI) initiatives in healthcare has never been clearer,^23,24 particularly as they relate to cultural competence^25-28 and cultural humility,^29,30 implicit and explicit bias,²⁷ expanding care for underserved patient populations, supporting our workforce, and broadening research agendas.²⁸

In this article, we report DEI efforts within our division, focusing on the development of our strategic plan and specific outcomes related to compensation, recruitment, and policies.

Our Division’s Framework to DEI—“It Takes a Village”

Our Division of Hospital Medicine (DHM), previously within the Division of General Internal Medicine, was founded in October 2017. The DHM at the University of Colorado Hospital (UCH) is composed of 100 faculty members (70 physicians and 30 advanced-practice providers; 58% women and 42% men). In 2018, we implemented a stepwise approach to critically assess DEI within our group and to build a strategic plan to address the issues. Key areas of focus included institutional structures, our people, our environments, and our core missions (Figure 1 and Appendix Figure 1). DHM members helped drive our work and partnered with departmental, hospital, and school of medicine committees; national organizations; and collaborators to enhance implementation and dissemination efforts. In addition to stakeholder engagement, we utilized strategic planning and rapid Plan-Do-Study-Act (PDSA) cycles to advance DEI work in our DHM.

Needs Assessment

As a new division, we sought stakeholder feedback from division members. All faculty within the division were invited to attend a meeting in which issues related to DEI were discussed. A literature review that spanned both medical and nonmedical fields was also completed. Search terms included salary equity, gender equity, diverse teams, diversity recruitment and retention, diversifying leadership, and diverse speakers. Salaries, internally funded time, and other processes, such as recruitment, promotion, and hiring for leadership positions, were evaluated during the first year we became a division.

Interventions

TThrough this work, and with stakeholder engagement, we developed a divisional strategic plan to address DEI globally. Our strategic plan included developing a DEI director role to assist with overseeing DEI efforts. We have highlighted the various methods utilized for each component (Figure 1). This work occurred from October 2017 to December 2018.

Our institutional structures

Using best practices from both medical and nonmedical fields, we developed evidence-based approaches to compensation,³¹ recruitment,³² and policies that support and foster a culture of DEI.³² These strategies were used to support the following initiatives:

Compensation: transparent and consistent approaches based upon benchmarking with a framework of equal pay for equal work and similar advanced training/academic rank. In conjunction with efforts within the School of Medicine (SOM), Department of Medicine (DOM), and the UCH, our division sought to study salaries across DHM faculty members. We had an open call for faculty to participate in a newly developed DHM Compensation Committee, with the intent of rigorously examining our compensation practices and goals. Through faculty feedback and committee work, salary equity was defined as equal pay (ie, base salary for one clinical full-time equivalent [FTE]) for equal work based on academic rank and/or years of practice/advanced training. We also compared DHM salaries to regional academic hospital medicine groups and concluded that DHM salaries were lower than local and national benchmarks. This information was used to create a two-phase approach to increasing salaries for all individuals below the American Association of Medical Colleges (AAMC) benchmarks³³ for academic hospitalists. We also developed a stipend system for external roles that came with additional compensation and roles within our own division that came with additional pay (ie, nocturnist). Phase 1 focused on those whose salaries were furthest away from and below benchmark, and phase 2 targeted all remaining individuals below benchmark.

A similar review of FTEs (based on required number of shifts for a full-time hospitalist) tied to our internal DHM leadership positions was completed by the division head and director of DEI. Specifically, the mission for each of our internally funded roles, job descriptions, and responsibilities was reviewed to ensure equity in funding.

Recruitment and advancement: processes to ensure equity and diversity in recruitment, tracking, and reporting, working to eliminate/mitigate bias. In collaboration with members of the AAMC Group on Women in Medicine and Science (GWIMS) and coauthors from various institutions, we developed toolkits and checklists aimed at achieving equity and diversity within candidate pools and on major committees, including, but not limited to, search and promotion committees.³² Additionally, a checklist was developed to help recruit more diverse speakers, including women and URMs, for local, regional, and national conferences.

Policies: evidence-based approaches, tracking and reporting, standardized approaches to eliminate/mitigate bias, embracing nontraditional paths. In partnership with our departmental efforts, members of our team led data collection and reporting for salary benchmarking, leadership roles, and committee membership. This included developing surveys and reporting templates that can be used to identify disparities and inform future efforts. We worked to ensure that we have faculty representing our field at the department and SOM levels. Specifically, we made sure to nominate division members during open calls for departmental and schoolwide committees, including the promotions committee.

Our People

The faculty and staff within our division have been instrumental in moving efforts forward in the following important areas.

Leadership: develop the position of director of DEI as well as leadership structures to support and increase DEI. One of the first steps in our strategic plan was creating a director of DEI leadership role (Appendix Figure 2). The director is responsible for researching, applying, and promoting a broad scope of DEI initiatives and best practices within the DHM, DOM, and SOM (in collaboration with their leaders), including recruitment, retention, and promotion of medical students, residents, and faculty; educational program development; health disparities research; and community-engaged scholarship.

Support: develop family leave policies/develop flexible work policies. Several members of our division worked on departmental committees and served in leadership roles on staff and faculty council. Estimated costs were assessed. Through collective efforts of department leadership and division head support, the department approved parental leave to employees following the birth of an employee’s child or the placement of a child with an employee in connection with adoption or permanent foster care.

Mentorship/sponsorship: enhance faculty advancement programs/develop pipeline and trainings/collaborate with student groups and organizations/invest in all of our people. Faculty across our divisional sites have held important roles in developing pipeline programs for undergraduate students bound for health professions, as well as programs developed specifically for medical students and internal medicine residents. This includes two programs, the CU Hospitalist Scholars Program (CUHSP) and Leadership Education for Aspiring Doctors (LEAD), in which undergraduate students have the opportunity to round with hospital medicine teams, work on quality-improvement projects, and receive extensive mentorship and advising from a diverse faculty team. Additionally, our faculty advancement team within the DHM has grown and been restructured to include more defined goals and to ensure each faculty member has at least one mentor in their area of interest.

Supportive: lactation space and support/diverse space options/inclusive and diverse environments. We worked closely with hospital leadership to advocate for adequately equipped lactation spaces, including equipment such as pumps, refrigerators, and computer workstations. Additionally, our team members conducted environmental scans (eg, identified pictures, artwork, or other images that were not representative of a diverse and inclusive environment and raised concerns when the environment was not inclusive).

Measures

Our measures focused on (1) development and implementation of our DEI strategic plan, including new policies, processes, and practices related to key components of the DEI program; and (2) assessment of specific DEI programs, including pre-post salary data disparities based on rank and pre-post disparities for protected time for similar roles.

Analysis

Through rapid PDSA cycles, we evaluated salary equity, equity in leadership allotment, and committee membership. We have developed a tracking board to track progress of the multiple projects in the strategic plan.

Strategic Plan Development and Tracking

From October 2017 to December 2018, we developed a robust strategic plan and stepwise approach to DEI (Figure 1 and Figure 2). The director of DEI position was developed (see Appendix Figure 2 for job description) to help oversee these efforts. Figure 3 highlights the specific efforts and the progress made on implementation (ie, high-level dashboard or “tracking board”). While outcomes are still pending in the areas of recruitment and advancement and environment, we have made measurable improvements in compensation, as outlined in the following section.

Compensation

One year after the salary-equity interventions, all of our physician faculty’s salaries were at the goal benchmark (Table), and differences in salary for those in similar years of rank were nearly eliminated. Similarly, after implementing an internally consistent approach to assigning FTE for new and established positions within the division (ie, those that fall within the purview of the division), all faculty in similar types of roles had similar amounts of protected time.

Recruitment and Advancement

Toolkits³² and committee recommendations have been incorporated into division goals, though some aspects are still in implementation phases, as division-wide implicit bias training was delayed secondary to the COVID-19 pandemic. Key goals include: (1) implicit bias training for all members of major committees; (2) aiming for a goal of at least 40% representation of women and 40% URMs on committees; (3) having a diversity expert serve on each committee in order to identify and discuss any potential bias in the search and candidate-selection processes; and (4) careful tracking of diversity metrics in regard to diversity of candidates at each step of the interview and selection process.

Surveys and reporting templates for equity on committees and leadership positions have been developed and deployed. Data dashboards for our division have been developed as well (for compensation, leadership, and committee membership). A divisional dashboard to report recruitment efforts is in progress.

We have successfully nominated several faculty members to the SOM promotions committee and departmental committees during open calls for these positions. At the division level, we have also adapted internal policies to ensure promotion occurs on time and offers alternative pathways for faculty that may primarily focus on clinical pathways. All faculty who have gone up for promotion thus far have been successfully promoted in their desired pathway.

Environment

We successfully advocated and achieved adequately equipped lactation spaces, including equipment such as pumps, refrigerators, and computer workstations. This achievement was possible because of our hospital partners. Our efforts helped us acquire sufficient space and facilities such that nursing mothers can pump and still be able to answer phones, enter orders, and document visits.

Our team members conducted environmental scans and raised concerns when the environment was not inclusive, such as conference rooms with portraits of leadership that do not show diversity. The all-male pictures were removed from one frequently used departmental conference room, which will eventually house a diverse group of pictures and achievements.

We aim to eliminate bias by offering implicit bias training for our faculty. While this is presently required for those who serve on committees, in leadership positions, or those involved in recruitment and interviewing for the DOM, our goal is to eventually provide this training to all faculty and staff in the division. We have also incorporated DEI topics into our educational conferences for faculty, including sessions on recognizing bias in medicine, how to be an upstander/ally, and the impact of race and racism on medicine.

DISCUSSION

The important findings of this work are: (1) that successes in DEI can be achieved with strategic planning and stakeholder engagement; (2) through simple modification of processes, we can improve equity in compensation and FTE allotted to leadership; (3) though it takes time, diversity recruitment can be improved using sound, sustainable, evidence-based processes; (4) this work is time-intensive and challenging, requiring ongoing efforts to improve, modify, and enhance current efforts and future successes.

We have certainly made some progress with DEI initiatives within our division and have also learned a great deal from this experience. First, change is difficult for all parties involved, including those leading change and those affected by the changes. We purposely made an effort to facilitate discussions with all of the DHM faculty and staff to ensure that everyone felt included in this work and that everyone’s voice was heard. This was exemplified by inviting all faculty members to a feedback session in which we discussed DEI within our division and areas that we wanted to improve on. Early on, we were able to define what diversity, equity, and inclusion meant to us as a division and then use these definitions to develop tangible goals for all the areas of highest importance to the group.

By increasing faculty presence on key committees, such as the promotions committee, we now have faculty members who are well versed in promotions processes. We are fortunate to have a promotions process that supports faculty advancement for faculty with diverse interests that spans from supporting highly clinical faculty, clinician educators, as well as more traditional researchers.³⁴ By having hospitalists serve in these roles, we help to add to the diverse perspectives on these committees, including emphasizing the scholarship that is associated with quality improvement, as well as DEI efforts which can often be viewed as service as opposed to scholarship.

Clear communication and transparency were key to all of our DEI initiatives. We had monthly updates on our DEI efforts during business meetings and also held impromptu meetings (also known as flash mobs³⁵) to answer questions and discuss concerns in real time. As with all DEI work, it is important to know where you are starting (having accurate data and a clear understanding of the data) and be able to communicate that data to the group. For example, using AAMC salary benchmarking³³ as well as other benchmarks allowed us to accurately calculate variance among salaries and identify the appropriate goal salary for each of our faculty members. Likewise, by completing an in-depth inventory on the work being done by all of our faculty in leadership roles, we were able to standardize the compensation/FTE for each of these roles. Tracking these changes over time, via the use of dashboards in our case, allows for real-time measurements and accountability for all of those involved. Our end goal will be to have all of these initiatives feed into one large dashboard.

Collaborating with leadership and stakeholders in the DOM, SOM, and hospital helped to make our DEI initiatives successful. Much too often, we work in silos when it comes to DEI work. However, we tend to have similar goals and can achieve much more if we work together. Collaboration with multiple stakeholders allowed for wider dissemination and resulted in a larger impact to the campus and community at large. This has been exemplified by the committee composition guidance that has been utilized by the DOM, as well as implementation of campus-wide policies, specifically the parental leave policy, which our faculty members played an important role in creating. Likewise, it is important to look outside of our institutions and work with other hospital medicine groups around the country who are interested in promoting DEI.

We still have much work ahead of us. We are continuing to measure outcomes status postimplementation of the toolkit and checklists being used for diversity recruitment and committee composition. Additionally, we are actively working on several initiatives, including:

• Instituting implicit bias training for all of our faculty
• Partnering with national leaders and our hospital systems to develop zero-tolerance policies regarding abusive behaviors (verbal, physical, and other), racism, and sexism in the hospital and other work settings
• Development of specific recruitment strategies as a means of diversifying our healthcare workforce (of note, based on a 2020 survey of our faculty, in which there was a 70% response rate, 8.5% of our faculty identified as URMs)
• Completion of a diversity dashboard to track our progress in all of these efforts over time
• Development of a more robust pipeline to promotion and leadership for our URM faculty

This study has several strengths. Many of the plans and strategies described here can be used to guide others interested in implementing this work. Figure 2 provides a stepwise
approach to addressing DEI in hospital medicine groups and divisions. We conducted this work at a large academic medical center, and while it may not be generalizable, it does offer some ideas for others to consider in their own work to advance DEI at their institutions. There are also several limitations to this work. Eliminating salary inequities with our approach did take resources. We took advantage of already lower salaries and the need to increase salaries closer to benchmark and paired this effort with our DEI efforts to achieve salary equity. This required partnerships with the department and hospital. Efforts to advance DEI also take a lot of time and effort, and thus commitment from the division, department, and institution as a whole is key. While we have outcomes for our efforts related to salary equity, recruitment efforts should be realized over time, as currently it is too early to tell. We have highlighted the efforts that have been put in place at this time.

Using a systematic evidence-based approach with key stakeholder involvement, a division-wide DEI strategy was developed and implemented. While this work is still ongoing, short-term wins are possible, in particular around salary equity and development of policies and structures to promote DEI.

Studies continue to demonstrate persistent gaps in equity for women and underrepresented minorities (URMs)¹ throughout nearly all aspects of academic medicine, including rank,^2-4 tenure,⁵ authorship,^6,7 funding opportunities,^8,9 awards,¹⁰ speakership,¹¹ leadership,^12,13 and salaries.^2,14,15 Hospital medicine, despite being a newer field,¹⁶ has also seen these disparities^17,18; however, there are numerous efforts in place to actively change our specialty’s course.^19-22 Hospital medicine is a field known for being a change agent in healthcare delivery,²² and its novel approaches are well poised to fundamentally shatter the glass ceilings imposed on traditionally underrepresented groups in medicine. The importance of diversity, equity, and inclusion (DEI) initiatives in healthcare has never been clearer,^23,24 particularly as they relate to cultural competence^25-28 and cultural humility,^29,30 implicit and explicit bias,²⁷ expanding care for underserved patient populations, supporting our workforce, and broadening research agendas.²⁸

In this article, we report DEI efforts within our division, focusing on the development of our strategic plan and specific outcomes related to compensation, recruitment, and policies.

Our Division’s Framework to DEI—“It Takes a Village”

Our Division of Hospital Medicine (DHM), previously within the Division of General Internal Medicine, was founded in October 2017. The DHM at the University of Colorado Hospital (UCH) is composed of 100 faculty members (70 physicians and 30 advanced-practice providers; 58% women and 42% men). In 2018, we implemented a stepwise approach to critically assess DEI within our group and to build a strategic plan to address the issues. Key areas of focus included institutional structures, our people, our environments, and our core missions (Figure 1 and Appendix Figure 1). DHM members helped drive our work and partnered with departmental, hospital, and school of medicine committees; national organizations; and collaborators to enhance implementation and dissemination efforts. In addition to stakeholder engagement, we utilized strategic planning and rapid Plan-Do-Study-Act (PDSA) cycles to advance DEI work in our DHM.

Needs Assessment

As a new division, we sought stakeholder feedback from division members. All faculty within the division were invited to attend a meeting in which issues related to DEI were discussed. A literature review that spanned both medical and nonmedical fields was also completed. Search terms included salary equity, gender equity, diverse teams, diversity recruitment and retention, diversifying leadership, and diverse speakers. Salaries, internally funded time, and other processes, such as recruitment, promotion, and hiring for leadership positions, were evaluated during the first year we became a division.

Interventions

TThrough this work, and with stakeholder engagement, we developed a divisional strategic plan to address DEI globally. Our strategic plan included developing a DEI director role to assist with overseeing DEI efforts. We have highlighted the various methods utilized for each component (Figure 1). This work occurred from October 2017 to December 2018.

Our institutional structures

Using best practices from both medical and nonmedical fields, we developed evidence-based approaches to compensation,³¹ recruitment,³² and policies that support and foster a culture of DEI.³² These strategies were used to support the following initiatives:

Compensation: transparent and consistent approaches based upon benchmarking with a framework of equal pay for equal work and similar advanced training/academic rank. In conjunction with efforts within the School of Medicine (SOM), Department of Medicine (DOM), and the UCH, our division sought to study salaries across DHM faculty members. We had an open call for faculty to participate in a newly developed DHM Compensation Committee, with the intent of rigorously examining our compensation practices and goals. Through faculty feedback and committee work, salary equity was defined as equal pay (ie, base salary for one clinical full-time equivalent [FTE]) for equal work based on academic rank and/or years of practice/advanced training. We also compared DHM salaries to regional academic hospital medicine groups and concluded that DHM salaries were lower than local and national benchmarks. This information was used to create a two-phase approach to increasing salaries for all individuals below the American Association of Medical Colleges (AAMC) benchmarks³³ for academic hospitalists. We also developed a stipend system for external roles that came with additional compensation and roles within our own division that came with additional pay (ie, nocturnist). Phase 1 focused on those whose salaries were furthest away from and below benchmark, and phase 2 targeted all remaining individuals below benchmark.

A similar review of FTEs (based on required number of shifts for a full-time hospitalist) tied to our internal DHM leadership positions was completed by the division head and director of DEI. Specifically, the mission for each of our internally funded roles, job descriptions, and responsibilities was reviewed to ensure equity in funding.

Recruitment and advancement: processes to ensure equity and diversity in recruitment, tracking, and reporting, working to eliminate/mitigate bias. In collaboration with members of the AAMC Group on Women in Medicine and Science (GWIMS) and coauthors from various institutions, we developed toolkits and checklists aimed at achieving equity and diversity within candidate pools and on major committees, including, but not limited to, search and promotion committees.³² Additionally, a checklist was developed to help recruit more diverse speakers, including women and URMs, for local, regional, and national conferences.

Policies: evidence-based approaches, tracking and reporting, standardized approaches to eliminate/mitigate bias, embracing nontraditional paths. In partnership with our departmental efforts, members of our team led data collection and reporting for salary benchmarking, leadership roles, and committee membership. This included developing surveys and reporting templates that can be used to identify disparities and inform future efforts. We worked to ensure that we have faculty representing our field at the department and SOM levels. Specifically, we made sure to nominate division members during open calls for departmental and schoolwide committees, including the promotions committee.

Our People

The faculty and staff within our division have been instrumental in moving efforts forward in the following important areas.

Leadership: develop the position of director of DEI as well as leadership structures to support and increase DEI. One of the first steps in our strategic plan was creating a director of DEI leadership role (Appendix Figure 2). The director is responsible for researching, applying, and promoting a broad scope of DEI initiatives and best practices within the DHM, DOM, and SOM (in collaboration with their leaders), including recruitment, retention, and promotion of medical students, residents, and faculty; educational program development; health disparities research; and community-engaged scholarship.

Support: develop family leave policies/develop flexible work policies. Several members of our division worked on departmental committees and served in leadership roles on staff and faculty council. Estimated costs were assessed. Through collective efforts of department leadership and division head support, the department approved parental leave to employees following the birth of an employee’s child or the placement of a child with an employee in connection with adoption or permanent foster care.

Mentorship/sponsorship: enhance faculty advancement programs/develop pipeline and trainings/collaborate with student groups and organizations/invest in all of our people. Faculty across our divisional sites have held important roles in developing pipeline programs for undergraduate students bound for health professions, as well as programs developed specifically for medical students and internal medicine residents. This includes two programs, the CU Hospitalist Scholars Program (CUHSP) and Leadership Education for Aspiring Doctors (LEAD), in which undergraduate students have the opportunity to round with hospital medicine teams, work on quality-improvement projects, and receive extensive mentorship and advising from a diverse faculty team. Additionally, our faculty advancement team within the DHM has grown and been restructured to include more defined goals and to ensure each faculty member has at least one mentor in their area of interest.

Supportive: lactation space and support/diverse space options/inclusive and diverse environments. We worked closely with hospital leadership to advocate for adequately equipped lactation spaces, including equipment such as pumps, refrigerators, and computer workstations. Additionally, our team members conducted environmental scans (eg, identified pictures, artwork, or other images that were not representative of a diverse and inclusive environment and raised concerns when the environment was not inclusive).

Measures

Our measures focused on (1) development and implementation of our DEI strategic plan, including new policies, processes, and practices related to key components of the DEI program; and (2) assessment of specific DEI programs, including pre-post salary data disparities based on rank and pre-post disparities for protected time for similar roles.

Analysis

Through rapid PDSA cycles, we evaluated salary equity, equity in leadership allotment, and committee membership. We have developed a tracking board to track progress of the multiple projects in the strategic plan.

Strategic Plan Development and Tracking

From October 2017 to December 2018, we developed a robust strategic plan and stepwise approach to DEI (Figure 1 and Figure 2). The director of DEI position was developed (see Appendix Figure 2 for job description) to help oversee these efforts. Figure 3 highlights the specific efforts and the progress made on implementation (ie, high-level dashboard or “tracking board”). While outcomes are still pending in the areas of recruitment and advancement and environment, we have made measurable improvements in compensation, as outlined in the following section.

Compensation

One year after the salary-equity interventions, all of our physician faculty’s salaries were at the goal benchmark (Table), and differences in salary for those in similar years of rank were nearly eliminated. Similarly, after implementing an internally consistent approach to assigning FTE for new and established positions within the division (ie, those that fall within the purview of the division), all faculty in similar types of roles had similar amounts of protected time.

Recruitment and Advancement

Toolkits³² and committee recommendations have been incorporated into division goals, though some aspects are still in implementation phases, as division-wide implicit bias training was delayed secondary to the COVID-19 pandemic. Key goals include: (1) implicit bias training for all members of major committees; (2) aiming for a goal of at least 40% representation of women and 40% URMs on committees; (3) having a diversity expert serve on each committee in order to identify and discuss any potential bias in the search and candidate-selection processes; and (4) careful tracking of diversity metrics in regard to diversity of candidates at each step of the interview and selection process.

Surveys and reporting templates for equity on committees and leadership positions have been developed and deployed. Data dashboards for our division have been developed as well (for compensation, leadership, and committee membership). A divisional dashboard to report recruitment efforts is in progress.

We have successfully nominated several faculty members to the SOM promotions committee and departmental committees during open calls for these positions. At the division level, we have also adapted internal policies to ensure promotion occurs on time and offers alternative pathways for faculty that may primarily focus on clinical pathways. All faculty who have gone up for promotion thus far have been successfully promoted in their desired pathway.

Environment

We successfully advocated and achieved adequately equipped lactation spaces, including equipment such as pumps, refrigerators, and computer workstations. This achievement was possible because of our hospital partners. Our efforts helped us acquire sufficient space and facilities such that nursing mothers can pump and still be able to answer phones, enter orders, and document visits.

Our team members conducted environmental scans and raised concerns when the environment was not inclusive, such as conference rooms with portraits of leadership that do not show diversity. The all-male pictures were removed from one frequently used departmental conference room, which will eventually house a diverse group of pictures and achievements.

We aim to eliminate bias by offering implicit bias training for our faculty. While this is presently required for those who serve on committees, in leadership positions, or those involved in recruitment and interviewing for the DOM, our goal is to eventually provide this training to all faculty and staff in the division. We have also incorporated DEI topics into our educational conferences for faculty, including sessions on recognizing bias in medicine, how to be an upstander/ally, and the impact of race and racism on medicine.

DISCUSSION

The important findings of this work are: (1) that successes in DEI can be achieved with strategic planning and stakeholder engagement; (2) through simple modification of processes, we can improve equity in compensation and FTE allotted to leadership; (3) though it takes time, diversity recruitment can be improved using sound, sustainable, evidence-based processes; (4) this work is time-intensive and challenging, requiring ongoing efforts to improve, modify, and enhance current efforts and future successes.

We have certainly made some progress with DEI initiatives within our division and have also learned a great deal from this experience. First, change is difficult for all parties involved, including those leading change and those affected by the changes. We purposely made an effort to facilitate discussions with all of the DHM faculty and staff to ensure that everyone felt included in this work and that everyone’s voice was heard. This was exemplified by inviting all faculty members to a feedback session in which we discussed DEI within our division and areas that we wanted to improve on. Early on, we were able to define what diversity, equity, and inclusion meant to us as a division and then use these definitions to develop tangible goals for all the areas of highest importance to the group.

By increasing faculty presence on key committees, such as the promotions committee, we now have faculty members who are well versed in promotions processes. We are fortunate to have a promotions process that supports faculty advancement for faculty with diverse interests that spans from supporting highly clinical faculty, clinician educators, as well as more traditional researchers.³⁴ By having hospitalists serve in these roles, we help to add to the diverse perspectives on these committees, including emphasizing the scholarship that is associated with quality improvement, as well as DEI efforts which can often be viewed as service as opposed to scholarship.

Clear communication and transparency were key to all of our DEI initiatives. We had monthly updates on our DEI efforts during business meetings and also held impromptu meetings (also known as flash mobs³⁵) to answer questions and discuss concerns in real time. As with all DEI work, it is important to know where you are starting (having accurate data and a clear understanding of the data) and be able to communicate that data to the group. For example, using AAMC salary benchmarking³³ as well as other benchmarks allowed us to accurately calculate variance among salaries and identify the appropriate goal salary for each of our faculty members. Likewise, by completing an in-depth inventory on the work being done by all of our faculty in leadership roles, we were able to standardize the compensation/FTE for each of these roles. Tracking these changes over time, via the use of dashboards in our case, allows for real-time measurements and accountability for all of those involved. Our end goal will be to have all of these initiatives feed into one large dashboard.

Collaborating with leadership and stakeholders in the DOM, SOM, and hospital helped to make our DEI initiatives successful. Much too often, we work in silos when it comes to DEI work. However, we tend to have similar goals and can achieve much more if we work together. Collaboration with multiple stakeholders allowed for wider dissemination and resulted in a larger impact to the campus and community at large. This has been exemplified by the committee composition guidance that has been utilized by the DOM, as well as implementation of campus-wide policies, specifically the parental leave policy, which our faculty members played an important role in creating. Likewise, it is important to look outside of our institutions and work with other hospital medicine groups around the country who are interested in promoting DEI.

We still have much work ahead of us. We are continuing to measure outcomes status postimplementation of the toolkit and checklists being used for diversity recruitment and committee composition. Additionally, we are actively working on several initiatives, including:

• Instituting implicit bias training for all of our faculty
• Partnering with national leaders and our hospital systems to develop zero-tolerance policies regarding abusive behaviors (verbal, physical, and other), racism, and sexism in the hospital and other work settings
• Development of specific recruitment strategies as a means of diversifying our healthcare workforce (of note, based on a 2020 survey of our faculty, in which there was a 70% response rate, 8.5% of our faculty identified as URMs)
• Completion of a diversity dashboard to track our progress in all of these efforts over time
• Development of a more robust pipeline to promotion and leadership for our URM faculty

This study has several strengths. Many of the plans and strategies described here can be used to guide others interested in implementing this work. Figure 2 provides a stepwise
approach to addressing DEI in hospital medicine groups and divisions. We conducted this work at a large academic medical center, and while it may not be generalizable, it does offer some ideas for others to consider in their own work to advance DEI at their institutions. There are also several limitations to this work. Eliminating salary inequities with our approach did take resources. We took advantage of already lower salaries and the need to increase salaries closer to benchmark and paired this effort with our DEI efforts to achieve salary equity. This required partnerships with the department and hospital. Efforts to advance DEI also take a lot of time and effort, and thus commitment from the division, department, and institution as a whole is key. While we have outcomes for our efforts related to salary equity, recruitment efforts should be realized over time, as currently it is too early to tell. We have highlighted the efforts that have been put in place at this time.

Using a systematic evidence-based approach with key stakeholder involvement, a division-wide DEI strategy was developed and implemented. While this work is still ongoing, short-term wins are possible, in particular around salary equity and development of policies and structures to promote DEI.

Studies continue to demonstrate persistent gaps in equity for women and underrepresented minorities (URMs)¹ throughout nearly all aspects of academic medicine, including rank,^2-4 tenure,⁵ authorship,^6,7 funding opportunities,^8,9 awards,¹⁰ speakership,¹¹ leadership,^12,13 and salaries.^2,14,15 Hospital medicine, despite being a newer field,¹⁶ has also seen these disparities^17,18; however, there are numerous efforts in place to actively change our specialty’s course.^19-22 Hospital medicine is a field known for being a change agent in healthcare delivery,²² and its novel approaches are well poised to fundamentally shatter the glass ceilings imposed on traditionally underrepresented groups in medicine. The importance of diversity, equity, and inclusion (DEI) initiatives in healthcare has never been clearer,^23,24 particularly as they relate to cultural competence^25-28 and cultural humility,^29,30 implicit and explicit bias,²⁷ expanding care for underserved patient populations, supporting our workforce, and broadening research agendas.²⁸

In this article, we report DEI efforts within our division, focusing on the development of our strategic plan and specific outcomes related to compensation, recruitment, and policies.

Our Division’s Framework to DEI—“It Takes a Village”

Our Division of Hospital Medicine (DHM), previously within the Division of General Internal Medicine, was founded in October 2017. The DHM at the University of Colorado Hospital (UCH) is composed of 100 faculty members (70 physicians and 30 advanced-practice providers; 58% women and 42% men). In 2018, we implemented a stepwise approach to critically assess DEI within our group and to build a strategic plan to address the issues. Key areas of focus included institutional structures, our people, our environments, and our core missions (Figure 1 and Appendix Figure 1). DHM members helped drive our work and partnered with departmental, hospital, and school of medicine committees; national organizations; and collaborators to enhance implementation and dissemination efforts. In addition to stakeholder engagement, we utilized strategic planning and rapid Plan-Do-Study-Act (PDSA) cycles to advance DEI work in our DHM.

Needs Assessment

As a new division, we sought stakeholder feedback from division members. All faculty within the division were invited to attend a meeting in which issues related to DEI were discussed. A literature review that spanned both medical and nonmedical fields was also completed. Search terms included salary equity, gender equity, diverse teams, diversity recruitment and retention, diversifying leadership, and diverse speakers. Salaries, internally funded time, and other processes, such as recruitment, promotion, and hiring for leadership positions, were evaluated during the first year we became a division.

Interventions

TThrough this work, and with stakeholder engagement, we developed a divisional strategic plan to address DEI globally. Our strategic plan included developing a DEI director role to assist with overseeing DEI efforts. We have highlighted the various methods utilized for each component (Figure 1). This work occurred from October 2017 to December 2018.

Our institutional structures

Using best practices from both medical and nonmedical fields, we developed evidence-based approaches to compensation,³¹ recruitment,³² and policies that support and foster a culture of DEI.³² These strategies were used to support the following initiatives:

Compensation: transparent and consistent approaches based upon benchmarking with a framework of equal pay for equal work and similar advanced training/academic rank. In conjunction with efforts within the School of Medicine (SOM), Department of Medicine (DOM), and the UCH, our division sought to study salaries across DHM faculty members. We had an open call for faculty to participate in a newly developed DHM Compensation Committee, with the intent of rigorously examining our compensation practices and goals. Through faculty feedback and committee work, salary equity was defined as equal pay (ie, base salary for one clinical full-time equivalent [FTE]) for equal work based on academic rank and/or years of practice/advanced training. We also compared DHM salaries to regional academic hospital medicine groups and concluded that DHM salaries were lower than local and national benchmarks. This information was used to create a two-phase approach to increasing salaries for all individuals below the American Association of Medical Colleges (AAMC) benchmarks³³ for academic hospitalists. We also developed a stipend system for external roles that came with additional compensation and roles within our own division that came with additional pay (ie, nocturnist). Phase 1 focused on those whose salaries were furthest away from and below benchmark, and phase 2 targeted all remaining individuals below benchmark.

A similar review of FTEs (based on required number of shifts for a full-time hospitalist) tied to our internal DHM leadership positions was completed by the division head and director of DEI. Specifically, the mission for each of our internally funded roles, job descriptions, and responsibilities was reviewed to ensure equity in funding.

Recruitment and advancement: processes to ensure equity and diversity in recruitment, tracking, and reporting, working to eliminate/mitigate bias. In collaboration with members of the AAMC Group on Women in Medicine and Science (GWIMS) and coauthors from various institutions, we developed toolkits and checklists aimed at achieving equity and diversity within candidate pools and on major committees, including, but not limited to, search and promotion committees.³² Additionally, a checklist was developed to help recruit more diverse speakers, including women and URMs, for local, regional, and national conferences.

Policies: evidence-based approaches, tracking and reporting, standardized approaches to eliminate/mitigate bias, embracing nontraditional paths. In partnership with our departmental efforts, members of our team led data collection and reporting for salary benchmarking, leadership roles, and committee membership. This included developing surveys and reporting templates that can be used to identify disparities and inform future efforts. We worked to ensure that we have faculty representing our field at the department and SOM levels. Specifically, we made sure to nominate division members during open calls for departmental and schoolwide committees, including the promotions committee.

Our People

The faculty and staff within our division have been instrumental in moving efforts forward in the following important areas.

Leadership: develop the position of director of DEI as well as leadership structures to support and increase DEI. One of the first steps in our strategic plan was creating a director of DEI leadership role (Appendix Figure 2). The director is responsible for researching, applying, and promoting a broad scope of DEI initiatives and best practices within the DHM, DOM, and SOM (in collaboration with their leaders), including recruitment, retention, and promotion of medical students, residents, and faculty; educational program development; health disparities research; and community-engaged scholarship.

Support: develop family leave policies/develop flexible work policies. Several members of our division worked on departmental committees and served in leadership roles on staff and faculty council. Estimated costs were assessed. Through collective efforts of department leadership and division head support, the department approved parental leave to employees following the birth of an employee’s child or the placement of a child with an employee in connection with adoption or permanent foster care.

Mentorship/sponsorship: enhance faculty advancement programs/develop pipeline and trainings/collaborate with student groups and organizations/invest in all of our people. Faculty across our divisional sites have held important roles in developing pipeline programs for undergraduate students bound for health professions, as well as programs developed specifically for medical students and internal medicine residents. This includes two programs, the CU Hospitalist Scholars Program (CUHSP) and Leadership Education for Aspiring Doctors (LEAD), in which undergraduate students have the opportunity to round with hospital medicine teams, work on quality-improvement projects, and receive extensive mentorship and advising from a diverse faculty team. Additionally, our faculty advancement team within the DHM has grown and been restructured to include more defined goals and to ensure each faculty member has at least one mentor in their area of interest.

Supportive: lactation space and support/diverse space options/inclusive and diverse environments. We worked closely with hospital leadership to advocate for adequately equipped lactation spaces, including equipment such as pumps, refrigerators, and computer workstations. Additionally, our team members conducted environmental scans (eg, identified pictures, artwork, or other images that were not representative of a diverse and inclusive environment and raised concerns when the environment was not inclusive).

Measures

Our measures focused on (1) development and implementation of our DEI strategic plan, including new policies, processes, and practices related to key components of the DEI program; and (2) assessment of specific DEI programs, including pre-post salary data disparities based on rank and pre-post disparities for protected time for similar roles.

Analysis

Through rapid PDSA cycles, we evaluated salary equity, equity in leadership allotment, and committee membership. We have developed a tracking board to track progress of the multiple projects in the strategic plan.

Strategic Plan Development and Tracking

From October 2017 to December 2018, we developed a robust strategic plan and stepwise approach to DEI (Figure 1 and Figure 2). The director of DEI position was developed (see Appendix Figure 2 for job description) to help oversee these efforts. Figure 3 highlights the specific efforts and the progress made on implementation (ie, high-level dashboard or “tracking board”). While outcomes are still pending in the areas of recruitment and advancement and environment, we have made measurable improvements in compensation, as outlined in the following section.

Compensation

One year after the salary-equity interventions, all of our physician faculty’s salaries were at the goal benchmark (Table), and differences in salary for those in similar years of rank were nearly eliminated. Similarly, after implementing an internally consistent approach to assigning FTE for new and established positions within the division (ie, those that fall within the purview of the division), all faculty in similar types of roles had similar amounts of protected time.

Recruitment and Advancement

Toolkits³² and committee recommendations have been incorporated into division goals, though some aspects are still in implementation phases, as division-wide implicit bias training was delayed secondary to the COVID-19 pandemic. Key goals include: (1) implicit bias training for all members of major committees; (2) aiming for a goal of at least 40% representation of women and 40% URMs on committees; (3) having a diversity expert serve on each committee in order to identify and discuss any potential bias in the search and candidate-selection processes; and (4) careful tracking of diversity metrics in regard to diversity of candidates at each step of the interview and selection process.

Surveys and reporting templates for equity on committees and leadership positions have been developed and deployed. Data dashboards for our division have been developed as well (for compensation, leadership, and committee membership). A divisional dashboard to report recruitment efforts is in progress.

We have successfully nominated several faculty members to the SOM promotions committee and departmental committees during open calls for these positions. At the division level, we have also adapted internal policies to ensure promotion occurs on time and offers alternative pathways for faculty that may primarily focus on clinical pathways. All faculty who have gone up for promotion thus far have been successfully promoted in their desired pathway.

Environment

We successfully advocated and achieved adequately equipped lactation spaces, including equipment such as pumps, refrigerators, and computer workstations. This achievement was possible because of our hospital partners. Our efforts helped us acquire sufficient space and facilities such that nursing mothers can pump and still be able to answer phones, enter orders, and document visits.

Our team members conducted environmental scans and raised concerns when the environment was not inclusive, such as conference rooms with portraits of leadership that do not show diversity. The all-male pictures were removed from one frequently used departmental conference room, which will eventually house a diverse group of pictures and achievements.

We aim to eliminate bias by offering implicit bias training for our faculty. While this is presently required for those who serve on committees, in leadership positions, or those involved in recruitment and interviewing for the DOM, our goal is to eventually provide this training to all faculty and staff in the division. We have also incorporated DEI topics into our educational conferences for faculty, including sessions on recognizing bias in medicine, how to be an upstander/ally, and the impact of race and racism on medicine.

DISCUSSION

The important findings of this work are: (1) that successes in DEI can be achieved with strategic planning and stakeholder engagement; (2) through simple modification of processes, we can improve equity in compensation and FTE allotted to leadership; (3) though it takes time, diversity recruitment can be improved using sound, sustainable, evidence-based processes; (4) this work is time-intensive and challenging, requiring ongoing efforts to improve, modify, and enhance current efforts and future successes.

We have certainly made some progress with DEI initiatives within our division and have also learned a great deal from this experience. First, change is difficult for all parties involved, including those leading change and those affected by the changes. We purposely made an effort to facilitate discussions with all of the DHM faculty and staff to ensure that everyone felt included in this work and that everyone’s voice was heard. This was exemplified by inviting all faculty members to a feedback session in which we discussed DEI within our division and areas that we wanted to improve on. Early on, we were able to define what diversity, equity, and inclusion meant to us as a division and then use these definitions to develop tangible goals for all the areas of highest importance to the group.

By increasing faculty presence on key committees, such as the promotions committee, we now have faculty members who are well versed in promotions processes. We are fortunate to have a promotions process that supports faculty advancement for faculty with diverse interests that spans from supporting highly clinical faculty, clinician educators, as well as more traditional researchers.³⁴ By having hospitalists serve in these roles, we help to add to the diverse perspectives on these committees, including emphasizing the scholarship that is associated with quality improvement, as well as DEI efforts which can often be viewed as service as opposed to scholarship.

Clear communication and transparency were key to all of our DEI initiatives. We had monthly updates on our DEI efforts during business meetings and also held impromptu meetings (also known as flash mobs³⁵) to answer questions and discuss concerns in real time. As with all DEI work, it is important to know where you are starting (having accurate data and a clear understanding of the data) and be able to communicate that data to the group. For example, using AAMC salary benchmarking³³ as well as other benchmarks allowed us to accurately calculate variance among salaries and identify the appropriate goal salary for each of our faculty members. Likewise, by completing an in-depth inventory on the work being done by all of our faculty in leadership roles, we were able to standardize the compensation/FTE for each of these roles. Tracking these changes over time, via the use of dashboards in our case, allows for real-time measurements and accountability for all of those involved. Our end goal will be to have all of these initiatives feed into one large dashboard.

Collaborating with leadership and stakeholders in the DOM, SOM, and hospital helped to make our DEI initiatives successful. Much too often, we work in silos when it comes to DEI work. However, we tend to have similar goals and can achieve much more if we work together. Collaboration with multiple stakeholders allowed for wider dissemination and resulted in a larger impact to the campus and community at large. This has been exemplified by the committee composition guidance that has been utilized by the DOM, as well as implementation of campus-wide policies, specifically the parental leave policy, which our faculty members played an important role in creating. Likewise, it is important to look outside of our institutions and work with other hospital medicine groups around the country who are interested in promoting DEI.

We still have much work ahead of us. We are continuing to measure outcomes status postimplementation of the toolkit and checklists being used for diversity recruitment and committee composition. Additionally, we are actively working on several initiatives, including:

• Instituting implicit bias training for all of our faculty
• Partnering with national leaders and our hospital systems to develop zero-tolerance policies regarding abusive behaviors (verbal, physical, and other), racism, and sexism in the hospital and other work settings
• Development of specific recruitment strategies as a means of diversifying our healthcare workforce (of note, based on a 2020 survey of our faculty, in which there was a 70% response rate, 8.5% of our faculty identified as URMs)
• Completion of a diversity dashboard to track our progress in all of these efforts over time
• Development of a more robust pipeline to promotion and leadership for our URM faculty

This study has several strengths. Many of the plans and strategies described here can be used to guide others interested in implementing this work. Figure 2 provides a stepwise
approach to addressing DEI in hospital medicine groups and divisions. We conducted this work at a large academic medical center, and while it may not be generalizable, it does offer some ideas for others to consider in their own work to advance DEI at their institutions. There are also several limitations to this work. Eliminating salary inequities with our approach did take resources. We took advantage of already lower salaries and the need to increase salaries closer to benchmark and paired this effort with our DEI efforts to achieve salary equity. This required partnerships with the department and hospital. Efforts to advance DEI also take a lot of time and effort, and thus commitment from the division, department, and institution as a whole is key. While we have outcomes for our efforts related to salary equity, recruitment efforts should be realized over time, as currently it is too early to tell. We have highlighted the efforts that have been put in place at this time.

Using a systematic evidence-based approach with key stakeholder involvement, a division-wide DEI strategy was developed and implemented. While this work is still ongoing, short-term wins are possible, in particular around salary equity and development of policies and structures to promote DEI.

Persistent gender disparities exist in pay,^1,2 leadership opportunities,^3,4 promotion,⁵ and speaking opportunities.⁶ While the gender distribution of the hospitalist workforce may be approaching parity,^3,7,8 gender differences in leadership, speakership, and authorship have already been noted in hospital medicine.³ Between 2006 and 2012, women constituted less than a third (26%) of the presenters at the national conferences of the Society of Hospital Medicine (SHM) and the Society of General Internal Medicine (SGIM).³

The SHM Annual Meeting has historically had an “open call” peer review process for workshop presenters with the goal of increasing the diversity of presenters. In 2019, this process was expanded to include didactic speakers. Our aim in this study was to assess whether these open call procedures resulted in improved representation of women speakers and how the proportion of women speakers affects the overall evaluation scores of the conference. Our hypothesis was that the introduction of an open call process for the SHM conference didactic speakers would be associated with an increased proportion of women speakers, compared with the closed call processes, without a negative impact on conference scores.

The study is a retrospective evaluation of data collected regarding speakers at the annual SHM conference from 2015 to 2019. The SHM national conference typically has two main types of offerings: workshops and didactics. Workshop presenters from 2015 to 2019 were selected via an open call process as defined below. Didactic speakers (except for plenary speakers) were selected using the open call process for 2019 only.

We aimed to compare (1) the number and proportion of women speakers, compared with men speakers, over time and (2) the proportion of women speakers when open call processes were utilized versus that seen with closed call processes. Open call included workshops for all years and didactics for 2019; closed call included didactics for 2015 to 2018 and plenary sessions 2015 to 2019 (Table). The speaker list for the conferences was obtained from conference pamphlets or agendas available via Internet searches or obtained through attendance at the conference.

Speaker Categories and Identification Process

We determined whether each individual was a featured speaker (one whose talk was unopposed by other sessions), plenary speaker (defined as such in the conference pamphlets), whether they spoke in a group format, and whether the speaking opportunity type was a workshop or a didactic session. Numbers of featured and plenary speakers were combined because of low numbers. SHM provided deidentified conference evaluation data for each year studied. For the purposes of this study, we analyzed all speakers which included physicians, advanced practice providers, and professionals such as nurses and other interdisciplinary team members. The same speaker could be included multiple times if they had multiple speaking opportunities.

Open Call Process

We defined the “open call process” (referred to as “open call” here forward) as the process utilized by SHM that includes the following two components: (1) advertisements to members of SHM and to the medical community at large through a variety of mechanisms including emails, websites, and social media outlets and (2) an online submission process that includes names of proposed speakers and their topic and, in the case of workshops, session objectives as well as an outline of the proposed workshop. SHM committees may also submit suggestions for topics and speakers. Annual Conference Committee members then review and rate submissions on the categories of topic, organization and clarity, objectives, and speaker qualifications (with a focus on institutional, geographic, and gender diversity). Scores are assigned from 1 to 5 (with 5 being the best score) for each category and a section for comments is available. All submissions are also evaluated by the course director.

After initial committee reviews, scores with marked reviewer discrepancies are rereviewed and discussed by the committee and course director. A cutoff score is then calculated with proposals falling below the cutoff threshold omitted from further consideration. Weekly calls are then focused on subcategories (ie tracks) with emphasis on clinical and educational content. Each of the tracks have a subcommittee with track leads to curate the best content first and then focus on final speaker selection. More recently, templates are shared with the track leads that include a location to call out gender and institutional diversity. Weekly calls are held to hone the content and determine the speakers.

For the purposes of this study, when the above process was not used, the authors refer to it as “closed call.” Closed call processes do not typically involve open invitations or a peer review process. (Table)

Gender

Gender was assigned based on the speaker’s self-identification by the pronouns used in their biography submitted to the conference or on their institutional website or other websites where the speaker was referenced. Persons using she/her/hers pronouns were noted as women and persons using he/him/his were noted as men. For the purposes of this study, we conceptualized gender as binary (ie woman/man) given the limited information we had from online sources.

REDCap, a secure, Web-based application for building and managing online survey and databases, was used to collect and manage all study data.⁹

All analyses were performed using SAS Enterprise Guide 8.1 (SAS Institute, Inc., Cary, North Carolina) using retrospectively collected data. A Cochran-Armitage test for trend was used to evaluate the proportion of women speakers from 2015 to 2019. A chi-square test was used to assess the proportion of women speakers for open call processes versus that seen with closed call. One-way analysis of variance (ANOVA) was used to evaluate annual conference evaluation scores from 2015 to 2019. Either numbers with proportions or means with standard deviations have been reported. Bonferroni’s correction for multiple comparisons was applied, with a P < .008 considered statistically significant.

Between 2015 and 2019, a total of 709 workshop and didactic presentations were given by 1,261 speakers at the annual Society of Hospital Medicine Conference. Of these, 505 (40%) were women; 756 (60%) were men. There were no missing data.

From 2015 to 2019, representation of women speakers increased from 35% of all speakers to 47% of all speakers (P = .0068). Women plenary speakers increased from 23% in 2015 to 45% in 2019 (P = .0396).

The proportion of women presenters for workshops (which have utilized an open call process throughout the study period), ranged from 43% to 53% from 2015 to 2019 with no statistically significant difference in gender distribution across years (Figure).

The important findings of this study are that there has been an increase in women speakers over the last 5 years at the annual Society of Hospital Medicine Conference, that women had higher representation as speakers when open call processes were followed, and that conference scores continued to improve during the time frame studied. These findings suggest that a systematic open call process helps to support equitable speaking opportunities for men and women at a national hospital medicine conference without a negative impact on conference quality.

To recruit more diverse speakers, open call and peer review processes were used in addition to deliberate efforts at ensuring diversity in speakers. We found that over time, the proportion of women with speaking opportunities increased from 2015 to 2019. Interestingly, workshops, which had open call processes in place for the duration of the study period, had almost equal numbers of men and women presenting in all years. We also found that the number of all-men speaking groups decreased between 2015 and 2019.

A single process change can impact gender equity, but the target of true equity is expected to require additional measures such as assessment of committee structures and diversity, checklists, and reporting structures (data analysis and plans when goals not achieved).^10-13 For instance, the American Society for Microbiology General Meeting was able to achieve gender equity in speakers by a multifold approach including ensuring the program committee was aware of gender statistics, increasing female representation among session convener teams, and direct instruction to try to avoid all-male sessions.¹¹

It is important to acknowledge that these processes do require valuable resources including time. SHM has historically used committee volunteers to conduct the peer review process with each committee member reviewing 20 to 30 workshop submissions and 30 to 50 didactic sessions. While open processes with peer review seem to generate improved gender equity, ensuring processes are in place during the selection process is also key.

Several recent notable efforts to enhance gender equity and to increase diversity have been proposed. One such example of a process that may further improve gender equity was proposed by editors at the Journal of Hospital Medicine to assess current representation via demographics including gender, race, and ethnicity of authors with plans to assess patterns in the coming years.¹⁴ The American College of Physicians also published a position paper on achieving gender equity with a recommendation that organizational policies and procedures should be implemented that address implicit bias.¹⁵

Our study showed that, from 2015 to 2019, conference evaluations saw a significant increase in the score concurrently with the rise in proportion of women speakers. This finding suggests that quality does not seem to be affected by this new methodology for speaker selection and in fact this methodology may actually help improve the overall quality of the conference. To our knowledge, this is one of the first studies to concurrently evaluate speaker gender equity with conference quality.

Our study offers several strengths. This study took a pragmatic approach to understanding how processes can impact gender equity, and we were able to take advantage of the evolution of the open call system (ie workshops which have been an open call process for the duration of the study versus speaking opportunities that were not).

Our study also has several limitations. First, this study is retrospective in nature and thus other processes could have contributed to the improved gender equity, such as an organization’s priorities over time. During this study period, the SHM conference saw an average 3% increase annually in women speakers and an increase of 8% from 2018 to 2019 for all speakers compared to national trends of approximately 1%,⁶ which suggests that the open call processes in place could be contributing to the overall increases seen. Similarly, because of the retrospective nature of the study, we cannot be certain that the improvements in conference scores were directly the result of improved gender equity, although it does suggest that the improvements in gender equity did not have an adverse impact on the scores. We also did not assess how the composition of selection committee members for the meeting could have impacted the overall composition of the speakers. Our study looked at diversity only from the perspective of gender in a binary fashion, and thus additional studies are needed to assess how to improve diversity overall. It is unclear how this new open call for speakers affects race and ethnic diversity specifically. Identifying gender for the purposes of this study was facilitated by speakers providing their own biographies and the respective pronouns used in those biographies, and thus gender was easier to ascertain than race and ethnicity, which are not as readily available. For organizations to understand their diversity, equity, and inclusion efforts, enhancing the ability to fairly track and measure diversity will be key. Lastly, understanding of the exact composition of hospitalists from both a gender and race/ethnicity perspective is lacking. Studies have suggested that, based upon those surveyed or studied, there is a fairly equal balance of men and women albeit in academic groups.³

An open call approach to speakers at a national hospitalist conference seems to have contributed to improvements regarding gender equity in speaking opportunities with a concurrent improvement in overall rating of the conference. The open call system is a potential mechanism that other institutions and organizations could employ to enhance their diversity efforts.

Acknowledgments

Society of Hospital Medicine Diversity, Equity, Inclusion Special Interest Group

Work Group for SPEAK UP: Marisha Burden, MD, Daniel Cabrera, MD, Amira del Pino-Jones, MD, Areeba Kara, MD, Angela Keniston, MSPH, Keshav Khanijow, MD, Flora Kisuule, MD, Chiara Mandel, Benji Mathews, MD, David Paje, MD, Stephan Papp, MD, Snehal Patel, MD, Suchita Shah Sata, MD, Dustin Smith, MD, Kevin Vuernick

Persistent gender disparities exist in pay,^1,2 leadership opportunities,^3,4 promotion,⁵ and speaking opportunities.⁶ While the gender distribution of the hospitalist workforce may be approaching parity,^3,7,8 gender differences in leadership, speakership, and authorship have already been noted in hospital medicine.³ Between 2006 and 2012, women constituted less than a third (26%) of the presenters at the national conferences of the Society of Hospital Medicine (SHM) and the Society of General Internal Medicine (SGIM).³

The SHM Annual Meeting has historically had an “open call” peer review process for workshop presenters with the goal of increasing the diversity of presenters. In 2019, this process was expanded to include didactic speakers. Our aim in this study was to assess whether these open call procedures resulted in improved representation of women speakers and how the proportion of women speakers affects the overall evaluation scores of the conference. Our hypothesis was that the introduction of an open call process for the SHM conference didactic speakers would be associated with an increased proportion of women speakers, compared with the closed call processes, without a negative impact on conference scores.

The study is a retrospective evaluation of data collected regarding speakers at the annual SHM conference from 2015 to 2019. The SHM national conference typically has two main types of offerings: workshops and didactics. Workshop presenters from 2015 to 2019 were selected via an open call process as defined below. Didactic speakers (except for plenary speakers) were selected using the open call process for 2019 only.

We aimed to compare (1) the number and proportion of women speakers, compared with men speakers, over time and (2) the proportion of women speakers when open call processes were utilized versus that seen with closed call processes. Open call included workshops for all years and didactics for 2019; closed call included didactics for 2015 to 2018 and plenary sessions 2015 to 2019 (Table). The speaker list for the conferences was obtained from conference pamphlets or agendas available via Internet searches or obtained through attendance at the conference.

Speaker Categories and Identification Process

We determined whether each individual was a featured speaker (one whose talk was unopposed by other sessions), plenary speaker (defined as such in the conference pamphlets), whether they spoke in a group format, and whether the speaking opportunity type was a workshop or a didactic session. Numbers of featured and plenary speakers were combined because of low numbers. SHM provided deidentified conference evaluation data for each year studied. For the purposes of this study, we analyzed all speakers which included physicians, advanced practice providers, and professionals such as nurses and other interdisciplinary team members. The same speaker could be included multiple times if they had multiple speaking opportunities.

Open Call Process

We defined the “open call process” (referred to as “open call” here forward) as the process utilized by SHM that includes the following two components: (1) advertisements to members of SHM and to the medical community at large through a variety of mechanisms including emails, websites, and social media outlets and (2) an online submission process that includes names of proposed speakers and their topic and, in the case of workshops, session objectives as well as an outline of the proposed workshop. SHM committees may also submit suggestions for topics and speakers. Annual Conference Committee members then review and rate submissions on the categories of topic, organization and clarity, objectives, and speaker qualifications (with a focus on institutional, geographic, and gender diversity). Scores are assigned from 1 to 5 (with 5 being the best score) for each category and a section for comments is available. All submissions are also evaluated by the course director.

After initial committee reviews, scores with marked reviewer discrepancies are rereviewed and discussed by the committee and course director. A cutoff score is then calculated with proposals falling below the cutoff threshold omitted from further consideration. Weekly calls are then focused on subcategories (ie tracks) with emphasis on clinical and educational content. Each of the tracks have a subcommittee with track leads to curate the best content first and then focus on final speaker selection. More recently, templates are shared with the track leads that include a location to call out gender and institutional diversity. Weekly calls are held to hone the content and determine the speakers.

For the purposes of this study, when the above process was not used, the authors refer to it as “closed call.” Closed call processes do not typically involve open invitations or a peer review process. (Table)

Gender

Gender was assigned based on the speaker’s self-identification by the pronouns used in their biography submitted to the conference or on their institutional website or other websites where the speaker was referenced. Persons using she/her/hers pronouns were noted as women and persons using he/him/his were noted as men. For the purposes of this study, we conceptualized gender as binary (ie woman/man) given the limited information we had from online sources.

REDCap, a secure, Web-based application for building and managing online survey and databases, was used to collect and manage all study data.⁹

All analyses were performed using SAS Enterprise Guide 8.1 (SAS Institute, Inc., Cary, North Carolina) using retrospectively collected data. A Cochran-Armitage test for trend was used to evaluate the proportion of women speakers from 2015 to 2019. A chi-square test was used to assess the proportion of women speakers for open call processes versus that seen with closed call. One-way analysis of variance (ANOVA) was used to evaluate annual conference evaluation scores from 2015 to 2019. Either numbers with proportions or means with standard deviations have been reported. Bonferroni’s correction for multiple comparisons was applied, with a P < .008 considered statistically significant.

Between 2015 and 2019, a total of 709 workshop and didactic presentations were given by 1,261 speakers at the annual Society of Hospital Medicine Conference. Of these, 505 (40%) were women; 756 (60%) were men. There were no missing data.

From 2015 to 2019, representation of women speakers increased from 35% of all speakers to 47% of all speakers (P = .0068). Women plenary speakers increased from 23% in 2015 to 45% in 2019 (P = .0396).

The proportion of women presenters for workshops (which have utilized an open call process throughout the study period), ranged from 43% to 53% from 2015 to 2019 with no statistically significant difference in gender distribution across years (Figure).

The important findings of this study are that there has been an increase in women speakers over the last 5 years at the annual Society of Hospital Medicine Conference, that women had higher representation as speakers when open call processes were followed, and that conference scores continued to improve during the time frame studied. These findings suggest that a systematic open call process helps to support equitable speaking opportunities for men and women at a national hospital medicine conference without a negative impact on conference quality.

To recruit more diverse speakers, open call and peer review processes were used in addition to deliberate efforts at ensuring diversity in speakers. We found that over time, the proportion of women with speaking opportunities increased from 2015 to 2019. Interestingly, workshops, which had open call processes in place for the duration of the study period, had almost equal numbers of men and women presenting in all years. We also found that the number of all-men speaking groups decreased between 2015 and 2019.

A single process change can impact gender equity, but the target of true equity is expected to require additional measures such as assessment of committee structures and diversity, checklists, and reporting structures (data analysis and plans when goals not achieved).^10-13 For instance, the American Society for Microbiology General Meeting was able to achieve gender equity in speakers by a multifold approach including ensuring the program committee was aware of gender statistics, increasing female representation among session convener teams, and direct instruction to try to avoid all-male sessions.¹¹

It is important to acknowledge that these processes do require valuable resources including time. SHM has historically used committee volunteers to conduct the peer review process with each committee member reviewing 20 to 30 workshop submissions and 30 to 50 didactic sessions. While open processes with peer review seem to generate improved gender equity, ensuring processes are in place during the selection process is also key.

Several recent notable efforts to enhance gender equity and to increase diversity have been proposed. One such example of a process that may further improve gender equity was proposed by editors at the Journal of Hospital Medicine to assess current representation via demographics including gender, race, and ethnicity of authors with plans to assess patterns in the coming years.¹⁴ The American College of Physicians also published a position paper on achieving gender equity with a recommendation that organizational policies and procedures should be implemented that address implicit bias.¹⁵

Our study showed that, from 2015 to 2019, conference evaluations saw a significant increase in the score concurrently with the rise in proportion of women speakers. This finding suggests that quality does not seem to be affected by this new methodology for speaker selection and in fact this methodology may actually help improve the overall quality of the conference. To our knowledge, this is one of the first studies to concurrently evaluate speaker gender equity with conference quality.

Our study offers several strengths. This study took a pragmatic approach to understanding how processes can impact gender equity, and we were able to take advantage of the evolution of the open call system (ie workshops which have been an open call process for the duration of the study versus speaking opportunities that were not).

Our study also has several limitations. First, this study is retrospective in nature and thus other processes could have contributed to the improved gender equity, such as an organization’s priorities over time. During this study period, the SHM conference saw an average 3% increase annually in women speakers and an increase of 8% from 2018 to 2019 for all speakers compared to national trends of approximately 1%,⁶ which suggests that the open call processes in place could be contributing to the overall increases seen. Similarly, because of the retrospective nature of the study, we cannot be certain that the improvements in conference scores were directly the result of improved gender equity, although it does suggest that the improvements in gender equity did not have an adverse impact on the scores. We also did not assess how the composition of selection committee members for the meeting could have impacted the overall composition of the speakers. Our study looked at diversity only from the perspective of gender in a binary fashion, and thus additional studies are needed to assess how to improve diversity overall. It is unclear how this new open call for speakers affects race and ethnic diversity specifically. Identifying gender for the purposes of this study was facilitated by speakers providing their own biographies and the respective pronouns used in those biographies, and thus gender was easier to ascertain than race and ethnicity, which are not as readily available. For organizations to understand their diversity, equity, and inclusion efforts, enhancing the ability to fairly track and measure diversity will be key. Lastly, understanding of the exact composition of hospitalists from both a gender and race/ethnicity perspective is lacking. Studies have suggested that, based upon those surveyed or studied, there is a fairly equal balance of men and women albeit in academic groups.³

An open call approach to speakers at a national hospitalist conference seems to have contributed to improvements regarding gender equity in speaking opportunities with a concurrent improvement in overall rating of the conference. The open call system is a potential mechanism that other institutions and organizations could employ to enhance their diversity efforts.

Acknowledgments

Society of Hospital Medicine Diversity, Equity, Inclusion Special Interest Group

Work Group for SPEAK UP: Marisha Burden, MD, Daniel Cabrera, MD, Amira del Pino-Jones, MD, Areeba Kara, MD, Angela Keniston, MSPH, Keshav Khanijow, MD, Flora Kisuule, MD, Chiara Mandel, Benji Mathews, MD, David Paje, MD, Stephan Papp, MD, Snehal Patel, MD, Suchita Shah Sata, MD, Dustin Smith, MD, Kevin Vuernick

Persistent gender disparities exist in pay,^1,2 leadership opportunities,^3,4 promotion,⁵ and speaking opportunities.⁶ While the gender distribution of the hospitalist workforce may be approaching parity,^3,7,8 gender differences in leadership, speakership, and authorship have already been noted in hospital medicine.³ Between 2006 and 2012, women constituted less than a third (26%) of the presenters at the national conferences of the Society of Hospital Medicine (SHM) and the Society of General Internal Medicine (SGIM).³

The SHM Annual Meeting has historically had an “open call” peer review process for workshop presenters with the goal of increasing the diversity of presenters. In 2019, this process was expanded to include didactic speakers. Our aim in this study was to assess whether these open call procedures resulted in improved representation of women speakers and how the proportion of women speakers affects the overall evaluation scores of the conference. Our hypothesis was that the introduction of an open call process for the SHM conference didactic speakers would be associated with an increased proportion of women speakers, compared with the closed call processes, without a negative impact on conference scores.

The study is a retrospective evaluation of data collected regarding speakers at the annual SHM conference from 2015 to 2019. The SHM national conference typically has two main types of offerings: workshops and didactics. Workshop presenters from 2015 to 2019 were selected via an open call process as defined below. Didactic speakers (except for plenary speakers) were selected using the open call process for 2019 only.

We aimed to compare (1) the number and proportion of women speakers, compared with men speakers, over time and (2) the proportion of women speakers when open call processes were utilized versus that seen with closed call processes. Open call included workshops for all years and didactics for 2019; closed call included didactics for 2015 to 2018 and plenary sessions 2015 to 2019 (Table). The speaker list for the conferences was obtained from conference pamphlets or agendas available via Internet searches or obtained through attendance at the conference.

Speaker Categories and Identification Process

We determined whether each individual was a featured speaker (one whose talk was unopposed by other sessions), plenary speaker (defined as such in the conference pamphlets), whether they spoke in a group format, and whether the speaking opportunity type was a workshop or a didactic session. Numbers of featured and plenary speakers were combined because of low numbers. SHM provided deidentified conference evaluation data for each year studied. For the purposes of this study, we analyzed all speakers which included physicians, advanced practice providers, and professionals such as nurses and other interdisciplinary team members. The same speaker could be included multiple times if they had multiple speaking opportunities.

Open Call Process

We defined the “open call process” (referred to as “open call” here forward) as the process utilized by SHM that includes the following two components: (1) advertisements to members of SHM and to the medical community at large through a variety of mechanisms including emails, websites, and social media outlets and (2) an online submission process that includes names of proposed speakers and their topic and, in the case of workshops, session objectives as well as an outline of the proposed workshop. SHM committees may also submit suggestions for topics and speakers. Annual Conference Committee members then review and rate submissions on the categories of topic, organization and clarity, objectives, and speaker qualifications (with a focus on institutional, geographic, and gender diversity). Scores are assigned from 1 to 5 (with 5 being the best score) for each category and a section for comments is available. All submissions are also evaluated by the course director.

After initial committee reviews, scores with marked reviewer discrepancies are rereviewed and discussed by the committee and course director. A cutoff score is then calculated with proposals falling below the cutoff threshold omitted from further consideration. Weekly calls are then focused on subcategories (ie tracks) with emphasis on clinical and educational content. Each of the tracks have a subcommittee with track leads to curate the best content first and then focus on final speaker selection. More recently, templates are shared with the track leads that include a location to call out gender and institutional diversity. Weekly calls are held to hone the content and determine the speakers.

For the purposes of this study, when the above process was not used, the authors refer to it as “closed call.” Closed call processes do not typically involve open invitations or a peer review process. (Table)

Gender

Gender was assigned based on the speaker’s self-identification by the pronouns used in their biography submitted to the conference or on their institutional website or other websites where the speaker was referenced. Persons using she/her/hers pronouns were noted as women and persons using he/him/his were noted as men. For the purposes of this study, we conceptualized gender as binary (ie woman/man) given the limited information we had from online sources.

REDCap, a secure, Web-based application for building and managing online survey and databases, was used to collect and manage all study data.⁹

All analyses were performed using SAS Enterprise Guide 8.1 (SAS Institute, Inc., Cary, North Carolina) using retrospectively collected data. A Cochran-Armitage test for trend was used to evaluate the proportion of women speakers from 2015 to 2019. A chi-square test was used to assess the proportion of women speakers for open call processes versus that seen with closed call. One-way analysis of variance (ANOVA) was used to evaluate annual conference evaluation scores from 2015 to 2019. Either numbers with proportions or means with standard deviations have been reported. Bonferroni’s correction for multiple comparisons was applied, with a P < .008 considered statistically significant.

Between 2015 and 2019, a total of 709 workshop and didactic presentations were given by 1,261 speakers at the annual Society of Hospital Medicine Conference. Of these, 505 (40%) were women; 756 (60%) were men. There were no missing data.

From 2015 to 2019, representation of women speakers increased from 35% of all speakers to 47% of all speakers (P = .0068). Women plenary speakers increased from 23% in 2015 to 45% in 2019 (P = .0396).

The proportion of women presenters for workshops (which have utilized an open call process throughout the study period), ranged from 43% to 53% from 2015 to 2019 with no statistically significant difference in gender distribution across years (Figure).

The important findings of this study are that there has been an increase in women speakers over the last 5 years at the annual Society of Hospital Medicine Conference, that women had higher representation as speakers when open call processes were followed, and that conference scores continued to improve during the time frame studied. These findings suggest that a systematic open call process helps to support equitable speaking opportunities for men and women at a national hospital medicine conference without a negative impact on conference quality.

To recruit more diverse speakers, open call and peer review processes were used in addition to deliberate efforts at ensuring diversity in speakers. We found that over time, the proportion of women with speaking opportunities increased from 2015 to 2019. Interestingly, workshops, which had open call processes in place for the duration of the study period, had almost equal numbers of men and women presenting in all years. We also found that the number of all-men speaking groups decreased between 2015 and 2019.

A single process change can impact gender equity, but the target of true equity is expected to require additional measures such as assessment of committee structures and diversity, checklists, and reporting structures (data analysis and plans when goals not achieved).^10-13 For instance, the American Society for Microbiology General Meeting was able to achieve gender equity in speakers by a multifold approach including ensuring the program committee was aware of gender statistics, increasing female representation among session convener teams, and direct instruction to try to avoid all-male sessions.¹¹

It is important to acknowledge that these processes do require valuable resources including time. SHM has historically used committee volunteers to conduct the peer review process with each committee member reviewing 20 to 30 workshop submissions and 30 to 50 didactic sessions. While open processes with peer review seem to generate improved gender equity, ensuring processes are in place during the selection process is also key.

Several recent notable efforts to enhance gender equity and to increase diversity have been proposed. One such example of a process that may further improve gender equity was proposed by editors at the Journal of Hospital Medicine to assess current representation via demographics including gender, race, and ethnicity of authors with plans to assess patterns in the coming years.¹⁴ The American College of Physicians also published a position paper on achieving gender equity with a recommendation that organizational policies and procedures should be implemented that address implicit bias.¹⁵

Our study showed that, from 2015 to 2019, conference evaluations saw a significant increase in the score concurrently with the rise in proportion of women speakers. This finding suggests that quality does not seem to be affected by this new methodology for speaker selection and in fact this methodology may actually help improve the overall quality of the conference. To our knowledge, this is one of the first studies to concurrently evaluate speaker gender equity with conference quality.

Our study offers several strengths. This study took a pragmatic approach to understanding how processes can impact gender equity, and we were able to take advantage of the evolution of the open call system (ie workshops which have been an open call process for the duration of the study versus speaking opportunities that were not).

Our study also has several limitations. First, this study is retrospective in nature and thus other processes could have contributed to the improved gender equity, such as an organization’s priorities over time. During this study period, the SHM conference saw an average 3% increase annually in women speakers and an increase of 8% from 2018 to 2019 for all speakers compared to national trends of approximately 1%,⁶ which suggests that the open call processes in place could be contributing to the overall increases seen. Similarly, because of the retrospective nature of the study, we cannot be certain that the improvements in conference scores were directly the result of improved gender equity, although it does suggest that the improvements in gender equity did not have an adverse impact on the scores. We also did not assess how the composition of selection committee members for the meeting could have impacted the overall composition of the speakers. Our study looked at diversity only from the perspective of gender in a binary fashion, and thus additional studies are needed to assess how to improve diversity overall. It is unclear how this new open call for speakers affects race and ethnic diversity specifically. Identifying gender for the purposes of this study was facilitated by speakers providing their own biographies and the respective pronouns used in those biographies, and thus gender was easier to ascertain than race and ethnicity, which are not as readily available. For organizations to understand their diversity, equity, and inclusion efforts, enhancing the ability to fairly track and measure diversity will be key. Lastly, understanding of the exact composition of hospitalists from both a gender and race/ethnicity perspective is lacking. Studies have suggested that, based upon those surveyed or studied, there is a fairly equal balance of men and women albeit in academic groups.³

An open call approach to speakers at a national hospitalist conference seems to have contributed to improvements regarding gender equity in speaking opportunities with a concurrent improvement in overall rating of the conference. The open call system is a potential mechanism that other institutions and organizations could employ to enhance their diversity efforts.

Acknowledgments

Society of Hospital Medicine Diversity, Equity, Inclusion Special Interest Group

Work Group for SPEAK UP: Marisha Burden, MD, Daniel Cabrera, MD, Amira del Pino-Jones, MD, Areeba Kara, MD, Angela Keniston, MSPH, Keshav Khanijow, MD, Flora Kisuule, MD, Chiara Mandel, Benji Mathews, MD, David Paje, MD, Stephan Papp, MD, Snehal Patel, MD, Suchita Shah Sata, MD, Dustin Smith, MD, Kevin Vuernick

Since 2000, the United States has seen a marked increase in opioid prescribing^1-3 and opioid-related complications, including overdoses, hospitalizations, and deaths.^2,4,5 A study from 2015 showed that more than one-third of the US civilian noninstitutionalized population reported receiving an opioid prescription in the prior year, with 12.5% reporting misuse, and, of those, 16.7% reported a prescription use disorder.⁶ While there has been a slight decrease in opioid prescriptions in the US since 2012, rates of opioid prescribing in 2015 were three times higher than in 1999 and approximately four times higher than in Europe in 2015.^3,7

Pain is commonly reported by hospitalized patients,^8,9 and opioids are often a mainstay of treatment;^9,10 however, treatment with opioids can have a number of adverse outcomes.^2,10,11 Short-term exposure to opioids can lead to long-term use,^12-16 and patients on opioids are at an increased risk for subsequent hospitalization and longer inpatient lengths of stay.⁵

Physician prescribing practices for opioids and patient expectations for pain control vary as a function of geographic region and culture,^10,12,17,18 and pain is influenced by the cultural context in which it occurs.^17,19-22 Treatment of pain may also be affected by limited access to or restrictions on selected medications, as well as by cultural biases.²³ Whether these variations in the treatment of pain are reflected in patients’ satisfaction with pain control is uncertain.

We sought to compare the inpatient analgesic prescribing practices and patients’ perceptions of pain control for medical patients in four teaching hospitals in the US and in seven teaching hospitals in seven other countries.

Study Design

We utilized a cross-sectional, observational design. The study was approved by the Institutional Review Boards at all participating sites.

Setting

The study was conducted at 11 academic hospitals in eight countries from October 8, 2013 to August 31, 2015. Sites in the US included Denver Health in Denver, Colorado; the University of Colorado Hospital in Aurora, Colorado; Hennepin Healthcare in Minneapolis, Minnesota; and Legacy Health in Portland, Oregon. Sites outside the US included McMaster University in Hamilton, Ontario, Canada; Hospital de la Santa Creu i Sant Pau, Universitat Autonòma de Barcelona in Barcelona, Spain; the University of Study of Milan and the University Ospedale “Luigi Sacco” in Milan, Italy, the National Taiwan University Hospital, in Taipei, Taiwan, the University of Ulsan College of Medicine, Asan Medical Center, in Seoul, Korea, the Imperial College, Chelsea and Westminster Hospital, in London, United Kingdom and Dunedin Hospital, Dunedin, New Zealand.

Inclusion and Exclusion Criteria

We included patients 18-89 years of age (20-89 in Taiwan because patients under 20 years of age in this country are a restricted group with respect to participating in research), admitted to an internal medicine service from the Emergency Department or Urgent Care clinic with an acute illness for a minimum of 24 hours (with time zero defined as the time care was initiated in the Emergency Department or Urgent Care Clinic), who reported pain at some time during the first 24-36 hours of their hospitalization and who provided informed consent. In the US, “admission” included both observation and inpatient status. We limited the patient population to those admitted via emergency departments and urgent care clinics in order to enroll similar patient populations across sites.

Scheduled admissions, patients transferred from an outside facility, patients admitted directly from a clinic, and those receiving care in intensive care units were excluded. We also excluded patients who were incarcerated, pregnant, those who received major surgery within the previous 14 days, those with a known diagnosis of active cancer, and those who were receiving palliative or hospice care. Patients receiving care from an investigator in the study at the time of enrollment were not eligible due to the potential conflict of interest.

Patient Screening

Primary teams were contacted to determine if any patients on their service might meet the criteria for inclusion in the study on preselected study days chosen on the basis of the research team’s availability. Identified patients were then screened to establish if they met the eligibility criteria. Patients were asked directly if they had experienced pain during their preadmission evaluation or during their hospitalization.

Data Collection

All patients were hospitalized at the time they gave consent and when data were collected. Data were collected via interviews with patients, as well as through chart review. We recorded patients’ age, gender, race, admitting diagnosis(es), length of stay, psychiatric illness, illicit drug use, whether they reported receiving opioid analgesics at the time of hospitalization, whether they were prescribed opioids and/or nonopioid analgesics during their hospitalization, the median and maximum doses of opioids prescribed and dispensed, and whether they were discharged on opioids. The question of illicit drug use was asked of all patients with the exception of those hospitalized in South Korea due to potential legal implications.

Opioid prescribing and receipt of opioids was recorded based upon current provider orders and medication administration records, respectively. Perception of and satisfaction with pain control was assessed with the American Pain Society Patient Outcome Questionnaire–Modified (APS-POQ-Modified).^24,25 Versions of this survey have been validated in English as well as in other languages and cultures.^26-28 Because hospitalization practices could differ across hospitals and in different countries, we compared patients’ severity of illness by using Charlson comorbidity scores. Consent forms and the APS-POQ were translated into each country’s primary language according to established processes.²⁹ The survey was filled out by having site investigators read questions aloud and by use of a large-font visual analog scale to aid patients’ verbal responses.

Data were collected and managed using a secure, web-based application electronic data capture tool (Research Electronic Data Capture [REDCap], Nashville, Tennessee), hosted at Denver Health.³⁰

Study Size

Preliminary data from the internal medicine units at our institution suggested that 40% of patients without cancer received opioid analgesics during their hospitalization. Assuming 90% power to detect an absolute difference in the proportion of inpatient medical patients who are receiving opioid analgesics during their hospital stay of 17%, a two-sided type 1 error rate of 0.05, six hospitals in the US, and nine hospitals from all other countries, we calculated an initial sample size of 150 patients per site. This sample size was considered feasible for enrollment in a busy inpatient clinical setting. Study end points were to either reach the goal number of patients (150 per site) or the predetermined study end date, whichever came first.

Data Analysis

We generated means with standard deviations (SDs) and medians with interquartile ranges (IQRs) for normally and nonnormally distributed continuous variables, respectively, and frequencies for categorical variables. We used linear mixed modeling for the analysis of continuous variables. For binary outcomes, our data were fitted to a generalized linear mixed model with logit as the link function and a binary distribution. For ordinal variables, specifically patient-reported satisfaction with pain control and the opinion statements, the data were fitted to a generalized linear mixed model with a cumulative logit link and a multinomial distribution. Hospital was included as a random effect in all models to account for patients cared for in the same hospital.

Country of origin, dichotomized as US or non-US, was the independent variable of interest for all models. An interaction term for exposure to opioids prior to admission and country was entered into all models to explore whether differences in the effect of country existed for patients who reported taking opioids prior to admission and those who did not.

The models for the frequency with which analgesics were given, doses of opioids given during hospitalization and at discharge, patient-reported pain score, and patient-reported satisfaction with pain control were adjusted for (1) age, (2) gender, (3) Charlson Comorbidity Index, (4) length of stay, (5) history of illicit drug use, (6) history of psychiatric illness, (7) daily dose in morphine milligram equivalents (MME) for opioids prior to admission, (8) average pain score, and (9) hospital. The patient-reported satisfaction with pain control model was also adjusted for whether or not opioids were given to the patient during their hospitalization. P < .05 was considered to indicate significance. All analyses were performed using SAS Enterprise Guide 7.1 (SAS Institute, Inc., Cary, North Carolina). We reported data on medications that were prescribed and dispensed (as opposed to just prescribed and not necessarily given). Opioids prescribed at discharge represented the total possible opioids that could be given based upon the order/prescription (eg, oxycodone 5 mg every 6 hours as needed for pain would be counted as 20 mg/24 hours maximum possible dose followed by conversion to MME).

Missing Data

When there were missing data, a query was sent to sites to verify if the data were retrievable. If retrievable, the data were then entered. Data were missing in 5% and 2% of patients who did or did not report taking an opioid prior to admission, respectively. If a variable was included in a specific statistical test, then subjects with missing data were excluded from that analysis (ie, complete case analysis).

We approached 1,309 eligible patients, of which 981 provided informed consent, for a response rate of 75%; 503 from the US and 478 patients from other countries (Figure). In unadjusted analyses, we found no significant differences between US and non-US patients in age (mean age 51, SD 15 vs 59, SD 19; P = .30), race, ethnicity, or Charlson comorbidity index scores (median 2, IQR 1-3 vs 3, IQR 1-4; P = .45). US patients had shorter lengths of stay (median 3 days, IQR 2-4 vs 6 days, IQR 3-11; P = .04), a more frequent history of illicit drug use (33% vs 6%; P = .003), a higher frequency of psychiatric illness (27% vs 8%; P < .0001), and more were receiving opioid analgesics prior to admission (38% vs 17%; P = .007) than those hospitalized in other countries (Table 1, Appendix 1). The primary admitting diagnoses for all patients in the study are listed in Appendix 2. Opioid prescribing practices across the individual sites are shown in Appendix 3.

Patients Taking Opioids Prior to Admission

After adjusting for relevant covariates, we found that more patients in the US were given opioids during their hospitalization and in higher doses than patients from other countries and more were prescribed opioids at discharge. Fewer patients in the US were dispensed nonopioid analgesics during their hospitalization than patients from other countries, but this difference was not significant (Table 2). Appendix 4 shows the types of nonopioid pain medications prescribed in the US and other countries.

After adjustment for relevant covariates, US patients reported greater pain severity at the time they completed their pain surveys. We found no significant difference in satisfaction with pain control between patients from the US and other countries in the models, regardless of whether we included average pain score or opioid receipt during hospitalization in the model (Table 3).

In unadjusted analyses, compared with patients hospitalized in other countries, more patients in the US stated that they would like a stronger dose of analgesic if they were still in pain, though the difference was nonsignificant, and US patients were more likely to agree with the statement that people become addicted to pain medication easily and less likely to agree with the statement that it is easier to endure pain than deal with the side effects of pain medications (Table 3).

Patients Not Taking Opioids Prior to Admission

After adjusting for relevant covariates, we found no significant difference in the proportion of US patients provided with nonopioid pain medications during their hospitalization compared with patients in other countries, but a greater percentage of US patients were given opioids during their hospitalization and at discharge and in higher doses (Table 2).

After adjusting for relevant covariates, US patients reported greater pain severity at the time they completed their pain surveys and greater pain severity in the 24-36 hours prior to completing the survey than patients from other countries, but we found no difference in patient satisfaction with pain control (Table 3). After we included the average pain score and whether or not opioids were given to the patient during their hospitalization in this model, patients in the US were more likely to report a higher level of satisfaction with pain control than patients in all other countries (P = .001).

Patient Satisfaction and Opioid Receipt

Among patients cared for in the US, after controlling for the average pain score, we did not find a significant association between receiving opioids while in the hospital and satisfaction with pain control for patients who either did or did not endorse taking opioids prior to admission (P = .38 and P = .24, respectively). Among patients cared for in all other countries, after controlling for the average pain score, we found a significant association between receiving opioids while in the hospital and a lower level of satisfaction with pain control for patients who reported taking opioids prior to admission (P = .02) but not for patients who did not report taking opioids prior to admission (P = .08).

Compared with patients hospitalized in other countries, a greater percentage of those hospitalized in the US were prescribed opioid analgesics both during hospitalization and at the time of discharge, even after adjustment for pain severity. In addition, patients hospitalized in the US reported greater pain severity at the time they completed their pain surveys and in the 24 to 36 hours prior to completing the survey than patients from other countries. In this sample, satisfaction, beliefs, and expectations about pain control differed between patients in the US and other sites. Our study also suggests that opioid receipt did not lead to improved patient satisfaction with pain control.

The frequency with which we observed opioid analgesics being prescribed during hospitalization in US hospitals (79%) was higher than the 51% of patients who received opioids reported by Herzig and colleagues.¹⁰ Patients in our study had a higher prevalence of illicit drug abuse and psychiatric illness, and our study only included patients who reported pain at some point during their hospitalization. We also studied prescribing practices through analysis of provider orders and medication administration records at the time the patient was hospitalized.

While we observed that physicians in the US more frequently prescribed opioid analgesics during hospitalizations than physicians working in other countries, we also observed that patients in the US reported higher levels of pain during their hospitalization. After adjusting for a number of variables, including pain severity, however, we still found that opioids were more commonly prescribed during hospitalizations by physicians working in the US sites studied than by physicians in the non-US sites.

Opioid prescribing practices varied across the sites sampled in our study. While the US sites, Taiwan, and Korea tended to be heavier utilizers of opioids during hospitalization, there were notable differences in discharge prescribing of opioids, with the US sites more commonly prescribing opioids and higher MME for patients who did not report taking opioids prior to their hospitalization (Appendix 3). A sensitivity analysis was conducted excluding South Korea from modeling, given that patients there were not asked about illicit opioid use. There were no important changes in the magnitude or direction of the results.

Our study supports previous studies indicating that there are cultural and societal differences when it comes to the experience of pain and the expectations around pain control.^17,20-22,31 Much of the focus on reducing opioid utilization has been on provider practices³² and on prescription drug monitoring programs.³³ Our findings suggest that another area of focus that may be important in mitigating the opioid epidemic is patient expectations of pain control.

Our study has a number of strengths. First, we included 11 hospitals from eight different countries. Second, we believe this is the first study to assess opioid prescribing and dispensing practices during hospitalization as well as at the time of discharge. Third, patient perceptions of pain control were assessed in conjunction with analgesic prescribing and were assessed during hospitalization. Fourth, we had high response rates for patient participation in our study. Fifth, we found much larger differences in opioid prescribing than anticipated, and thus, while we did not achieve the sample size originally planned for either the number of hospitals or patients enrolled per hospital, we were sufficiently powered. This is likely secondary to the fact that the population we studied was one that specifically reported pain, resulting in the larger differences seen.

Our study also had a number of limitations. First, the prescribing practices in countries other than the US are represented by only one hospital per country and, in some countries, by limited numbers of patients. While we studied four sites in the US, we did not have a site in the Northeast, a region previously shown to have lower prescribing rates.¹⁰ Additionally, patient samples for the US sites compared with the sites in other countries varied considerably with respect to ethnicity. While some studies in US patients have shown that opioid prescribing may vary based on race/ethnicity,³⁴ we are uncertain as to how this might impact a study that crosses multiple countries. We also had a low number of patients receiving opioids prior to hospitalization for several of the non-US countries, which reduced the power to detect differences in this subgroup. Previous research has shown that there are wide variations in prescribing practices even within countries;^10,12,18 therefore, caution should be taken when generalizing our findings. Second, we assessed analgesic prescribing patterns and pain control during the first 24 to 36 hours of hospitalization and did not consider hospital days beyond this timeframe with the exception of noting what medications were prescribed at discharge. We chose this methodology in an attempt to eliminate as many differences that might exist in the duration of hospitalization across many countries. Third, investigators in the study administered the survey, and respondents may have been affected by social desirability bias in how the survey questions were answered. Because investigators were not a part of the care team of any study patients, we believe this to be unlikely. Fourth, our study was conducted from October 8, 2013 to August 31, 2015 and the opioid epidemic is dynamic. Accordingly, our data may not reflect current opioid prescribing practices or patients’ current beliefs regarding pain control. Fifth, we did not collect demographic data on the patients who did not participate and could not look for systematic differences between participants and nonparticipants. Sixth, we relied on patients to self-report whether they were taking opioids prior to hospitalization or using illicit drugs. Seventh, we found comorbid mental health conditions to be more frequent in the US population studied. Previous work has shown regional variation in mental health conditions,^35,36 which could have affected our findings. To account for this, our models included psychiatric illness.

Our data suggest that physicians in the US may prescribe opioids more frequently during patients’ hospitalizations and at discharge than their colleagues in other countries. We also found that patient satisfaction, beliefs, and expectations about pain control differed between patients in the US and other sites. Although the small number of hospitals included in our sample coupled with the small sample size in some of the non-US countries limits the generalizability of our findings, the data suggest that reducing the opioid epidemic in the US may require addressing patients’ expectations regarding pain control in addition to providers’ inpatient analgesic prescribing patterns.

Disclosures

The authors report no conflicts of interest.

Funding

The authors report no funding source for this work.

Since 2000, the United States has seen a marked increase in opioid prescribing^1-3 and opioid-related complications, including overdoses, hospitalizations, and deaths.^2,4,5 A study from 2015 showed that more than one-third of the US civilian noninstitutionalized population reported receiving an opioid prescription in the prior year, with 12.5% reporting misuse, and, of those, 16.7% reported a prescription use disorder.⁶ While there has been a slight decrease in opioid prescriptions in the US since 2012, rates of opioid prescribing in 2015 were three times higher than in 1999 and approximately four times higher than in Europe in 2015.^3,7

Pain is commonly reported by hospitalized patients,^8,9 and opioids are often a mainstay of treatment;^9,10 however, treatment with opioids can have a number of adverse outcomes.^2,10,11 Short-term exposure to opioids can lead to long-term use,^12-16 and patients on opioids are at an increased risk for subsequent hospitalization and longer inpatient lengths of stay.⁵

Physician prescribing practices for opioids and patient expectations for pain control vary as a function of geographic region and culture,^10,12,17,18 and pain is influenced by the cultural context in which it occurs.^17,19-22 Treatment of pain may also be affected by limited access to or restrictions on selected medications, as well as by cultural biases.²³ Whether these variations in the treatment of pain are reflected in patients’ satisfaction with pain control is uncertain.

We sought to compare the inpatient analgesic prescribing practices and patients’ perceptions of pain control for medical patients in four teaching hospitals in the US and in seven teaching hospitals in seven other countries.

Study Design

We utilized a cross-sectional, observational design. The study was approved by the Institutional Review Boards at all participating sites.

Setting

The study was conducted at 11 academic hospitals in eight countries from October 8, 2013 to August 31, 2015. Sites in the US included Denver Health in Denver, Colorado; the University of Colorado Hospital in Aurora, Colorado; Hennepin Healthcare in Minneapolis, Minnesota; and Legacy Health in Portland, Oregon. Sites outside the US included McMaster University in Hamilton, Ontario, Canada; Hospital de la Santa Creu i Sant Pau, Universitat Autonòma de Barcelona in Barcelona, Spain; the University of Study of Milan and the University Ospedale “Luigi Sacco” in Milan, Italy, the National Taiwan University Hospital, in Taipei, Taiwan, the University of Ulsan College of Medicine, Asan Medical Center, in Seoul, Korea, the Imperial College, Chelsea and Westminster Hospital, in London, United Kingdom and Dunedin Hospital, Dunedin, New Zealand.

Inclusion and Exclusion Criteria

We included patients 18-89 years of age (20-89 in Taiwan because patients under 20 years of age in this country are a restricted group with respect to participating in research), admitted to an internal medicine service from the Emergency Department or Urgent Care clinic with an acute illness for a minimum of 24 hours (with time zero defined as the time care was initiated in the Emergency Department or Urgent Care Clinic), who reported pain at some time during the first 24-36 hours of their hospitalization and who provided informed consent. In the US, “admission” included both observation and inpatient status. We limited the patient population to those admitted via emergency departments and urgent care clinics in order to enroll similar patient populations across sites.

Scheduled admissions, patients transferred from an outside facility, patients admitted directly from a clinic, and those receiving care in intensive care units were excluded. We also excluded patients who were incarcerated, pregnant, those who received major surgery within the previous 14 days, those with a known diagnosis of active cancer, and those who were receiving palliative or hospice care. Patients receiving care from an investigator in the study at the time of enrollment were not eligible due to the potential conflict of interest.

Patient Screening

Primary teams were contacted to determine if any patients on their service might meet the criteria for inclusion in the study on preselected study days chosen on the basis of the research team’s availability. Identified patients were then screened to establish if they met the eligibility criteria. Patients were asked directly if they had experienced pain during their preadmission evaluation or during their hospitalization.

Data Collection

All patients were hospitalized at the time they gave consent and when data were collected. Data were collected via interviews with patients, as well as through chart review. We recorded patients’ age, gender, race, admitting diagnosis(es), length of stay, psychiatric illness, illicit drug use, whether they reported receiving opioid analgesics at the time of hospitalization, whether they were prescribed opioids and/or nonopioid analgesics during their hospitalization, the median and maximum doses of opioids prescribed and dispensed, and whether they were discharged on opioids. The question of illicit drug use was asked of all patients with the exception of those hospitalized in South Korea due to potential legal implications.

Opioid prescribing and receipt of opioids was recorded based upon current provider orders and medication administration records, respectively. Perception of and satisfaction with pain control was assessed with the American Pain Society Patient Outcome Questionnaire–Modified (APS-POQ-Modified).^24,25 Versions of this survey have been validated in English as well as in other languages and cultures.^26-28 Because hospitalization practices could differ across hospitals and in different countries, we compared patients’ severity of illness by using Charlson comorbidity scores. Consent forms and the APS-POQ were translated into each country’s primary language according to established processes.²⁹ The survey was filled out by having site investigators read questions aloud and by use of a large-font visual analog scale to aid patients’ verbal responses.

Data were collected and managed using a secure, web-based application electronic data capture tool (Research Electronic Data Capture [REDCap], Nashville, Tennessee), hosted at Denver Health.³⁰

Study Size

Preliminary data from the internal medicine units at our institution suggested that 40% of patients without cancer received opioid analgesics during their hospitalization. Assuming 90% power to detect an absolute difference in the proportion of inpatient medical patients who are receiving opioid analgesics during their hospital stay of 17%, a two-sided type 1 error rate of 0.05, six hospitals in the US, and nine hospitals from all other countries, we calculated an initial sample size of 150 patients per site. This sample size was considered feasible for enrollment in a busy inpatient clinical setting. Study end points were to either reach the goal number of patients (150 per site) or the predetermined study end date, whichever came first.

Data Analysis

We generated means with standard deviations (SDs) and medians with interquartile ranges (IQRs) for normally and nonnormally distributed continuous variables, respectively, and frequencies for categorical variables. We used linear mixed modeling for the analysis of continuous variables. For binary outcomes, our data were fitted to a generalized linear mixed model with logit as the link function and a binary distribution. For ordinal variables, specifically patient-reported satisfaction with pain control and the opinion statements, the data were fitted to a generalized linear mixed model with a cumulative logit link and a multinomial distribution. Hospital was included as a random effect in all models to account for patients cared for in the same hospital.

Country of origin, dichotomized as US or non-US, was the independent variable of interest for all models. An interaction term for exposure to opioids prior to admission and country was entered into all models to explore whether differences in the effect of country existed for patients who reported taking opioids prior to admission and those who did not.

The models for the frequency with which analgesics were given, doses of opioids given during hospitalization and at discharge, patient-reported pain score, and patient-reported satisfaction with pain control were adjusted for (1) age, (2) gender, (3) Charlson Comorbidity Index, (4) length of stay, (5) history of illicit drug use, (6) history of psychiatric illness, (7) daily dose in morphine milligram equivalents (MME) for opioids prior to admission, (8) average pain score, and (9) hospital. The patient-reported satisfaction with pain control model was also adjusted for whether or not opioids were given to the patient during their hospitalization. P < .05 was considered to indicate significance. All analyses were performed using SAS Enterprise Guide 7.1 (SAS Institute, Inc., Cary, North Carolina). We reported data on medications that were prescribed and dispensed (as opposed to just prescribed and not necessarily given). Opioids prescribed at discharge represented the total possible opioids that could be given based upon the order/prescription (eg, oxycodone 5 mg every 6 hours as needed for pain would be counted as 20 mg/24 hours maximum possible dose followed by conversion to MME).

Missing Data

When there were missing data, a query was sent to sites to verify if the data were retrievable. If retrievable, the data were then entered. Data were missing in 5% and 2% of patients who did or did not report taking an opioid prior to admission, respectively. If a variable was included in a specific statistical test, then subjects with missing data were excluded from that analysis (ie, complete case analysis).

We approached 1,309 eligible patients, of which 981 provided informed consent, for a response rate of 75%; 503 from the US and 478 patients from other countries (Figure). In unadjusted analyses, we found no significant differences between US and non-US patients in age (mean age 51, SD 15 vs 59, SD 19; P = .30), race, ethnicity, or Charlson comorbidity index scores (median 2, IQR 1-3 vs 3, IQR 1-4; P = .45). US patients had shorter lengths of stay (median 3 days, IQR 2-4 vs 6 days, IQR 3-11; P = .04), a more frequent history of illicit drug use (33% vs 6%; P = .003), a higher frequency of psychiatric illness (27% vs 8%; P < .0001), and more were receiving opioid analgesics prior to admission (38% vs 17%; P = .007) than those hospitalized in other countries (Table 1, Appendix 1). The primary admitting diagnoses for all patients in the study are listed in Appendix 2. Opioid prescribing practices across the individual sites are shown in Appendix 3.

Patients Taking Opioids Prior to Admission

After adjusting for relevant covariates, we found that more patients in the US were given opioids during their hospitalization and in higher doses than patients from other countries and more were prescribed opioids at discharge. Fewer patients in the US were dispensed nonopioid analgesics during their hospitalization than patients from other countries, but this difference was not significant (Table 2). Appendix 4 shows the types of nonopioid pain medications prescribed in the US and other countries.

After adjustment for relevant covariates, US patients reported greater pain severity at the time they completed their pain surveys. We found no significant difference in satisfaction with pain control between patients from the US and other countries in the models, regardless of whether we included average pain score or opioid receipt during hospitalization in the model (Table 3).

In unadjusted analyses, compared with patients hospitalized in other countries, more patients in the US stated that they would like a stronger dose of analgesic if they were still in pain, though the difference was nonsignificant, and US patients were more likely to agree with the statement that people become addicted to pain medication easily and less likely to agree with the statement that it is easier to endure pain than deal with the side effects of pain medications (Table 3).

Patients Not Taking Opioids Prior to Admission

After adjusting for relevant covariates, we found no significant difference in the proportion of US patients provided with nonopioid pain medications during their hospitalization compared with patients in other countries, but a greater percentage of US patients were given opioids during their hospitalization and at discharge and in higher doses (Table 2).

After adjusting for relevant covariates, US patients reported greater pain severity at the time they completed their pain surveys and greater pain severity in the 24-36 hours prior to completing the survey than patients from other countries, but we found no difference in patient satisfaction with pain control (Table 3). After we included the average pain score and whether or not opioids were given to the patient during their hospitalization in this model, patients in the US were more likely to report a higher level of satisfaction with pain control than patients in all other countries (P = .001).

Patient Satisfaction and Opioid Receipt

Among patients cared for in the US, after controlling for the average pain score, we did not find a significant association between receiving opioids while in the hospital and satisfaction with pain control for patients who either did or did not endorse taking opioids prior to admission (P = .38 and P = .24, respectively). Among patients cared for in all other countries, after controlling for the average pain score, we found a significant association between receiving opioids while in the hospital and a lower level of satisfaction with pain control for patients who reported taking opioids prior to admission (P = .02) but not for patients who did not report taking opioids prior to admission (P = .08).

Compared with patients hospitalized in other countries, a greater percentage of those hospitalized in the US were prescribed opioid analgesics both during hospitalization and at the time of discharge, even after adjustment for pain severity. In addition, patients hospitalized in the US reported greater pain severity at the time they completed their pain surveys and in the 24 to 36 hours prior to completing the survey than patients from other countries. In this sample, satisfaction, beliefs, and expectations about pain control differed between patients in the US and other sites. Our study also suggests that opioid receipt did not lead to improved patient satisfaction with pain control.

The frequency with which we observed opioid analgesics being prescribed during hospitalization in US hospitals (79%) was higher than the 51% of patients who received opioids reported by Herzig and colleagues.¹⁰ Patients in our study had a higher prevalence of illicit drug abuse and psychiatric illness, and our study only included patients who reported pain at some point during their hospitalization. We also studied prescribing practices through analysis of provider orders and medication administration records at the time the patient was hospitalized.

While we observed that physicians in the US more frequently prescribed opioid analgesics during hospitalizations than physicians working in other countries, we also observed that patients in the US reported higher levels of pain during their hospitalization. After adjusting for a number of variables, including pain severity, however, we still found that opioids were more commonly prescribed during hospitalizations by physicians working in the US sites studied than by physicians in the non-US sites.

Opioid prescribing practices varied across the sites sampled in our study. While the US sites, Taiwan, and Korea tended to be heavier utilizers of opioids during hospitalization, there were notable differences in discharge prescribing of opioids, with the US sites more commonly prescribing opioids and higher MME for patients who did not report taking opioids prior to their hospitalization (Appendix 3). A sensitivity analysis was conducted excluding South Korea from modeling, given that patients there were not asked about illicit opioid use. There were no important changes in the magnitude or direction of the results.

Our study supports previous studies indicating that there are cultural and societal differences when it comes to the experience of pain and the expectations around pain control.^17,20-22,31 Much of the focus on reducing opioid utilization has been on provider practices³² and on prescription drug monitoring programs.³³ Our findings suggest that another area of focus that may be important in mitigating the opioid epidemic is patient expectations of pain control.

Our study has a number of strengths. First, we included 11 hospitals from eight different countries. Second, we believe this is the first study to assess opioid prescribing and dispensing practices during hospitalization as well as at the time of discharge. Third, patient perceptions of pain control were assessed in conjunction with analgesic prescribing and were assessed during hospitalization. Fourth, we had high response rates for patient participation in our study. Fifth, we found much larger differences in opioid prescribing than anticipated, and thus, while we did not achieve the sample size originally planned for either the number of hospitals or patients enrolled per hospital, we were sufficiently powered. This is likely secondary to the fact that the population we studied was one that specifically reported pain, resulting in the larger differences seen.

Our study also had a number of limitations. First, the prescribing practices in countries other than the US are represented by only one hospital per country and, in some countries, by limited numbers of patients. While we studied four sites in the US, we did not have a site in the Northeast, a region previously shown to have lower prescribing rates.¹⁰ Additionally, patient samples for the US sites compared with the sites in other countries varied considerably with respect to ethnicity. While some studies in US patients have shown that opioid prescribing may vary based on race/ethnicity,³⁴ we are uncertain as to how this might impact a study that crosses multiple countries. We also had a low number of patients receiving opioids prior to hospitalization for several of the non-US countries, which reduced the power to detect differences in this subgroup. Previous research has shown that there are wide variations in prescribing practices even within countries;^10,12,18 therefore, caution should be taken when generalizing our findings. Second, we assessed analgesic prescribing patterns and pain control during the first 24 to 36 hours of hospitalization and did not consider hospital days beyond this timeframe with the exception of noting what medications were prescribed at discharge. We chose this methodology in an attempt to eliminate as many differences that might exist in the duration of hospitalization across many countries. Third, investigators in the study administered the survey, and respondents may have been affected by social desirability bias in how the survey questions were answered. Because investigators were not a part of the care team of any study patients, we believe this to be unlikely. Fourth, our study was conducted from October 8, 2013 to August 31, 2015 and the opioid epidemic is dynamic. Accordingly, our data may not reflect current opioid prescribing practices or patients’ current beliefs regarding pain control. Fifth, we did not collect demographic data on the patients who did not participate and could not look for systematic differences between participants and nonparticipants. Sixth, we relied on patients to self-report whether they were taking opioids prior to hospitalization or using illicit drugs. Seventh, we found comorbid mental health conditions to be more frequent in the US population studied. Previous work has shown regional variation in mental health conditions,^35,36 which could have affected our findings. To account for this, our models included psychiatric illness.

Our data suggest that physicians in the US may prescribe opioids more frequently during patients’ hospitalizations and at discharge than their colleagues in other countries. We also found that patient satisfaction, beliefs, and expectations about pain control differed between patients in the US and other sites. Although the small number of hospitals included in our sample coupled with the small sample size in some of the non-US countries limits the generalizability of our findings, the data suggest that reducing the opioid epidemic in the US may require addressing patients’ expectations regarding pain control in addition to providers’ inpatient analgesic prescribing patterns.

Disclosures

The authors report no conflicts of interest.

Funding

The authors report no funding source for this work.

Since 2000, the United States has seen a marked increase in opioid prescribing^1-3 and opioid-related complications, including overdoses, hospitalizations, and deaths.^2,4,5 A study from 2015 showed that more than one-third of the US civilian noninstitutionalized population reported receiving an opioid prescription in the prior year, with 12.5% reporting misuse, and, of those, 16.7% reported a prescription use disorder.⁶ While there has been a slight decrease in opioid prescriptions in the US since 2012, rates of opioid prescribing in 2015 were three times higher than in 1999 and approximately four times higher than in Europe in 2015.^3,7

Pain is commonly reported by hospitalized patients,^8,9 and opioids are often a mainstay of treatment;^9,10 however, treatment with opioids can have a number of adverse outcomes.^2,10,11 Short-term exposure to opioids can lead to long-term use,^12-16 and patients on opioids are at an increased risk for subsequent hospitalization and longer inpatient lengths of stay.⁵

Physician prescribing practices for opioids and patient expectations for pain control vary as a function of geographic region and culture,^10,12,17,18 and pain is influenced by the cultural context in which it occurs.^17,19-22 Treatment of pain may also be affected by limited access to or restrictions on selected medications, as well as by cultural biases.²³ Whether these variations in the treatment of pain are reflected in patients’ satisfaction with pain control is uncertain.

We sought to compare the inpatient analgesic prescribing practices and patients’ perceptions of pain control for medical patients in four teaching hospitals in the US and in seven teaching hospitals in seven other countries.

Study Design

We utilized a cross-sectional, observational design. The study was approved by the Institutional Review Boards at all participating sites.

Setting

The study was conducted at 11 academic hospitals in eight countries from October 8, 2013 to August 31, 2015. Sites in the US included Denver Health in Denver, Colorado; the University of Colorado Hospital in Aurora, Colorado; Hennepin Healthcare in Minneapolis, Minnesota; and Legacy Health in Portland, Oregon. Sites outside the US included McMaster University in Hamilton, Ontario, Canada; Hospital de la Santa Creu i Sant Pau, Universitat Autonòma de Barcelona in Barcelona, Spain; the University of Study of Milan and the University Ospedale “Luigi Sacco” in Milan, Italy, the National Taiwan University Hospital, in Taipei, Taiwan, the University of Ulsan College of Medicine, Asan Medical Center, in Seoul, Korea, the Imperial College, Chelsea and Westminster Hospital, in London, United Kingdom and Dunedin Hospital, Dunedin, New Zealand.

Inclusion and Exclusion Criteria

We included patients 18-89 years of age (20-89 in Taiwan because patients under 20 years of age in this country are a restricted group with respect to participating in research), admitted to an internal medicine service from the Emergency Department or Urgent Care clinic with an acute illness for a minimum of 24 hours (with time zero defined as the time care was initiated in the Emergency Department or Urgent Care Clinic), who reported pain at some time during the first 24-36 hours of their hospitalization and who provided informed consent. In the US, “admission” included both observation and inpatient status. We limited the patient population to those admitted via emergency departments and urgent care clinics in order to enroll similar patient populations across sites.

Scheduled admissions, patients transferred from an outside facility, patients admitted directly from a clinic, and those receiving care in intensive care units were excluded. We also excluded patients who were incarcerated, pregnant, those who received major surgery within the previous 14 days, those with a known diagnosis of active cancer, and those who were receiving palliative or hospice care. Patients receiving care from an investigator in the study at the time of enrollment were not eligible due to the potential conflict of interest.

Patient Screening

Primary teams were contacted to determine if any patients on their service might meet the criteria for inclusion in the study on preselected study days chosen on the basis of the research team’s availability. Identified patients were then screened to establish if they met the eligibility criteria. Patients were asked directly if they had experienced pain during their preadmission evaluation or during their hospitalization.

Data Collection

All patients were hospitalized at the time they gave consent and when data were collected. Data were collected via interviews with patients, as well as through chart review. We recorded patients’ age, gender, race, admitting diagnosis(es), length of stay, psychiatric illness, illicit drug use, whether they reported receiving opioid analgesics at the time of hospitalization, whether they were prescribed opioids and/or nonopioid analgesics during their hospitalization, the median and maximum doses of opioids prescribed and dispensed, and whether they were discharged on opioids. The question of illicit drug use was asked of all patients with the exception of those hospitalized in South Korea due to potential legal implications.

Opioid prescribing and receipt of opioids was recorded based upon current provider orders and medication administration records, respectively. Perception of and satisfaction with pain control was assessed with the American Pain Society Patient Outcome Questionnaire–Modified (APS-POQ-Modified).^24,25 Versions of this survey have been validated in English as well as in other languages and cultures.^26-28 Because hospitalization practices could differ across hospitals and in different countries, we compared patients’ severity of illness by using Charlson comorbidity scores. Consent forms and the APS-POQ were translated into each country’s primary language according to established processes.²⁹ The survey was filled out by having site investigators read questions aloud and by use of a large-font visual analog scale to aid patients’ verbal responses.

Data were collected and managed using a secure, web-based application electronic data capture tool (Research Electronic Data Capture [REDCap], Nashville, Tennessee), hosted at Denver Health.³⁰

Study Size

Preliminary data from the internal medicine units at our institution suggested that 40% of patients without cancer received opioid analgesics during their hospitalization. Assuming 90% power to detect an absolute difference in the proportion of inpatient medical patients who are receiving opioid analgesics during their hospital stay of 17%, a two-sided type 1 error rate of 0.05, six hospitals in the US, and nine hospitals from all other countries, we calculated an initial sample size of 150 patients per site. This sample size was considered feasible for enrollment in a busy inpatient clinical setting. Study end points were to either reach the goal number of patients (150 per site) or the predetermined study end date, whichever came first.

Data Analysis

We generated means with standard deviations (SDs) and medians with interquartile ranges (IQRs) for normally and nonnormally distributed continuous variables, respectively, and frequencies for categorical variables. We used linear mixed modeling for the analysis of continuous variables. For binary outcomes, our data were fitted to a generalized linear mixed model with logit as the link function and a binary distribution. For ordinal variables, specifically patient-reported satisfaction with pain control and the opinion statements, the data were fitted to a generalized linear mixed model with a cumulative logit link and a multinomial distribution. Hospital was included as a random effect in all models to account for patients cared for in the same hospital.

Country of origin, dichotomized as US or non-US, was the independent variable of interest for all models. An interaction term for exposure to opioids prior to admission and country was entered into all models to explore whether differences in the effect of country existed for patients who reported taking opioids prior to admission and those who did not.

The models for the frequency with which analgesics were given, doses of opioids given during hospitalization and at discharge, patient-reported pain score, and patient-reported satisfaction with pain control were adjusted for (1) age, (2) gender, (3) Charlson Comorbidity Index, (4) length of stay, (5) history of illicit drug use, (6) history of psychiatric illness, (7) daily dose in morphine milligram equivalents (MME) for opioids prior to admission, (8) average pain score, and (9) hospital. The patient-reported satisfaction with pain control model was also adjusted for whether or not opioids were given to the patient during their hospitalization. P < .05 was considered to indicate significance. All analyses were performed using SAS Enterprise Guide 7.1 (SAS Institute, Inc., Cary, North Carolina). We reported data on medications that were prescribed and dispensed (as opposed to just prescribed and not necessarily given). Opioids prescribed at discharge represented the total possible opioids that could be given based upon the order/prescription (eg, oxycodone 5 mg every 6 hours as needed for pain would be counted as 20 mg/24 hours maximum possible dose followed by conversion to MME).

Missing Data

When there were missing data, a query was sent to sites to verify if the data were retrievable. If retrievable, the data were then entered. Data were missing in 5% and 2% of patients who did or did not report taking an opioid prior to admission, respectively. If a variable was included in a specific statistical test, then subjects with missing data were excluded from that analysis (ie, complete case analysis).

We approached 1,309 eligible patients, of which 981 provided informed consent, for a response rate of 75%; 503 from the US and 478 patients from other countries (Figure). In unadjusted analyses, we found no significant differences between US and non-US patients in age (mean age 51, SD 15 vs 59, SD 19; P = .30), race, ethnicity, or Charlson comorbidity index scores (median 2, IQR 1-3 vs 3, IQR 1-4; P = .45). US patients had shorter lengths of stay (median 3 days, IQR 2-4 vs 6 days, IQR 3-11; P = .04), a more frequent history of illicit drug use (33% vs 6%; P = .003), a higher frequency of psychiatric illness (27% vs 8%; P < .0001), and more were receiving opioid analgesics prior to admission (38% vs 17%; P = .007) than those hospitalized in other countries (Table 1, Appendix 1). The primary admitting diagnoses for all patients in the study are listed in Appendix 2. Opioid prescribing practices across the individual sites are shown in Appendix 3.

Patients Taking Opioids Prior to Admission

After adjusting for relevant covariates, we found that more patients in the US were given opioids during their hospitalization and in higher doses than patients from other countries and more were prescribed opioids at discharge. Fewer patients in the US were dispensed nonopioid analgesics during their hospitalization than patients from other countries, but this difference was not significant (Table 2). Appendix 4 shows the types of nonopioid pain medications prescribed in the US and other countries.

After adjustment for relevant covariates, US patients reported greater pain severity at the time they completed their pain surveys. We found no significant difference in satisfaction with pain control between patients from the US and other countries in the models, regardless of whether we included average pain score or opioid receipt during hospitalization in the model (Table 3).

In unadjusted analyses, compared with patients hospitalized in other countries, more patients in the US stated that they would like a stronger dose of analgesic if they were still in pain, though the difference was nonsignificant, and US patients were more likely to agree with the statement that people become addicted to pain medication easily and less likely to agree with the statement that it is easier to endure pain than deal with the side effects of pain medications (Table 3).

Patients Not Taking Opioids Prior to Admission

After adjusting for relevant covariates, we found no significant difference in the proportion of US patients provided with nonopioid pain medications during their hospitalization compared with patients in other countries, but a greater percentage of US patients were given opioids during their hospitalization and at discharge and in higher doses (Table 2).

After adjusting for relevant covariates, US patients reported greater pain severity at the time they completed their pain surveys and greater pain severity in the 24-36 hours prior to completing the survey than patients from other countries, but we found no difference in patient satisfaction with pain control (Table 3). After we included the average pain score and whether or not opioids were given to the patient during their hospitalization in this model, patients in the US were more likely to report a higher level of satisfaction with pain control than patients in all other countries (P = .001).

Patient Satisfaction and Opioid Receipt

Among patients cared for in the US, after controlling for the average pain score, we did not find a significant association between receiving opioids while in the hospital and satisfaction with pain control for patients who either did or did not endorse taking opioids prior to admission (P = .38 and P = .24, respectively). Among patients cared for in all other countries, after controlling for the average pain score, we found a significant association between receiving opioids while in the hospital and a lower level of satisfaction with pain control for patients who reported taking opioids prior to admission (P = .02) but not for patients who did not report taking opioids prior to admission (P = .08).

Compared with patients hospitalized in other countries, a greater percentage of those hospitalized in the US were prescribed opioid analgesics both during hospitalization and at the time of discharge, even after adjustment for pain severity. In addition, patients hospitalized in the US reported greater pain severity at the time they completed their pain surveys and in the 24 to 36 hours prior to completing the survey than patients from other countries. In this sample, satisfaction, beliefs, and expectations about pain control differed between patients in the US and other sites. Our study also suggests that opioid receipt did not lead to improved patient satisfaction with pain control.

The frequency with which we observed opioid analgesics being prescribed during hospitalization in US hospitals (79%) was higher than the 51% of patients who received opioids reported by Herzig and colleagues.¹⁰ Patients in our study had a higher prevalence of illicit drug abuse and psychiatric illness, and our study only included patients who reported pain at some point during their hospitalization. We also studied prescribing practices through analysis of provider orders and medication administration records at the time the patient was hospitalized.

While we observed that physicians in the US more frequently prescribed opioid analgesics during hospitalizations than physicians working in other countries, we also observed that patients in the US reported higher levels of pain during their hospitalization. After adjusting for a number of variables, including pain severity, however, we still found that opioids were more commonly prescribed during hospitalizations by physicians working in the US sites studied than by physicians in the non-US sites.

Opioid prescribing practices varied across the sites sampled in our study. While the US sites, Taiwan, and Korea tended to be heavier utilizers of opioids during hospitalization, there were notable differences in discharge prescribing of opioids, with the US sites more commonly prescribing opioids and higher MME for patients who did not report taking opioids prior to their hospitalization (Appendix 3). A sensitivity analysis was conducted excluding South Korea from modeling, given that patients there were not asked about illicit opioid use. There were no important changes in the magnitude or direction of the results.

Our study supports previous studies indicating that there are cultural and societal differences when it comes to the experience of pain and the expectations around pain control.^17,20-22,31 Much of the focus on reducing opioid utilization has been on provider practices³² and on prescription drug monitoring programs.³³ Our findings suggest that another area of focus that may be important in mitigating the opioid epidemic is patient expectations of pain control.

Our study has a number of strengths. First, we included 11 hospitals from eight different countries. Second, we believe this is the first study to assess opioid prescribing and dispensing practices during hospitalization as well as at the time of discharge. Third, patient perceptions of pain control were assessed in conjunction with analgesic prescribing and were assessed during hospitalization. Fourth, we had high response rates for patient participation in our study. Fifth, we found much larger differences in opioid prescribing than anticipated, and thus, while we did not achieve the sample size originally planned for either the number of hospitals or patients enrolled per hospital, we were sufficiently powered. This is likely secondary to the fact that the population we studied was one that specifically reported pain, resulting in the larger differences seen.

Our study also had a number of limitations. First, the prescribing practices in countries other than the US are represented by only one hospital per country and, in some countries, by limited numbers of patients. While we studied four sites in the US, we did not have a site in the Northeast, a region previously shown to have lower prescribing rates.¹⁰ Additionally, patient samples for the US sites compared with the sites in other countries varied considerably with respect to ethnicity. While some studies in US patients have shown that opioid prescribing may vary based on race/ethnicity,³⁴ we are uncertain as to how this might impact a study that crosses multiple countries. We also had a low number of patients receiving opioids prior to hospitalization for several of the non-US countries, which reduced the power to detect differences in this subgroup. Previous research has shown that there are wide variations in prescribing practices even within countries;^10,12,18 therefore, caution should be taken when generalizing our findings. Second, we assessed analgesic prescribing patterns and pain control during the first 24 to 36 hours of hospitalization and did not consider hospital days beyond this timeframe with the exception of noting what medications were prescribed at discharge. We chose this methodology in an attempt to eliminate as many differences that might exist in the duration of hospitalization across many countries. Third, investigators in the study administered the survey, and respondents may have been affected by social desirability bias in how the survey questions were answered. Because investigators were not a part of the care team of any study patients, we believe this to be unlikely. Fourth, our study was conducted from October 8, 2013 to August 31, 2015 and the opioid epidemic is dynamic. Accordingly, our data may not reflect current opioid prescribing practices or patients’ current beliefs regarding pain control. Fifth, we did not collect demographic data on the patients who did not participate and could not look for systematic differences between participants and nonparticipants. Sixth, we relied on patients to self-report whether they were taking opioids prior to hospitalization or using illicit drugs. Seventh, we found comorbid mental health conditions to be more frequent in the US population studied. Previous work has shown regional variation in mental health conditions,^35,36 which could have affected our findings. To account for this, our models included psychiatric illness.

Our data suggest that physicians in the US may prescribe opioids more frequently during patients’ hospitalizations and at discharge than their colleagues in other countries. We also found that patient satisfaction, beliefs, and expectations about pain control differed between patients in the US and other sites. Although the small number of hospitals included in our sample coupled with the small sample size in some of the non-US countries limits the generalizability of our findings, the data suggest that reducing the opioid epidemic in the US may require addressing patients’ expectations regarding pain control in addition to providers’ inpatient analgesic prescribing patterns.

Disclosures

The authors report no conflicts of interest.

Funding

The authors report no funding source for this work.

Hospital discharges frequently occur in the afternoon or evening hours.^1-5 Late discharges can adversely affect patient flow throughout the hospital,^3,6-9 which, in turn, can result in delays in care,^10-16 more medication errors,¹⁷ increased mortality,^18-20 longer lengths of stay,^20-22 higher costs,²³ and lower patient satisfaction.²⁴

Various interventions have been employed in the attempts to find ways of moving discharge times to earlier in the day, including preparing the discharge paperwork and medications the previous night,²⁵ using checklists,^1,25 team huddles,² providing real-time feedback to unit staff,¹ and employing multidisciplinary teamwork.^1,2,6,25,26

The purpose of this study was to identify and determine the relative frequency of barriers to writing discharge orders in the hopes of identifying issues that might be addressed by targeted interventions. We also assessed the effects of daily team census, patients being on teaching versus nonteaching services, and how daily rounds were structured at the time that the discharge orders were written.

Study Design, Setting, and Participants

We conducted a prospective, cross-sectional survey of house-staff and attending physicians on general medicine teaching and nonteaching services from November 13, 2014, through May 31, 2016. The study was conducted at the following five hospitals: Denver Health Medical Center (DHMC) and Presbyterian/Saint Luke’s Medical Center (PSL) in Denver, Colorado; Ronald Reagan University (UCLA) and Los Angeles County/University of Southern California Medical Center (LAC+USC) in Los Angeles, California; and Harborview Medical Center (HMC) in Seattle, Washington. The study was approved by the Colorado Multi-Institutional Review Board as well as by the review boards of the other participating sites.

Data Collection

The results of the focus groups composed of attending physicians at DHMC were used to develop our initial data collection template. Additional sites joining the study provided feedback, leading to modifications (Appendix 1).

Physicians were surveyed at three different time points on study days that were selected according to the convenience of the investigators. The sampling occurred only on weekdays and was done based on the investigators’ availability. Investigators would attempt to survey as many teams as they were able to but, secondary to feasibility, not all teams could be surveyed on study days. The specific time points varied as a function of physician workflows but were standardized as much as possible to occur in the early morning, around noon, and midafternoon on weekdays. Physicians were contacted either in person or by telephone for verbal consent prior to administering the first survey. All general medicine teams were eligible. For teaching teams, the order of contact was resident, intern, and then attending based on which physician was available at the time of the survey and on which member of the team was thought to know the patients the best. For the nonteaching services, the attending physicians were contacted.

During the initial survey, the investigators assessed the provider role (ie, attending or housestaff), whether the service was a teaching or a nonteaching service, and the starting patient census on that service primarily based on interviewing the provider of record for the team and looking at team census lists. Physicians were asked about their rounding style (ie, sickest patients first, patients likely to be discharged first, room-by-room, most recently admitted patients first, patients on the team the longest, or other) and then to identify all patients they thought would be definite discharges sometime during the day of the survey. Definite discharges were defined as patients whom the provider thought were either currently ready for discharge or who had only minor barriers that, if unresolved, would not prevent same-day discharge. They were asked if the discharge order had been entered and, if not, what was preventing them from doing so, if the discharge could in their opinion have occurred the day prior and, if so, why this did not occur. We also obtained the date and time of the admission and discharge orders, the actual discharge time, as well as the length of stay either through chart review (majority of sites) or from data warehouses (Denver Health and Presbyterian St. Lukes had length of stay data retrieved from their data warehouse).

Physicians were also asked to identify all patients whom they thought might possibly be discharged that day. Possible discharges were defined as patients with barriers to discharge that, if unresolved, would prevent same-day discharge. For each of these, the physicians were asked to list whatever issues needed to be resolved prior to placing the discharge order (Appendix 1).

The second survey was administered late morning on the same day, typically between 11 am and 12 pm. In this survey, the physicians were asked to reassess the patients previously classified as definite and possible discharges for changes in status and/or barriers and to identify patients who had become definite or possible discharges since the earlier survey. Newly identified possible or definite discharges were evaluated in a similar manner as the initial survey.

The third survey was administered midafternoon, typically around 3 PM similar to the first two surveys, with the exception that the third survey did not attempt to identify new definite or possible discharges.

Sample Size

We stopped collecting data after obtaining a convenience sample of 5% of total discharges at each study site or on the study end date, which was May 31, 2016, whichever came first.

Data Analysis

Data were collected and managed using a secure, web-based application electronic data capture tool (REDCap), hosted at Denver Health. REDCap (Research Electronic Data Capture, Nashville, Tennessee) is designed to support data collection for research studies.²⁷ Data were then analyzed using SAS Enterprise Guide 5.1 (SAS Institute, Inc., Cary, North Carolina). All data entered into REDCap were reviewed by the principal investigator to ensure that data were not missing, and when there were missing data, a query was sent to verify if the data were retrievable. If retrievable, then the data would be entered. The volume of missing data that remained is described in our results.

Continuous variables were described using means and standard deviations (SD) or medians and interquartile ranges (IQR) based on tests of normality. Differences in the time that the discharge orders were placed in the electronic medical record according to morning patient census, teaching versus nonteaching service, and rounding style were compared using the Wilcoxon rank sum test. Linear regression was used to evaluate the effect of patient census on discharge order time. P < .05 was considered as significant.

We conducted 1,584 patient evaluations through surveys of 254 physicians over 156 days. Given surveys coincided with the existing work we had full participation (ie, 100% participation) and no dropout during the study days. Median (IQR) survey time points were 8:30 am (7:51 am, 9:12 am), 11:45 am (11:30 am, 12:17 pm), and 3:20 pm (3:00 pm, 4:06 pm).

The characteristics of the five hospitals participating in the study, the patients’ final discharge status, the types of physicians surveyed, the services on which they were working, the rounding styles employed, and the median starting daily census are summarized in Table 1. The majority of the physicians surveyed were housestaff working on teaching services, and only a small minority structured rounds such that patients ready for discharge were seen first.

The important findings of this study are that (1) the large majority of issues thought to delay discharging patients identified as definite discharges were related to physicians caring for other patients on their team, (2) although 91% of patients ever identified as being definite discharges were discharged on the day of the survey, only 48% of those identified as possible discharges became definite discharges by the afternoon time point, largely because the anticipated clinical improvement did not occur or care being provided by ancillary services had not been completed, and (3) discharge orders on patients identified as definite discharges were written on average 50 minutes earlier by physicians on teams with a smaller starting patient census, on nonteaching services, or when the rounding style was to see patients ready for discharges first.

Previous research has reported that physician-perceived barriers to discharge were extrinsic to providers and even extrinsic to the hospital setting (eg, awaiting subacute nursing placement and transportation).^28,29 However, many of the barriers that we identified were related directly to the providers’ workload and rounding styles and whether the patients were on teaching versus nonteaching services. We also found that delays in the ability of hospital services to complete care also contributed to delayed discharges.

Our observational data suggest that delays resulting from caring for other patients might be reduced by changing rounding styles such that patients ready for discharge are seen first and are discharged prior to seeing other patients on the team, as previously reported by Beck et al.³⁰ Intuitively, this would seem to be a straightforward way of freeing up beds earlier in the day, but such a change will, of necessity, lead to delaying care for other patients, which, in turn, could increase their length of stays. Durvasula et al. suggested that discharges could be moved to earlier in the day by completing orders and paperwork the day prior to discharge.²⁵ Such an approach might be effective on an Obstetrical or elective Orthopedic service on which patients predictably are hospitalized for a fixed number of days (or even hours) but may be less relevant to patients on internal medicine services where lengths of stay are less predictable. Interventions to improve discharge times have resulted in earlier discharge times in some studies,^2,4 but the overall length of stay either did not decrease²⁵ or increased³¹ in others. Werthheimer et al.¹ did find earlier discharge times, but other interventions also occurred during the study period (eg, extending social work services to include weekends).^1,32

We found that discharge times were approximately 50 minutes earlier on teams with a smaller starting census, on nonteaching compared with teaching services, or when the attending’s rounding style was to see patients ready for discharges first. Although 50 minutes may seem like a small change in discharge time, Khanna et al.³³ found that when discharges occur even 1 hour earlier, hospital overcrowding is reduced. To have a lower team census would require having more teams and more providers to staff these teams, raising cost-effectiveness concerns. Moving to more nonteaching services could represent a conflict with respect to one of the missions of teaching hospitals and raises a cost-benefit issue as several teaching hospitals receive substantial funding in support of their teaching activities and housestaff would have to be replaced with more expensive providers.

Delays attributable to ancillary services indicate imbalances between demand and availability of these services. Inappropriate demand and inefficiencies could be reduced by systems redesign, but in at least some instances, additional resources will be needed to add staff, increase space, or add additional equipment.

Our study has several limitations. First, we surveyed only physicians working in university-affiliated hospitals, and three of these were public safety-net hospitals. Accordingly, our results may not be generalizable to different patient populations. Second, we surveyed only physicians, and Minichiello et al.²⁹ found that barriers to discharge perceived by physicians were different from those of other staff. Third, our data were observational and were collected only on weekdays. Fourth, we did not differentiate interns from residents, and thus, potentially the level of training could have affected these results. Similarly, the decision for a “possible” and a “definite” discharge is likely dependent on the knowledge base of the participant, such that less experienced participants may have had differing perspectives than someone with more experience. Fifth, the sites did vary based on the infrastructure and support but also had several similarities. All sites had social work and case management involved in care, although at some sites, they were assigned according to team and at others according to geographic location. Similarly, rounding times varied. Most of the services surveyed did not utilize advanced practice providers (the exception was the nonteaching services at Denver Health, and their presence was variable). These differences in staffing models could also have affected these results.

Our study also has a number of strengths. First, we assessed the barriers at five different hospitals. Second, we collected real-time data related to specific barriers at multiple time points throughout the day, allowing us to assess the dynamic nature of identifying patients as being ready or nearly ready for discharge. Third, we assessed the perceptions of barriers to discharge from physicians working on teaching as well as nonteaching services and from physicians utilizing a variety of rounding styles. Fourth, we had a very high participation rate (100%), probably due to the fact that our study was strategically aligned with participants’ daily work activities.

In conclusion, we found two distinct categories of issues that physicians perceived as most commonly delaying writing discharge orders on their patients. The first pertained to patients thought to definitely be ready for discharge and was related to the physicians having to care for other patients on their team. The second pertained to patients identified as possibly ready for discharge and was related to the need for care to be completed by a variety of ancillary services. Addressing each of these barriers would require different interventions and a need to weigh the potential improvements that could be achieved against the increased costs and/or delays in care for other patients that may result.

Disclosures

The authors report no conflicts of interest relevant to this work.

Hospital discharges frequently occur in the afternoon or evening hours.^1-5 Late discharges can adversely affect patient flow throughout the hospital,^3,6-9 which, in turn, can result in delays in care,^10-16 more medication errors,¹⁷ increased mortality,^18-20 longer lengths of stay,^20-22 higher costs,²³ and lower patient satisfaction.²⁴

Various interventions have been employed in the attempts to find ways of moving discharge times to earlier in the day, including preparing the discharge paperwork and medications the previous night,²⁵ using checklists,^1,25 team huddles,² providing real-time feedback to unit staff,¹ and employing multidisciplinary teamwork.^1,2,6,25,26

The purpose of this study was to identify and determine the relative frequency of barriers to writing discharge orders in the hopes of identifying issues that might be addressed by targeted interventions. We also assessed the effects of daily team census, patients being on teaching versus nonteaching services, and how daily rounds were structured at the time that the discharge orders were written.

Study Design, Setting, and Participants

We conducted a prospective, cross-sectional survey of house-staff and attending physicians on general medicine teaching and nonteaching services from November 13, 2014, through May 31, 2016. The study was conducted at the following five hospitals: Denver Health Medical Center (DHMC) and Presbyterian/Saint Luke’s Medical Center (PSL) in Denver, Colorado; Ronald Reagan University (UCLA) and Los Angeles County/University of Southern California Medical Center (LAC+USC) in Los Angeles, California; and Harborview Medical Center (HMC) in Seattle, Washington. The study was approved by the Colorado Multi-Institutional Review Board as well as by the review boards of the other participating sites.

Data Collection

The results of the focus groups composed of attending physicians at DHMC were used to develop our initial data collection template. Additional sites joining the study provided feedback, leading to modifications (Appendix 1).

Physicians were surveyed at three different time points on study days that were selected according to the convenience of the investigators. The sampling occurred only on weekdays and was done based on the investigators’ availability. Investigators would attempt to survey as many teams as they were able to but, secondary to feasibility, not all teams could be surveyed on study days. The specific time points varied as a function of physician workflows but were standardized as much as possible to occur in the early morning, around noon, and midafternoon on weekdays. Physicians were contacted either in person or by telephone for verbal consent prior to administering the first survey. All general medicine teams were eligible. For teaching teams, the order of contact was resident, intern, and then attending based on which physician was available at the time of the survey and on which member of the team was thought to know the patients the best. For the nonteaching services, the attending physicians were contacted.

During the initial survey, the investigators assessed the provider role (ie, attending or housestaff), whether the service was a teaching or a nonteaching service, and the starting patient census on that service primarily based on interviewing the provider of record for the team and looking at team census lists. Physicians were asked about their rounding style (ie, sickest patients first, patients likely to be discharged first, room-by-room, most recently admitted patients first, patients on the team the longest, or other) and then to identify all patients they thought would be definite discharges sometime during the day of the survey. Definite discharges were defined as patients whom the provider thought were either currently ready for discharge or who had only minor barriers that, if unresolved, would not prevent same-day discharge. They were asked if the discharge order had been entered and, if not, what was preventing them from doing so, if the discharge could in their opinion have occurred the day prior and, if so, why this did not occur. We also obtained the date and time of the admission and discharge orders, the actual discharge time, as well as the length of stay either through chart review (majority of sites) or from data warehouses (Denver Health and Presbyterian St. Lukes had length of stay data retrieved from their data warehouse).

Physicians were also asked to identify all patients whom they thought might possibly be discharged that day. Possible discharges were defined as patients with barriers to discharge that, if unresolved, would prevent same-day discharge. For each of these, the physicians were asked to list whatever issues needed to be resolved prior to placing the discharge order (Appendix 1).

The second survey was administered late morning on the same day, typically between 11 am and 12 pm. In this survey, the physicians were asked to reassess the patients previously classified as definite and possible discharges for changes in status and/or barriers and to identify patients who had become definite or possible discharges since the earlier survey. Newly identified possible or definite discharges were evaluated in a similar manner as the initial survey.

The third survey was administered midafternoon, typically around 3 PM similar to the first two surveys, with the exception that the third survey did not attempt to identify new definite or possible discharges.

Sample Size

We stopped collecting data after obtaining a convenience sample of 5% of total discharges at each study site or on the study end date, which was May 31, 2016, whichever came first.

Data Analysis

Data were collected and managed using a secure, web-based application electronic data capture tool (REDCap), hosted at Denver Health. REDCap (Research Electronic Data Capture, Nashville, Tennessee) is designed to support data collection for research studies.²⁷ Data were then analyzed using SAS Enterprise Guide 5.1 (SAS Institute, Inc., Cary, North Carolina). All data entered into REDCap were reviewed by the principal investigator to ensure that data were not missing, and when there were missing data, a query was sent to verify if the data were retrievable. If retrievable, then the data would be entered. The volume of missing data that remained is described in our results.

Continuous variables were described using means and standard deviations (SD) or medians and interquartile ranges (IQR) based on tests of normality. Differences in the time that the discharge orders were placed in the electronic medical record according to morning patient census, teaching versus nonteaching service, and rounding style were compared using the Wilcoxon rank sum test. Linear regression was used to evaluate the effect of patient census on discharge order time. P < .05 was considered as significant.

We conducted 1,584 patient evaluations through surveys of 254 physicians over 156 days. Given surveys coincided with the existing work we had full participation (ie, 100% participation) and no dropout during the study days. Median (IQR) survey time points were 8:30 am (7:51 am, 9:12 am), 11:45 am (11:30 am, 12:17 pm), and 3:20 pm (3:00 pm, 4:06 pm).

The characteristics of the five hospitals participating in the study, the patients’ final discharge status, the types of physicians surveyed, the services on which they were working, the rounding styles employed, and the median starting daily census are summarized in Table 1. The majority of the physicians surveyed were housestaff working on teaching services, and only a small minority structured rounds such that patients ready for discharge were seen first.

The important findings of this study are that (1) the large majority of issues thought to delay discharging patients identified as definite discharges were related to physicians caring for other patients on their team, (2) although 91% of patients ever identified as being definite discharges were discharged on the day of the survey, only 48% of those identified as possible discharges became definite discharges by the afternoon time point, largely because the anticipated clinical improvement did not occur or care being provided by ancillary services had not been completed, and (3) discharge orders on patients identified as definite discharges were written on average 50 minutes earlier by physicians on teams with a smaller starting patient census, on nonteaching services, or when the rounding style was to see patients ready for discharges first.

Previous research has reported that physician-perceived barriers to discharge were extrinsic to providers and even extrinsic to the hospital setting (eg, awaiting subacute nursing placement and transportation).^28,29 However, many of the barriers that we identified were related directly to the providers’ workload and rounding styles and whether the patients were on teaching versus nonteaching services. We also found that delays in the ability of hospital services to complete care also contributed to delayed discharges.

Our observational data suggest that delays resulting from caring for other patients might be reduced by changing rounding styles such that patients ready for discharge are seen first and are discharged prior to seeing other patients on the team, as previously reported by Beck et al.³⁰ Intuitively, this would seem to be a straightforward way of freeing up beds earlier in the day, but such a change will, of necessity, lead to delaying care for other patients, which, in turn, could increase their length of stays. Durvasula et al. suggested that discharges could be moved to earlier in the day by completing orders and paperwork the day prior to discharge.²⁵ Such an approach might be effective on an Obstetrical or elective Orthopedic service on which patients predictably are hospitalized for a fixed number of days (or even hours) but may be less relevant to patients on internal medicine services where lengths of stay are less predictable. Interventions to improve discharge times have resulted in earlier discharge times in some studies,^2,4 but the overall length of stay either did not decrease²⁵ or increased³¹ in others. Werthheimer et al.¹ did find earlier discharge times, but other interventions also occurred during the study period (eg, extending social work services to include weekends).^1,32

We found that discharge times were approximately 50 minutes earlier on teams with a smaller starting census, on nonteaching compared with teaching services, or when the attending’s rounding style was to see patients ready for discharges first. Although 50 minutes may seem like a small change in discharge time, Khanna et al.³³ found that when discharges occur even 1 hour earlier, hospital overcrowding is reduced. To have a lower team census would require having more teams and more providers to staff these teams, raising cost-effectiveness concerns. Moving to more nonteaching services could represent a conflict with respect to one of the missions of teaching hospitals and raises a cost-benefit issue as several teaching hospitals receive substantial funding in support of their teaching activities and housestaff would have to be replaced with more expensive providers.

Delays attributable to ancillary services indicate imbalances between demand and availability of these services. Inappropriate demand and inefficiencies could be reduced by systems redesign, but in at least some instances, additional resources will be needed to add staff, increase space, or add additional equipment.

Our study has several limitations. First, we surveyed only physicians working in university-affiliated hospitals, and three of these were public safety-net hospitals. Accordingly, our results may not be generalizable to different patient populations. Second, we surveyed only physicians, and Minichiello et al.²⁹ found that barriers to discharge perceived by physicians were different from those of other staff. Third, our data were observational and were collected only on weekdays. Fourth, we did not differentiate interns from residents, and thus, potentially the level of training could have affected these results. Similarly, the decision for a “possible” and a “definite” discharge is likely dependent on the knowledge base of the participant, such that less experienced participants may have had differing perspectives than someone with more experience. Fifth, the sites did vary based on the infrastructure and support but also had several similarities. All sites had social work and case management involved in care, although at some sites, they were assigned according to team and at others according to geographic location. Similarly, rounding times varied. Most of the services surveyed did not utilize advanced practice providers (the exception was the nonteaching services at Denver Health, and their presence was variable). These differences in staffing models could also have affected these results.

Our study also has a number of strengths. First, we assessed the barriers at five different hospitals. Second, we collected real-time data related to specific barriers at multiple time points throughout the day, allowing us to assess the dynamic nature of identifying patients as being ready or nearly ready for discharge. Third, we assessed the perceptions of barriers to discharge from physicians working on teaching as well as nonteaching services and from physicians utilizing a variety of rounding styles. Fourth, we had a very high participation rate (100%), probably due to the fact that our study was strategically aligned with participants’ daily work activities.

In conclusion, we found two distinct categories of issues that physicians perceived as most commonly delaying writing discharge orders on their patients. The first pertained to patients thought to definitely be ready for discharge and was related to the physicians having to care for other patients on their team. The second pertained to patients identified as possibly ready for discharge and was related to the need for care to be completed by a variety of ancillary services. Addressing each of these barriers would require different interventions and a need to weigh the potential improvements that could be achieved against the increased costs and/or delays in care for other patients that may result.

Disclosures

The authors report no conflicts of interest relevant to this work.

Hospital discharges frequently occur in the afternoon or evening hours.^1-5 Late discharges can adversely affect patient flow throughout the hospital,^3,6-9 which, in turn, can result in delays in care,^10-16 more medication errors,¹⁷ increased mortality,^18-20 longer lengths of stay,^20-22 higher costs,²³ and lower patient satisfaction.²⁴

Various interventions have been employed in the attempts to find ways of moving discharge times to earlier in the day, including preparing the discharge paperwork and medications the previous night,²⁵ using checklists,^1,25 team huddles,² providing real-time feedback to unit staff,¹ and employing multidisciplinary teamwork.^1,2,6,25,26

The purpose of this study was to identify and determine the relative frequency of barriers to writing discharge orders in the hopes of identifying issues that might be addressed by targeted interventions. We also assessed the effects of daily team census, patients being on teaching versus nonteaching services, and how daily rounds were structured at the time that the discharge orders were written.

Study Design, Setting, and Participants

We conducted a prospective, cross-sectional survey of house-staff and attending physicians on general medicine teaching and nonteaching services from November 13, 2014, through May 31, 2016. The study was conducted at the following five hospitals: Denver Health Medical Center (DHMC) and Presbyterian/Saint Luke’s Medical Center (PSL) in Denver, Colorado; Ronald Reagan University (UCLA) and Los Angeles County/University of Southern California Medical Center (LAC+USC) in Los Angeles, California; and Harborview Medical Center (HMC) in Seattle, Washington. The study was approved by the Colorado Multi-Institutional Review Board as well as by the review boards of the other participating sites.

Data Collection

The results of the focus groups composed of attending physicians at DHMC were used to develop our initial data collection template. Additional sites joining the study provided feedback, leading to modifications (Appendix 1).

Physicians were surveyed at three different time points on study days that were selected according to the convenience of the investigators. The sampling occurred only on weekdays and was done based on the investigators’ availability. Investigators would attempt to survey as many teams as they were able to but, secondary to feasibility, not all teams could be surveyed on study days. The specific time points varied as a function of physician workflows but were standardized as much as possible to occur in the early morning, around noon, and midafternoon on weekdays. Physicians were contacted either in person or by telephone for verbal consent prior to administering the first survey. All general medicine teams were eligible. For teaching teams, the order of contact was resident, intern, and then attending based on which physician was available at the time of the survey and on which member of the team was thought to know the patients the best. For the nonteaching services, the attending physicians were contacted.

During the initial survey, the investigators assessed the provider role (ie, attending or housestaff), whether the service was a teaching or a nonteaching service, and the starting patient census on that service primarily based on interviewing the provider of record for the team and looking at team census lists. Physicians were asked about their rounding style (ie, sickest patients first, patients likely to be discharged first, room-by-room, most recently admitted patients first, patients on the team the longest, or other) and then to identify all patients they thought would be definite discharges sometime during the day of the survey. Definite discharges were defined as patients whom the provider thought were either currently ready for discharge or who had only minor barriers that, if unresolved, would not prevent same-day discharge. They were asked if the discharge order had been entered and, if not, what was preventing them from doing so, if the discharge could in their opinion have occurred the day prior and, if so, why this did not occur. We also obtained the date and time of the admission and discharge orders, the actual discharge time, as well as the length of stay either through chart review (majority of sites) or from data warehouses (Denver Health and Presbyterian St. Lukes had length of stay data retrieved from their data warehouse).

Physicians were also asked to identify all patients whom they thought might possibly be discharged that day. Possible discharges were defined as patients with barriers to discharge that, if unresolved, would prevent same-day discharge. For each of these, the physicians were asked to list whatever issues needed to be resolved prior to placing the discharge order (Appendix 1).

The second survey was administered late morning on the same day, typically between 11 am and 12 pm. In this survey, the physicians were asked to reassess the patients previously classified as definite and possible discharges for changes in status and/or barriers and to identify patients who had become definite or possible discharges since the earlier survey. Newly identified possible or definite discharges were evaluated in a similar manner as the initial survey.

The third survey was administered midafternoon, typically around 3 PM similar to the first two surveys, with the exception that the third survey did not attempt to identify new definite or possible discharges.

Sample Size

We stopped collecting data after obtaining a convenience sample of 5% of total discharges at each study site or on the study end date, which was May 31, 2016, whichever came first.

Data Analysis

Data were collected and managed using a secure, web-based application electronic data capture tool (REDCap), hosted at Denver Health. REDCap (Research Electronic Data Capture, Nashville, Tennessee) is designed to support data collection for research studies.²⁷ Data were then analyzed using SAS Enterprise Guide 5.1 (SAS Institute, Inc., Cary, North Carolina). All data entered into REDCap were reviewed by the principal investigator to ensure that data were not missing, and when there were missing data, a query was sent to verify if the data were retrievable. If retrievable, then the data would be entered. The volume of missing data that remained is described in our results.

Continuous variables were described using means and standard deviations (SD) or medians and interquartile ranges (IQR) based on tests of normality. Differences in the time that the discharge orders were placed in the electronic medical record according to morning patient census, teaching versus nonteaching service, and rounding style were compared using the Wilcoxon rank sum test. Linear regression was used to evaluate the effect of patient census on discharge order time. P < .05 was considered as significant.

We conducted 1,584 patient evaluations through surveys of 254 physicians over 156 days. Given surveys coincided with the existing work we had full participation (ie, 100% participation) and no dropout during the study days. Median (IQR) survey time points were 8:30 am (7:51 am, 9:12 am), 11:45 am (11:30 am, 12:17 pm), and 3:20 pm (3:00 pm, 4:06 pm).

The characteristics of the five hospitals participating in the study, the patients’ final discharge status, the types of physicians surveyed, the services on which they were working, the rounding styles employed, and the median starting daily census are summarized in Table 1. The majority of the physicians surveyed were housestaff working on teaching services, and only a small minority structured rounds such that patients ready for discharge were seen first.

The important findings of this study are that (1) the large majority of issues thought to delay discharging patients identified as definite discharges were related to physicians caring for other patients on their team, (2) although 91% of patients ever identified as being definite discharges were discharged on the day of the survey, only 48% of those identified as possible discharges became definite discharges by the afternoon time point, largely because the anticipated clinical improvement did not occur or care being provided by ancillary services had not been completed, and (3) discharge orders on patients identified as definite discharges were written on average 50 minutes earlier by physicians on teams with a smaller starting patient census, on nonteaching services, or when the rounding style was to see patients ready for discharges first.

Previous research has reported that physician-perceived barriers to discharge were extrinsic to providers and even extrinsic to the hospital setting (eg, awaiting subacute nursing placement and transportation).^28,29 However, many of the barriers that we identified were related directly to the providers’ workload and rounding styles and whether the patients were on teaching versus nonteaching services. We also found that delays in the ability of hospital services to complete care also contributed to delayed discharges.

Our observational data suggest that delays resulting from caring for other patients might be reduced by changing rounding styles such that patients ready for discharge are seen first and are discharged prior to seeing other patients on the team, as previously reported by Beck et al.³⁰ Intuitively, this would seem to be a straightforward way of freeing up beds earlier in the day, but such a change will, of necessity, lead to delaying care for other patients, which, in turn, could increase their length of stays. Durvasula et al. suggested that discharges could be moved to earlier in the day by completing orders and paperwork the day prior to discharge.²⁵ Such an approach might be effective on an Obstetrical or elective Orthopedic service on which patients predictably are hospitalized for a fixed number of days (or even hours) but may be less relevant to patients on internal medicine services where lengths of stay are less predictable. Interventions to improve discharge times have resulted in earlier discharge times in some studies,^2,4 but the overall length of stay either did not decrease²⁵ or increased³¹ in others. Werthheimer et al.¹ did find earlier discharge times, but other interventions also occurred during the study period (eg, extending social work services to include weekends).^1,32

We found that discharge times were approximately 50 minutes earlier on teams with a smaller starting census, on nonteaching compared with teaching services, or when the attending’s rounding style was to see patients ready for discharges first. Although 50 minutes may seem like a small change in discharge time, Khanna et al.³³ found that when discharges occur even 1 hour earlier, hospital overcrowding is reduced. To have a lower team census would require having more teams and more providers to staff these teams, raising cost-effectiveness concerns. Moving to more nonteaching services could represent a conflict with respect to one of the missions of teaching hospitals and raises a cost-benefit issue as several teaching hospitals receive substantial funding in support of their teaching activities and housestaff would have to be replaced with more expensive providers.

Delays attributable to ancillary services indicate imbalances between demand and availability of these services. Inappropriate demand and inefficiencies could be reduced by systems redesign, but in at least some instances, additional resources will be needed to add staff, increase space, or add additional equipment.

Our study has several limitations. First, we surveyed only physicians working in university-affiliated hospitals, and three of these were public safety-net hospitals. Accordingly, our results may not be generalizable to different patient populations. Second, we surveyed only physicians, and Minichiello et al.²⁹ found that barriers to discharge perceived by physicians were different from those of other staff. Third, our data were observational and were collected only on weekdays. Fourth, we did not differentiate interns from residents, and thus, potentially the level of training could have affected these results. Similarly, the decision for a “possible” and a “definite” discharge is likely dependent on the knowledge base of the participant, such that less experienced participants may have had differing perspectives than someone with more experience. Fifth, the sites did vary based on the infrastructure and support but also had several similarities. All sites had social work and case management involved in care, although at some sites, they were assigned according to team and at others according to geographic location. Similarly, rounding times varied. Most of the services surveyed did not utilize advanced practice providers (the exception was the nonteaching services at Denver Health, and their presence was variable). These differences in staffing models could also have affected these results.

Our study also has a number of strengths. First, we assessed the barriers at five different hospitals. Second, we collected real-time data related to specific barriers at multiple time points throughout the day, allowing us to assess the dynamic nature of identifying patients as being ready or nearly ready for discharge. Third, we assessed the perceptions of barriers to discharge from physicians working on teaching as well as nonteaching services and from physicians utilizing a variety of rounding styles. Fourth, we had a very high participation rate (100%), probably due to the fact that our study was strategically aligned with participants’ daily work activities.

In conclusion, we found two distinct categories of issues that physicians perceived as most commonly delaying writing discharge orders on their patients. The first pertained to patients thought to definitely be ready for discharge and was related to the physicians having to care for other patients on their team. The second pertained to patients identified as possibly ready for discharge and was related to the need for care to be completed by a variety of ancillary services. Addressing each of these barriers would require different interventions and a need to weigh the potential improvements that could be achieved against the increased costs and/or delays in care for other patients that may result.

Disclosures

The authors report no conflicts of interest relevant to this work.