Hospitalizations frequently last longer than warranted by medical necessity alone, due to inefficiencies within the US healthcare system.[1, 2] Discharge delays place patients at risk for hospital‐acquired complications and increase costs. With the growing emphasis on high‐value care, hospital length of stay (LOS) has emerged as a key metric for inpatient care and will remain a central focus of hospital‐based improvement initiatives for the foreseeable future.

Hospitals may find it difficult to identify the primary drivers of inpatient LOS in a dynamic and increasingly complex healthcare system. Multiple recent policy changes have affected inpatient care. The Health Information Technology for Economic and Clinical Health Act of 2009 has led to widespread adoption of electronic health records (EHRs) that have markedly impacted provider workflows.[3] In October 2013, the Centers for Medicare & Medicaid Services implemented the 2‐midnight rule, which reclassified lower acuity inpatients with an expected stay <48 hours to observation status.[4] In January 2014, expansion of insurance coverage under the Affordable Care Act (ACA) altered payer mix for hospitals nationwide.[5] At a local level, hospitals that are rapidly adjusting resource allocation, capital investments, and marketing efforts and making complex operational decisions (eg, to open new units or change admission or referral algorithms) may simultaneously experience shifts in patient volumes, case‐mix index, and staffing ratios with downstream effects on LOS.

Given the myriad factors influencing inpatient LOS, hospital leaders may encounter real challenges in designing effective LOS reduction strategies. For example, they may expend significant resources on real‐time demand‐capacity management systems to improve hospital‐wide patient flow, but the resultant emphasis on bed placement and early discharges may shave only hours off average LOS.[6, 7] An alternative approach may be to target the small percentage of patients with prolonged hospitalizations who contribute disproportionately to the average LOS, as other initiatives focused on high utilizers have done.[8, 9, 10]

Our institution noted an increase in the average inpatient LOS for general medicine patients from 2012 to 2014, prompting a call to action by hospital leaders. We sought to characterize the predictors of prolonged hospitalizations among medicine patients to guide future efforts aimed at mitigating the contribution of prolonged LOS to overall LOS.

METHODS

RESULTS

We identified 18,363 inpatient discharges among 12,511 medicine patients between January 1, 2012 and December 31, 2014. Of these discharges, 416 (2.3%) demonstrated prolonged LOS. Prolonged hospitalizations accounted for 18.6% of total inpatient days. The average LOS during the study period was 4.8 days including patients with prolonged LOS and 4.0 days excluding patients with prolonged LOS, a contribution of 0.8 days.

Table 1 compares the characteristics of patients with and without prolonged LOS. Age, insurance, discharge disposition, palliative care consults, ICU stays, and surgeries were among the variables that differed significantly between the 2 groups. Among patients undergoing surgery, those with prolonged LOS were more likely to have surgery >24 hours after admission than those without prolonged LOS (85.7% vs 51.4%, P<0.001).

Unspecified sepsis was the most frequent primary diagnosis, regardless of LOS category (Table 2). However, the second through fifth most frequent diagnoses differed for patients with and without prolonged LOS.

In an adjusted logistic regression model (Table 3), we found lower odds of prolonged LOS for each 10‐year increase in age and higher odds of prolonged LOS for Medicaid insurance, discharge to home with home health, discharge to a postacute‐care or long‐term acute‐care facility, and in‐hospital death. Methicillin‐resistant Staphylococcus aureus (MRSA) septicemia, palliative care consults, ICU stays, and surgeries were all also associated with increased odds of prolonged LOS. We identified a statistically significant interaction between ICU stay and surgical procedure (odds ratio: 2.53, 95% confidence interval: 1.51‐4.26, P<0.001).

Sensitivity analyses using LOS >14 and >30 days yielded similar results to LOS >21 days (see Supporting Appendix Table 1 in the online version of this article).

DISCUSSION

We found that a small proportion of medicine patients with prolonged hospitalizations contributed substantially to both total inpatient days and average inpatient LOS. Such disproportionate healthcare utilization is concerning in light of the Institute of Medicine's charge for health systems to deliver timely, efficient, and equitable care.[11]

Few studies in the United States have analyzed patient characteristics that predict prolonged LOS, and to our knowledge, none have evaluated prolonged LOS specifically in general medicine patients.[12, 13, 14] Among selected surgical populations, prolonged hospitalizations are most often related to placement difficulties, operational delays, and payer‐related issues, rather than severity of illness, baseline comorbidities, or in‐hospital complications.[12, 13] In our study, we found that patients with prolonged LOS were more likely to require a palliative care consult, ICU stay, or surgery, all proxies for disease severity. Patients with prolonged LOS were also more likely to undergo surgery >24 hours after admission than those without prolonged LOS, suggesting that the former were either too unstable to proceed directly to surgery or developed complications later during their hospitalization. Even after controlling for palliative care consults, ICU stays, and surgeries, placement at a postacute‐care facility was strongly associated with prolonged LOS. Patients with prolonged LOS were also more likely to have Medicaid compared to other insurance types.

Our findings have several potential implications for efforts aimed at decreasing the number of and length of prolonged hospitalizations. Although demographic and clinical factors such as Medicaid insurance, ICU stays, and surgeries are generally not modifiable, they could, particularly in combination, be used to trigger earlier and more intensive case management involvement. A streamlined insurance approval process for Medicaid pending inpatients could be beneficial, given the recent expansion of Medicaid eligibility under the ACA. Hospital partnerships with postacute‐care facilities could also relieve bottlenecks in placement.[8] Chart review of the patients with MRSA septicemia and prolonged LOS indicated that development of an intensive outpatient parenteral antimicrobial therapy pathway with substance abuse counseling could provide an alternative to extended inpatient treatment for intravenous drug users with complicated infections.[15]

This study has several limitations. First, given the lack of consensus in the literature regarding the definition of a prolonged hospitalization, it is difficult to directly compare our results with existing studies.[8, 12, 13, 14] However, we believe LOS >21 days to be a meaningful cutoff for our cohort. Most demographic and clinical variables that were predictive at >21 days were also predictive at >14 and >30 days, which reassured us that the relationship between variables and prolonged LOS was stable at different thresholds. Second, our database did not allow us to fully adjust for baseline comorbidities or categorize the reasons for discharge delays. Finally, this was a single‐center program evaluation. Although this limits generalization to other institutions, we believe our approach may serve as a guide for others interested in reducing prolonged hospitalizations.

In summary, prolonged hospitalizations represent a potentially high‐yield target for LOS reduction efforts. Prolonged hospitalizations among medicine patients at our institution particularly affected Medicaid enrollees with complex hospital stays who were not discharged home. Further studies are needed to determine the specific reasons for unnecessary hospital days in this population.

Hospitalizations frequently last longer than warranted by medical necessity alone, due to inefficiencies within the US healthcare system.[1, 2] Discharge delays place patients at risk for hospital‐acquired complications and increase costs. With the growing emphasis on high‐value care, hospital length of stay (LOS) has emerged as a key metric for inpatient care and will remain a central focus of hospital‐based improvement initiatives for the foreseeable future.

Hospitals may find it difficult to identify the primary drivers of inpatient LOS in a dynamic and increasingly complex healthcare system. Multiple recent policy changes have affected inpatient care. The Health Information Technology for Economic and Clinical Health Act of 2009 has led to widespread adoption of electronic health records (EHRs) that have markedly impacted provider workflows.[3] In October 2013, the Centers for Medicare & Medicaid Services implemented the 2‐midnight rule, which reclassified lower acuity inpatients with an expected stay <48 hours to observation status.[4] In January 2014, expansion of insurance coverage under the Affordable Care Act (ACA) altered payer mix for hospitals nationwide.[5] At a local level, hospitals that are rapidly adjusting resource allocation, capital investments, and marketing efforts and making complex operational decisions (eg, to open new units or change admission or referral algorithms) may simultaneously experience shifts in patient volumes, case‐mix index, and staffing ratios with downstream effects on LOS.

Given the myriad factors influencing inpatient LOS, hospital leaders may encounter real challenges in designing effective LOS reduction strategies. For example, they may expend significant resources on real‐time demand‐capacity management systems to improve hospital‐wide patient flow, but the resultant emphasis on bed placement and early discharges may shave only hours off average LOS.[6, 7] An alternative approach may be to target the small percentage of patients with prolonged hospitalizations who contribute disproportionately to the average LOS, as other initiatives focused on high utilizers have done.[8, 9, 10]

Our institution noted an increase in the average inpatient LOS for general medicine patients from 2012 to 2014, prompting a call to action by hospital leaders. We sought to characterize the predictors of prolonged hospitalizations among medicine patients to guide future efforts aimed at mitigating the contribution of prolonged LOS to overall LOS.

METHODS

RESULTS

We identified 18,363 inpatient discharges among 12,511 medicine patients between January 1, 2012 and December 31, 2014. Of these discharges, 416 (2.3%) demonstrated prolonged LOS. Prolonged hospitalizations accounted for 18.6% of total inpatient days. The average LOS during the study period was 4.8 days including patients with prolonged LOS and 4.0 days excluding patients with prolonged LOS, a contribution of 0.8 days.

Table 1 compares the characteristics of patients with and without prolonged LOS. Age, insurance, discharge disposition, palliative care consults, ICU stays, and surgeries were among the variables that differed significantly between the 2 groups. Among patients undergoing surgery, those with prolonged LOS were more likely to have surgery >24 hours after admission than those without prolonged LOS (85.7% vs 51.4%, P<0.001).

Unspecified sepsis was the most frequent primary diagnosis, regardless of LOS category (Table 2). However, the second through fifth most frequent diagnoses differed for patients with and without prolonged LOS.

In an adjusted logistic regression model (Table 3), we found lower odds of prolonged LOS for each 10‐year increase in age and higher odds of prolonged LOS for Medicaid insurance, discharge to home with home health, discharge to a postacute‐care or long‐term acute‐care facility, and in‐hospital death. Methicillin‐resistant Staphylococcus aureus (MRSA) septicemia, palliative care consults, ICU stays, and surgeries were all also associated with increased odds of prolonged LOS. We identified a statistically significant interaction between ICU stay and surgical procedure (odds ratio: 2.53, 95% confidence interval: 1.51‐4.26, P<0.001).

Sensitivity analyses using LOS >14 and >30 days yielded similar results to LOS >21 days (see Supporting Appendix Table 1 in the online version of this article).

DISCUSSION

We found that a small proportion of medicine patients with prolonged hospitalizations contributed substantially to both total inpatient days and average inpatient LOS. Such disproportionate healthcare utilization is concerning in light of the Institute of Medicine's charge for health systems to deliver timely, efficient, and equitable care.[11]

Few studies in the United States have analyzed patient characteristics that predict prolonged LOS, and to our knowledge, none have evaluated prolonged LOS specifically in general medicine patients.[12, 13, 14] Among selected surgical populations, prolonged hospitalizations are most often related to placement difficulties, operational delays, and payer‐related issues, rather than severity of illness, baseline comorbidities, or in‐hospital complications.[12, 13] In our study, we found that patients with prolonged LOS were more likely to require a palliative care consult, ICU stay, or surgery, all proxies for disease severity. Patients with prolonged LOS were also more likely to undergo surgery >24 hours after admission than those without prolonged LOS, suggesting that the former were either too unstable to proceed directly to surgery or developed complications later during their hospitalization. Even after controlling for palliative care consults, ICU stays, and surgeries, placement at a postacute‐care facility was strongly associated with prolonged LOS. Patients with prolonged LOS were also more likely to have Medicaid compared to other insurance types.

Our findings have several potential implications for efforts aimed at decreasing the number of and length of prolonged hospitalizations. Although demographic and clinical factors such as Medicaid insurance, ICU stays, and surgeries are generally not modifiable, they could, particularly in combination, be used to trigger earlier and more intensive case management involvement. A streamlined insurance approval process for Medicaid pending inpatients could be beneficial, given the recent expansion of Medicaid eligibility under the ACA. Hospital partnerships with postacute‐care facilities could also relieve bottlenecks in placement.[8] Chart review of the patients with MRSA septicemia and prolonged LOS indicated that development of an intensive outpatient parenteral antimicrobial therapy pathway with substance abuse counseling could provide an alternative to extended inpatient treatment for intravenous drug users with complicated infections.[15]

This study has several limitations. First, given the lack of consensus in the literature regarding the definition of a prolonged hospitalization, it is difficult to directly compare our results with existing studies.[8, 12, 13, 14] However, we believe LOS >21 days to be a meaningful cutoff for our cohort. Most demographic and clinical variables that were predictive at >21 days were also predictive at >14 and >30 days, which reassured us that the relationship between variables and prolonged LOS was stable at different thresholds. Second, our database did not allow us to fully adjust for baseline comorbidities or categorize the reasons for discharge delays. Finally, this was a single‐center program evaluation. Although this limits generalization to other institutions, we believe our approach may serve as a guide for others interested in reducing prolonged hospitalizations.

In summary, prolonged hospitalizations represent a potentially high‐yield target for LOS reduction efforts. Prolonged hospitalizations among medicine patients at our institution particularly affected Medicaid enrollees with complex hospital stays who were not discharged home. Further studies are needed to determine the specific reasons for unnecessary hospital days in this population.

Hospitalizations frequently last longer than warranted by medical necessity alone, due to inefficiencies within the US healthcare system.[1, 2] Discharge delays place patients at risk for hospital‐acquired complications and increase costs. With the growing emphasis on high‐value care, hospital length of stay (LOS) has emerged as a key metric for inpatient care and will remain a central focus of hospital‐based improvement initiatives for the foreseeable future.

Hospitals may find it difficult to identify the primary drivers of inpatient LOS in a dynamic and increasingly complex healthcare system. Multiple recent policy changes have affected inpatient care. The Health Information Technology for Economic and Clinical Health Act of 2009 has led to widespread adoption of electronic health records (EHRs) that have markedly impacted provider workflows.[3] In October 2013, the Centers for Medicare & Medicaid Services implemented the 2‐midnight rule, which reclassified lower acuity inpatients with an expected stay <48 hours to observation status.[4] In January 2014, expansion of insurance coverage under the Affordable Care Act (ACA) altered payer mix for hospitals nationwide.[5] At a local level, hospitals that are rapidly adjusting resource allocation, capital investments, and marketing efforts and making complex operational decisions (eg, to open new units or change admission or referral algorithms) may simultaneously experience shifts in patient volumes, case‐mix index, and staffing ratios with downstream effects on LOS.

Given the myriad factors influencing inpatient LOS, hospital leaders may encounter real challenges in designing effective LOS reduction strategies. For example, they may expend significant resources on real‐time demand‐capacity management systems to improve hospital‐wide patient flow, but the resultant emphasis on bed placement and early discharges may shave only hours off average LOS.[6, 7] An alternative approach may be to target the small percentage of patients with prolonged hospitalizations who contribute disproportionately to the average LOS, as other initiatives focused on high utilizers have done.[8, 9, 10]

Our institution noted an increase in the average inpatient LOS for general medicine patients from 2012 to 2014, prompting a call to action by hospital leaders. We sought to characterize the predictors of prolonged hospitalizations among medicine patients to guide future efforts aimed at mitigating the contribution of prolonged LOS to overall LOS.

METHODS

RESULTS

We identified 18,363 inpatient discharges among 12,511 medicine patients between January 1, 2012 and December 31, 2014. Of these discharges, 416 (2.3%) demonstrated prolonged LOS. Prolonged hospitalizations accounted for 18.6% of total inpatient days. The average LOS during the study period was 4.8 days including patients with prolonged LOS and 4.0 days excluding patients with prolonged LOS, a contribution of 0.8 days.

Table 1 compares the characteristics of patients with and without prolonged LOS. Age, insurance, discharge disposition, palliative care consults, ICU stays, and surgeries were among the variables that differed significantly between the 2 groups. Among patients undergoing surgery, those with prolonged LOS were more likely to have surgery >24 hours after admission than those without prolonged LOS (85.7% vs 51.4%, P<0.001).

Unspecified sepsis was the most frequent primary diagnosis, regardless of LOS category (Table 2). However, the second through fifth most frequent diagnoses differed for patients with and without prolonged LOS.

In an adjusted logistic regression model (Table 3), we found lower odds of prolonged LOS for each 10‐year increase in age and higher odds of prolonged LOS for Medicaid insurance, discharge to home with home health, discharge to a postacute‐care or long‐term acute‐care facility, and in‐hospital death. Methicillin‐resistant Staphylococcus aureus (MRSA) septicemia, palliative care consults, ICU stays, and surgeries were all also associated with increased odds of prolonged LOS. We identified a statistically significant interaction between ICU stay and surgical procedure (odds ratio: 2.53, 95% confidence interval: 1.51‐4.26, P<0.001).

Sensitivity analyses using LOS >14 and >30 days yielded similar results to LOS >21 days (see Supporting Appendix Table 1 in the online version of this article).

DISCUSSION

We found that a small proportion of medicine patients with prolonged hospitalizations contributed substantially to both total inpatient days and average inpatient LOS. Such disproportionate healthcare utilization is concerning in light of the Institute of Medicine's charge for health systems to deliver timely, efficient, and equitable care.[11]

Few studies in the United States have analyzed patient characteristics that predict prolonged LOS, and to our knowledge, none have evaluated prolonged LOS specifically in general medicine patients.[12, 13, 14] Among selected surgical populations, prolonged hospitalizations are most often related to placement difficulties, operational delays, and payer‐related issues, rather than severity of illness, baseline comorbidities, or in‐hospital complications.[12, 13] In our study, we found that patients with prolonged LOS were more likely to require a palliative care consult, ICU stay, or surgery, all proxies for disease severity. Patients with prolonged LOS were also more likely to undergo surgery >24 hours after admission than those without prolonged LOS, suggesting that the former were either too unstable to proceed directly to surgery or developed complications later during their hospitalization. Even after controlling for palliative care consults, ICU stays, and surgeries, placement at a postacute‐care facility was strongly associated with prolonged LOS. Patients with prolonged LOS were also more likely to have Medicaid compared to other insurance types.

Our findings have several potential implications for efforts aimed at decreasing the number of and length of prolonged hospitalizations. Although demographic and clinical factors such as Medicaid insurance, ICU stays, and surgeries are generally not modifiable, they could, particularly in combination, be used to trigger earlier and more intensive case management involvement. A streamlined insurance approval process for Medicaid pending inpatients could be beneficial, given the recent expansion of Medicaid eligibility under the ACA. Hospital partnerships with postacute‐care facilities could also relieve bottlenecks in placement.[8] Chart review of the patients with MRSA septicemia and prolonged LOS indicated that development of an intensive outpatient parenteral antimicrobial therapy pathway with substance abuse counseling could provide an alternative to extended inpatient treatment for intravenous drug users with complicated infections.[15]

This study has several limitations. First, given the lack of consensus in the literature regarding the definition of a prolonged hospitalization, it is difficult to directly compare our results with existing studies.[8, 12, 13, 14] However, we believe LOS >21 days to be a meaningful cutoff for our cohort. Most demographic and clinical variables that were predictive at >21 days were also predictive at >14 and >30 days, which reassured us that the relationship between variables and prolonged LOS was stable at different thresholds. Second, our database did not allow us to fully adjust for baseline comorbidities or categorize the reasons for discharge delays. Finally, this was a single‐center program evaluation. Although this limits generalization to other institutions, we believe our approach may serve as a guide for others interested in reducing prolonged hospitalizations.

In summary, prolonged hospitalizations represent a potentially high‐yield target for LOS reduction efforts. Prolonged hospitalizations among medicine patients at our institution particularly affected Medicaid enrollees with complex hospital stays who were not discharged home. Further studies are needed to determine the specific reasons for unnecessary hospital days in this population.

In the spring of 1998 at the Society of Hospital Medicine's (SHM) (then known as the National Association of Inpatient Physicians) first annual meeting, Dr. John Eisenberg asked, If the hospitalist model of practice were a drug, do we have enough evidence about its risks and benefits to support its use? His question is only one of many often‐repeated dictums and phrases regarding how the hospitalist model of practice is organized and performs. These can serve as useful lenses to assess the past and future of the field.

Data and opinions used to answer Dr. Eisenberg's question continue to evolve. Many studies and opinions of its effects on costs and quality have appeared in the peer‐reviewed literature, including the Journal of Hospital Medicine, which has become a principal home for studies of the hospitalist model of care. In 1998, hospital medicine's impact on outcomes and costs was only beginning, and descriptions of the hospitalist's role in implementation of new programs, such as team‐based rounding models, geographic assignment of hospitalists, or the costs of interruptions, were not even on our radar. Effective management of these and other operational concerns will help ensure we are able to answer Dr. Eisenberg's question with an increasingly confident yes.

Early in the history of hospital medicine, it became common to speak of the voltage drop of information loss as a patient's care transitions to and from hospitalists and other caregivers. This term remains in common use today and encourages a focus on handoff communication. As of April 2015, the Journal of Hospital Medicine has published 15 articles that mention handoffs in the title, and many more that address the topic more peripherally.[1] Collectively, these provide thoughtful strategies to mitigate a voltage drop and its risks,[2] even though it persists and more work is needed to overcome it.

Referring to work as a hospitalist, many have said that this is a young doctor's game; one cannot do it for a whole career. The field is young enough that one cannot convincingly prove or disprove this idea, and evidence can be found on either side. Hospitalist burnout is distressingly common, though potentially similar to many other physician specialties.[3, 4, 5] Through both peer‐reviewed literature and more informal channels, primarily SHM activities, there is a substantial and growing set of data and opinions regarding factors related to burnout and potential mitigation strategies.

Donald Redelmeier observed that a hospitalist's time is to a large degree governed by a pager, in contrast to an office‐based physician whose time is governed by a clock.[6] Frequent interruptions delivered by a pager, many of which are of low importance and not urgent, are a significant issue for hospitalists, and to some extent all healthcare providers, and one begging for solutions.[7] Technology that replaces pagers will be helpful and will need to be paired with new methods around what is communicated, how urgently, and by what method.

Perhaps the most common dictum used by those who think about sharing best practices across our field is: If you have seen one hospitalist practice, you have seen one hospitalist practice. This has been invoked countless times as shorthand for the myriad ways hospitalist practices are organized, differing significantly in scheduling, workloads, compensation, leadership, cost structure, and other operational details. Here, the SHM serves as a valuable forum for exchange of ideas and information about the relative merits of different operational structures, and in 2014 published expert opinion regarding valuable characteristics of hospital medicine groups associated with success.[8]

In the 1990s, the principal mission of a hospitalist group was to replace primary care physicians who were leaving hospital practice and to increase efficiency of care. Many activities have since been added to this still‐important original mission, including improving performance on patient safety, quality, and satisfaction, and ensuring good hospital performance during the transition to dramatically different forms of reimbursement for services. Moreover, hospitals are increasingly organized into networks, most of which are now seeking to reduce variation in hospitalist organizational models and performance across all of their hospitals.[9]

This final dictum is a foundational one for our field, and will help us solve the challenges posed by the others: A hospitalist's job is to provide care for the sick person occupying a room in the hospital, and to care for and improve the performance of the hospital itself. Laurence Wellikson, Chief Executive Officer of the SHM, may have said this first. By embracing both of these goals, hospitalists have the opportunity to achieve much on behalf of individual patients and the healthcare system as a whole.

New dictums and sayings are sure to arise, and there is ample room for optimism that they will increasingly highlight the successes and vital role of hospital medicine.

In the spring of 1998 at the Society of Hospital Medicine's (SHM) (then known as the National Association of Inpatient Physicians) first annual meeting, Dr. John Eisenberg asked, If the hospitalist model of practice were a drug, do we have enough evidence about its risks and benefits to support its use? His question is only one of many often‐repeated dictums and phrases regarding how the hospitalist model of practice is organized and performs. These can serve as useful lenses to assess the past and future of the field.

Data and opinions used to answer Dr. Eisenberg's question continue to evolve. Many studies and opinions of its effects on costs and quality have appeared in the peer‐reviewed literature, including the Journal of Hospital Medicine, which has become a principal home for studies of the hospitalist model of care. In 1998, hospital medicine's impact on outcomes and costs was only beginning, and descriptions of the hospitalist's role in implementation of new programs, such as team‐based rounding models, geographic assignment of hospitalists, or the costs of interruptions, were not even on our radar. Effective management of these and other operational concerns will help ensure we are able to answer Dr. Eisenberg's question with an increasingly confident yes.

Early in the history of hospital medicine, it became common to speak of the voltage drop of information loss as a patient's care transitions to and from hospitalists and other caregivers. This term remains in common use today and encourages a focus on handoff communication. As of April 2015, the Journal of Hospital Medicine has published 15 articles that mention handoffs in the title, and many more that address the topic more peripherally.[1] Collectively, these provide thoughtful strategies to mitigate a voltage drop and its risks,[2] even though it persists and more work is needed to overcome it.

Referring to work as a hospitalist, many have said that this is a young doctor's game; one cannot do it for a whole career. The field is young enough that one cannot convincingly prove or disprove this idea, and evidence can be found on either side. Hospitalist burnout is distressingly common, though potentially similar to many other physician specialties.[3, 4, 5] Through both peer‐reviewed literature and more informal channels, primarily SHM activities, there is a substantial and growing set of data and opinions regarding factors related to burnout and potential mitigation strategies.

Donald Redelmeier observed that a hospitalist's time is to a large degree governed by a pager, in contrast to an office‐based physician whose time is governed by a clock.[6] Frequent interruptions delivered by a pager, many of which are of low importance and not urgent, are a significant issue for hospitalists, and to some extent all healthcare providers, and one begging for solutions.[7] Technology that replaces pagers will be helpful and will need to be paired with new methods around what is communicated, how urgently, and by what method.

Perhaps the most common dictum used by those who think about sharing best practices across our field is: If you have seen one hospitalist practice, you have seen one hospitalist practice. This has been invoked countless times as shorthand for the myriad ways hospitalist practices are organized, differing significantly in scheduling, workloads, compensation, leadership, cost structure, and other operational details. Here, the SHM serves as a valuable forum for exchange of ideas and information about the relative merits of different operational structures, and in 2014 published expert opinion regarding valuable characteristics of hospital medicine groups associated with success.[8]

In the 1990s, the principal mission of a hospitalist group was to replace primary care physicians who were leaving hospital practice and to increase efficiency of care. Many activities have since been added to this still‐important original mission, including improving performance on patient safety, quality, and satisfaction, and ensuring good hospital performance during the transition to dramatically different forms of reimbursement for services. Moreover, hospitals are increasingly organized into networks, most of which are now seeking to reduce variation in hospitalist organizational models and performance across all of their hospitals.[9]

This final dictum is a foundational one for our field, and will help us solve the challenges posed by the others: A hospitalist's job is to provide care for the sick person occupying a room in the hospital, and to care for and improve the performance of the hospital itself. Laurence Wellikson, Chief Executive Officer of the SHM, may have said this first. By embracing both of these goals, hospitalists have the opportunity to achieve much on behalf of individual patients and the healthcare system as a whole.

New dictums and sayings are sure to arise, and there is ample room for optimism that they will increasingly highlight the successes and vital role of hospital medicine.

In the spring of 1998 at the Society of Hospital Medicine's (SHM) (then known as the National Association of Inpatient Physicians) first annual meeting, Dr. John Eisenberg asked, If the hospitalist model of practice were a drug, do we have enough evidence about its risks and benefits to support its use? His question is only one of many often‐repeated dictums and phrases regarding how the hospitalist model of practice is organized and performs. These can serve as useful lenses to assess the past and future of the field.

Data and opinions used to answer Dr. Eisenberg's question continue to evolve. Many studies and opinions of its effects on costs and quality have appeared in the peer‐reviewed literature, including the Journal of Hospital Medicine, which has become a principal home for studies of the hospitalist model of care. In 1998, hospital medicine's impact on outcomes and costs was only beginning, and descriptions of the hospitalist's role in implementation of new programs, such as team‐based rounding models, geographic assignment of hospitalists, or the costs of interruptions, were not even on our radar. Effective management of these and other operational concerns will help ensure we are able to answer Dr. Eisenberg's question with an increasingly confident yes.

Early in the history of hospital medicine, it became common to speak of the voltage drop of information loss as a patient's care transitions to and from hospitalists and other caregivers. This term remains in common use today and encourages a focus on handoff communication. As of April 2015, the Journal of Hospital Medicine has published 15 articles that mention handoffs in the title, and many more that address the topic more peripherally.[1] Collectively, these provide thoughtful strategies to mitigate a voltage drop and its risks,[2] even though it persists and more work is needed to overcome it.

Referring to work as a hospitalist, many have said that this is a young doctor's game; one cannot do it for a whole career. The field is young enough that one cannot convincingly prove or disprove this idea, and evidence can be found on either side. Hospitalist burnout is distressingly common, though potentially similar to many other physician specialties.[3, 4, 5] Through both peer‐reviewed literature and more informal channels, primarily SHM activities, there is a substantial and growing set of data and opinions regarding factors related to burnout and potential mitigation strategies.

Donald Redelmeier observed that a hospitalist's time is to a large degree governed by a pager, in contrast to an office‐based physician whose time is governed by a clock.[6] Frequent interruptions delivered by a pager, many of which are of low importance and not urgent, are a significant issue for hospitalists, and to some extent all healthcare providers, and one begging for solutions.[7] Technology that replaces pagers will be helpful and will need to be paired with new methods around what is communicated, how urgently, and by what method.

Perhaps the most common dictum used by those who think about sharing best practices across our field is: If you have seen one hospitalist practice, you have seen one hospitalist practice. This has been invoked countless times as shorthand for the myriad ways hospitalist practices are organized, differing significantly in scheduling, workloads, compensation, leadership, cost structure, and other operational details. Here, the SHM serves as a valuable forum for exchange of ideas and information about the relative merits of different operational structures, and in 2014 published expert opinion regarding valuable characteristics of hospital medicine groups associated with success.[8]

In the 1990s, the principal mission of a hospitalist group was to replace primary care physicians who were leaving hospital practice and to increase efficiency of care. Many activities have since been added to this still‐important original mission, including improving performance on patient safety, quality, and satisfaction, and ensuring good hospital performance during the transition to dramatically different forms of reimbursement for services. Moreover, hospitals are increasingly organized into networks, most of which are now seeking to reduce variation in hospitalist organizational models and performance across all of their hospitals.[9]

This final dictum is a foundational one for our field, and will help us solve the challenges posed by the others: A hospitalist's job is to provide care for the sick person occupying a room in the hospital, and to care for and improve the performance of the hospital itself. Laurence Wellikson, Chief Executive Officer of the SHM, may have said this first. By embracing both of these goals, hospitalists have the opportunity to achieve much on behalf of individual patients and the healthcare system as a whole.

New dictums and sayings are sure to arise, and there is ample room for optimism that they will increasingly highlight the successes and vital role of hospital medicine.

Hospitalists are a growing workforce numbering over 40,000 physicians, one‐third of whom are women.[1] Flexibility of work schedules and control over personal time have been the traditional selling points of the specialty.[2] Multiple studies of physician work life reveal growing physician dissatisfaction and a high prevalence of burnout.[3] To mitigate burnout risk, leaders in hospital medicine recognize the importance of creating a sustainable profession that offers both job and career satisfaction as well as work‐life balance and, importantly, fairness within the work environment.[4] Although success in some of these endeavors has been realized sporadically, sustaining work‐life balance and fairness in the specialty remains a work in progress, whereas evidence of high job attrition and pay inequities remain.[5, 6]

Pay inequity for women relative to men continues to be pervasive in medicine, including among early‐career physicians, researchers, and various specialists.[6, 7, 8, 9, 10, 11, 12, 13] The earnings gap seems to persist for physicians, even as federal efforts such as the Fair Pay Act of 2013 and the Paycheck Fairness Act of 2014 aim to end wage discrimination.[11, 14] Differences in specialty, part‐time status, and practice type do not mitigate the disparity.[8, 10, 15] Additional explanations have been proposed to explain the variability, including gender differences in negotiating skills, lack of opportunities to join networks of influence within organizations, and implicit or explicit bias and discrimination.[12, 16, 17, 18, 19, 20]

The earnings gap is also a consequence of what is commonly called the glass ceiling.[18, 19] Most agree that obstacles to fair advancement of women include absence of collaborative environments and role models who have successfully achieved work‐life balance.[17, 20, 21, 22] Somewhat surprisingly, women leaders in medicine seem to suffer greater income disparity than nonleaders; this income gap is prevalent among leaders in other elite professions as well.[7, 23] It is unknown whether women physicians' emphasis on work‐life balance, seen repeatedly in surveys, explains any of the pay disparity.[24] Little research to date has examined whether work‐life priorities of women in hospital medicine differ from men.

In this study, we sought to examine differences in job priorities between men and women hospitalists. In particular, we examine the relative prioritization of substantial pay to job satisfaction. We also examined gender differences in work patterns and earnings to explore potential sources of the persistent gender earnings gap.

METHODS

We analyzed data from the 20092010 Hospital Medicine Physician Worklife Survey, the design of which is detailed elsewhere.[4] Briefly, a 118‐item survey was administered by mail to a stratified sample of hospitalists from the Society of Hospital Medicine database and 3 large multisite hospitalist groups. A single survey item asked respondents to identify up to 4 out of 12 most important domains to their satisfaction with a hospitalist job. The domains were distilled from focus groups of nationally representative hospitalists as described previously,[4] and the survey item allowed up to one‐third of these domains to be identified as respondents' personal priorities. The list included: optimal variety of tasks, optimal workload, substantial pay, collegiality with other physicians, recognition by leaders, rewarding relationships with patients, satisfaction with nurses, optimal autonomy, control over personal time, fairness within organization, ample availability of resources to do job, and organizational climate of trust and belonging. We tabulated and ranked the frequency with which respondents selected each satisfaction domain by gender. Due to the nonstandard format of the survey item, we a priori decided to analyze only responses that were completed as instructed.

We also used demographic data including detailed work characteristics, clinical and nonclinical workload, total pretax earnings in 2009 as a hospitalist, and self‐identification as leader of their hospital medicine group. Respondent characteristics were tabulated and gender differences were tested using the t test, rank sum test, and the Fischer exact test as appropriate. We also listed the number of nonrespondents for each item. In estimating gender differences in earnings, we opted to use multiple‐imputation techniques to more conservatively account for greater variance inherent in the presence of missing data. Consistent with existing guidelines,[25] we demonstrated that item responses were not missing monotonically by visually inspecting patterns of nonresponse. We further demonstrated that data were missing at random by showing that response patterns of completed survey items did not predict whether or not a given variable response was missing using logistic regression models. We found no significant differences between respondents with complete and missing data. We verified that appropriate regression models for each variable on every other variable converged. We used Stata 13.1 (StataCorp, College Station, TX) to perform multiple imputations using chain equations (mi impute chain) to create 10 imputed tables for 7 normally distributed continuous variables using the ordinary least squares method, 3 non‐normally distributed variables using the predictive mean matching method, 2 nonordinal categorical variables using the multinomial logit method, and 1 binary variable using the logit method.[26, 27] Gender, pediatric specialty status, region of practice, and whether or not respondents prioritized substantial pay for job satisfaction were used as regular variables without missing data points.

Differences in earnings were assessed using a multivariate ordinary linear regression model applied to the imputed datasets fitted by forward selection of explanatory variables using P < 0.20 in bivariate analysis for inclusion and manual backward elimination of all statistically nonsignificant variables. We tested the significance of the women leader interaction term in the final parsimonious model. We used the usual significance threshold of P < 0.05 for inferences. Our analysis of publicly available anonymous data was exempt from IRB review.

RESULTS

Of the 816 survey respondents (response rate 25.6%), 40 either omitted the item soliciting work priorities or completed it incorrectly. Data from the remaining 776 respondents were used for the present analysis. Respondent characteristics are tabulated in Table 1. The characteristics of hospitalists by age, gender, specialty, practice model, and practice region were representative of US hospitalists from other surveys.[28]

Several gender differences were seen in the characteristics of hospitalists and their work (Table 1). Women compared to men hospitalists were less likely to be leaders, more likely to be pediatricians, work in university settings, and practice in Western states. Women compared to men, on average, were younger by 3 years, worked fewer full‐time equivalents (FTEs), worked a greater percentage of nights, and reported fewer billable encounters per shift. They were also more likely to be divorced or separated.

Job satisfaction priorities differed for women and men hospitalists. Table 2 lists job satisfaction domains in descending order of the frequency prioritized by men. The largest proportion of women and men prioritized optimal workload. However, although substantial pay was prioritized next most frequently by men, more women prioritized collegiality and control over personal time than substantial pay.

Key differences in individual characteristics, work patterns, and indicating substantial pay as a priority were associated with self‐reported total earnings in 2009 from respondents' work as a hospitalist. As shown in Table 3, the inclusion of detailed productivity measures such as FTE, days of monthly clinical work, and estimated number of daily billable encounters yielded a model that explained 33% of variance in earnings. After adjusting for significant covariates including pediatric specialty, practice model, geography, and amount and type of clinical work, the estimated underpayment of women compared to men was $14,581. Hospitalists who prioritized substantial pay earned $10,771 more than those who did not. The female x leader interaction term testing the hypothesis that gender disparity is greater among leaders than frontline hospitalists was not statistically significant ($16,720, P = 0.087) and excluded from the final model.

DISCUSSION

In a national stratified sample of US hospitalists, we found gender differences in job satisfaction priorities and hospitalist work characteristics. We also confirmed the persistence of a substantial gender earnings disparity. Lower earnings among women compared to men hospitalists were present in our data after controlling for age, pediatric specialty, practice model, geography, type of clinical work, and productivity measures. The gender earnings disparity noted in 1999[6] persists, although it appears to have decreased, possibly indicating progress toward equity. We showed that women hospitalists' relative tendency not to prioritize pay explains a significant portion of the residual income gap.

Hoff examined hospitalist earnings in a large national survey of hospitalists in 1999. Our cohorts differed in age and experience (both lower in the Hoff study). An estimated $24,000 ($124,266 vs. $148,132) earnings gap between women and men was greater than our estimate of $14,581 following an interval of 10 years. Although survey items differed, both studies found that women were less interested in pay than men when considering a hospitalist job. Hoff also found that work setting and attitudes about pay and lifestyle were significantly related to earnings. We extended the previous analyses of gender differences in job satisfaction priorities, work, and demographic characteristics to explain the earnings gap and understand how it may be remedied.

When considering job satisfaction, we found that more men than women prioritized substantial pay and that prioritization of substantial pay was directly related to higher earnings. Therefore, fewer women prioritizing pay partly explains women's lower earnings. Reasons for why fewer women prioritize pay were not assessed in this study but may include factors like being part of 2‐income households and competing commitments.[29] Priorities may even be influenced by empirically observed gender differences in discussions of financial matters, governed by cultural norms. Such norms may implicitly sanction employers to offer women less pay than men for the same or similar work. Women may disadvantage themselves by negotiating less or less well than men for higher starting and promotion salaries. They may be perceived more negatively than men when they do negotiate pay, leading to unintended negative consequences such as loss of social networks, decreased likability, and even loss of job offers.[29, 30, 31, 32]

More women prioritized optimal variety of tasks (6th most prevalent among women and 10th among men). Women who highly rate optimal variety of tasks as a job satisfier may choose positions in which they teach, perform research, and participate in hospital committees and quality‐improvement work, but offer lower pay. Yet hours per month doing nonclinical work was not significantly different between men and women, nor associated with earnings differences in our earnings models. Understanding whether women self‐select into hospitalist jobs with like‐minded colleagues to achieve complementary fit or end up supplementing their skills with hospitalists with different priorities may inform strategies to reduce the gender income disparity.[5] Unlike disparities between various hospital medicine groups, systematic disparities within practices risk generating low levels of organizational fairness and burnout among employees.

Not surprisingly, productivity was positively associated with earnings but did not fully account for the gender earnings gap. Our data demonstrated that women, on average, were associated with work characteristics that expectedly generate less compensation. For example, women were younger, more often part time, academic, pediatric, less often leaders, and reported fewer billable encounters compared to men. These differences account for some of the earnings gap between men and women, but these factors were controlled for in the earnings model. In addition, our analysis may have underestimated the gap by not incorporating loss of fringe benefits from part‐time status and not comprehensively counting incentive pay associated with high productivity. Other work patterns more commonly associated with women suggest an imbalance in reimbursement. More women than men work nights that are often compensated at higher rates than daytime work, yet their average pay was less, suggesting that compensation for night work may need to be adjusted to reflect its unique burdens and responsibilities.[33]

Although the gender pay gap was not more extreme among leaders compared to frontline hospitalists in our data, the trend, nonetheless, underscores an important consideration. Whereas clinical work is paid for in mostly measurable ways, pay for leadership may be influenced by intangible factors such as reputation, negotiation, and confidence that may disadvantage women relative to men.[7, 19, 23, 34, 35, 36] Efforts to overcome implicit gender bias should be most effective when we consciously couple fair promotion of women to leadership with fair compensation commensurate with their male peers.[21]

Our data are vulnerable to nonresponse bias.[1, 4, 5] Post hoc analyses demonstrated that distributions of age, gender, practice model and region of our respondents were similar to other nationally representative cohorts of hospitalists. Consequently, we believe our data can make valid estimates about a nationally representative sample of hospitalists. However, we acknowledge several additional weaknesses of self‐reported data, including recall bias and accuracy of productivity figures, which were rounded to variable significant digits by respondents. Earnings analysis using this data was intended to be exploratory, but the findings echoed analyses using more authoritative data sources.[11] Still, we made inferences conservatively by adopting multiple imputation techniques for dealing with nonresponse surveys in adherence to established reporting guidelines.[25] We also note several limitations relevant to multiple imputations. The greater prevalence of missing data for survey items soliciting earnings and the number of billable encounters suggest they were not truly missing at random as assumed. However, we showed that missingness is unrelated to the variables under study, justifying use of the technique. The wider measures of variance derived from multiple imputations make us vulnerable to not detecting associations that may exist.

The gender earnings gap found in hospital medicine echoes the gap found in multiple medical specialties, including but not limited to pediatrics, academic medicine, gastroenterology, and plastic surgery.[7, 8, 9, 11, 12, 13, 37] Hospital medicine employment models and practice patterns have important structural differences compared to previously studied populations that could mitigate factors contributing to women physicians' lower earnings. However, despite well‐defined working hours, lack of control over the number of patient encounters per day and high prevalence of hospital‐employed practice models, the gender earnings gap persists. We showed that lower prioritization for pay may reflect the self‐selection of women into lower paying jobs. Unmeasured factors, including implicit bias and differences in negotiations, social networks and mentoring opportunities[38, 39] may also contribute to pay differences between men and women hospitalists. As hospital medicine tackles gender inequities and other disparities, strategies to assess and address fair physician compensation must be on the table.

Hospitalists are a growing workforce numbering over 40,000 physicians, one‐third of whom are women.[1] Flexibility of work schedules and control over personal time have been the traditional selling points of the specialty.[2] Multiple studies of physician work life reveal growing physician dissatisfaction and a high prevalence of burnout.[3] To mitigate burnout risk, leaders in hospital medicine recognize the importance of creating a sustainable profession that offers both job and career satisfaction as well as work‐life balance and, importantly, fairness within the work environment.[4] Although success in some of these endeavors has been realized sporadically, sustaining work‐life balance and fairness in the specialty remains a work in progress, whereas evidence of high job attrition and pay inequities remain.[5, 6]

Pay inequity for women relative to men continues to be pervasive in medicine, including among early‐career physicians, researchers, and various specialists.[6, 7, 8, 9, 10, 11, 12, 13] The earnings gap seems to persist for physicians, even as federal efforts such as the Fair Pay Act of 2013 and the Paycheck Fairness Act of 2014 aim to end wage discrimination.[11, 14] Differences in specialty, part‐time status, and practice type do not mitigate the disparity.[8, 10, 15] Additional explanations have been proposed to explain the variability, including gender differences in negotiating skills, lack of opportunities to join networks of influence within organizations, and implicit or explicit bias and discrimination.[12, 16, 17, 18, 19, 20]

The earnings gap is also a consequence of what is commonly called the glass ceiling.[18, 19] Most agree that obstacles to fair advancement of women include absence of collaborative environments and role models who have successfully achieved work‐life balance.[17, 20, 21, 22] Somewhat surprisingly, women leaders in medicine seem to suffer greater income disparity than nonleaders; this income gap is prevalent among leaders in other elite professions as well.[7, 23] It is unknown whether women physicians' emphasis on work‐life balance, seen repeatedly in surveys, explains any of the pay disparity.[24] Little research to date has examined whether work‐life priorities of women in hospital medicine differ from men.

In this study, we sought to examine differences in job priorities between men and women hospitalists. In particular, we examine the relative prioritization of substantial pay to job satisfaction. We also examined gender differences in work patterns and earnings to explore potential sources of the persistent gender earnings gap.

METHODS

We analyzed data from the 20092010 Hospital Medicine Physician Worklife Survey, the design of which is detailed elsewhere.[4] Briefly, a 118‐item survey was administered by mail to a stratified sample of hospitalists from the Society of Hospital Medicine database and 3 large multisite hospitalist groups. A single survey item asked respondents to identify up to 4 out of 12 most important domains to their satisfaction with a hospitalist job. The domains were distilled from focus groups of nationally representative hospitalists as described previously,[4] and the survey item allowed up to one‐third of these domains to be identified as respondents' personal priorities. The list included: optimal variety of tasks, optimal workload, substantial pay, collegiality with other physicians, recognition by leaders, rewarding relationships with patients, satisfaction with nurses, optimal autonomy, control over personal time, fairness within organization, ample availability of resources to do job, and organizational climate of trust and belonging. We tabulated and ranked the frequency with which respondents selected each satisfaction domain by gender. Due to the nonstandard format of the survey item, we a priori decided to analyze only responses that were completed as instructed.

We also used demographic data including detailed work characteristics, clinical and nonclinical workload, total pretax earnings in 2009 as a hospitalist, and self‐identification as leader of their hospital medicine group. Respondent characteristics were tabulated and gender differences were tested using the t test, rank sum test, and the Fischer exact test as appropriate. We also listed the number of nonrespondents for each item. In estimating gender differences in earnings, we opted to use multiple‐imputation techniques to more conservatively account for greater variance inherent in the presence of missing data. Consistent with existing guidelines,[25] we demonstrated that item responses were not missing monotonically by visually inspecting patterns of nonresponse. We further demonstrated that data were missing at random by showing that response patterns of completed survey items did not predict whether or not a given variable response was missing using logistic regression models. We found no significant differences between respondents with complete and missing data. We verified that appropriate regression models for each variable on every other variable converged. We used Stata 13.1 (StataCorp, College Station, TX) to perform multiple imputations using chain equations (mi impute chain) to create 10 imputed tables for 7 normally distributed continuous variables using the ordinary least squares method, 3 non‐normally distributed variables using the predictive mean matching method, 2 nonordinal categorical variables using the multinomial logit method, and 1 binary variable using the logit method.[26, 27] Gender, pediatric specialty status, region of practice, and whether or not respondents prioritized substantial pay for job satisfaction were used as regular variables without missing data points.

Differences in earnings were assessed using a multivariate ordinary linear regression model applied to the imputed datasets fitted by forward selection of explanatory variables using P < 0.20 in bivariate analysis for inclusion and manual backward elimination of all statistically nonsignificant variables. We tested the significance of the women leader interaction term in the final parsimonious model. We used the usual significance threshold of P < 0.05 for inferences. Our analysis of publicly available anonymous data was exempt from IRB review.

RESULTS

Of the 816 survey respondents (response rate 25.6%), 40 either omitted the item soliciting work priorities or completed it incorrectly. Data from the remaining 776 respondents were used for the present analysis. Respondent characteristics are tabulated in Table 1. The characteristics of hospitalists by age, gender, specialty, practice model, and practice region were representative of US hospitalists from other surveys.[28]

Several gender differences were seen in the characteristics of hospitalists and their work (Table 1). Women compared to men hospitalists were less likely to be leaders, more likely to be pediatricians, work in university settings, and practice in Western states. Women compared to men, on average, were younger by 3 years, worked fewer full‐time equivalents (FTEs), worked a greater percentage of nights, and reported fewer billable encounters per shift. They were also more likely to be divorced or separated.

Job satisfaction priorities differed for women and men hospitalists. Table 2 lists job satisfaction domains in descending order of the frequency prioritized by men. The largest proportion of women and men prioritized optimal workload. However, although substantial pay was prioritized next most frequently by men, more women prioritized collegiality and control over personal time than substantial pay.

Key differences in individual characteristics, work patterns, and indicating substantial pay as a priority were associated with self‐reported total earnings in 2009 from respondents' work as a hospitalist. As shown in Table 3, the inclusion of detailed productivity measures such as FTE, days of monthly clinical work, and estimated number of daily billable encounters yielded a model that explained 33% of variance in earnings. After adjusting for significant covariates including pediatric specialty, practice model, geography, and amount and type of clinical work, the estimated underpayment of women compared to men was $14,581. Hospitalists who prioritized substantial pay earned $10,771 more than those who did not. The female x leader interaction term testing the hypothesis that gender disparity is greater among leaders than frontline hospitalists was not statistically significant ($16,720, P = 0.087) and excluded from the final model.

DISCUSSION

In a national stratified sample of US hospitalists, we found gender differences in job satisfaction priorities and hospitalist work characteristics. We also confirmed the persistence of a substantial gender earnings disparity. Lower earnings among women compared to men hospitalists were present in our data after controlling for age, pediatric specialty, practice model, geography, type of clinical work, and productivity measures. The gender earnings disparity noted in 1999[6] persists, although it appears to have decreased, possibly indicating progress toward equity. We showed that women hospitalists' relative tendency not to prioritize pay explains a significant portion of the residual income gap.

Hoff examined hospitalist earnings in a large national survey of hospitalists in 1999. Our cohorts differed in age and experience (both lower in the Hoff study). An estimated $24,000 ($124,266 vs. $148,132) earnings gap between women and men was greater than our estimate of $14,581 following an interval of 10 years. Although survey items differed, both studies found that women were less interested in pay than men when considering a hospitalist job. Hoff also found that work setting and attitudes about pay and lifestyle were significantly related to earnings. We extended the previous analyses of gender differences in job satisfaction priorities, work, and demographic characteristics to explain the earnings gap and understand how it may be remedied.

When considering job satisfaction, we found that more men than women prioritized substantial pay and that prioritization of substantial pay was directly related to higher earnings. Therefore, fewer women prioritizing pay partly explains women's lower earnings. Reasons for why fewer women prioritize pay were not assessed in this study but may include factors like being part of 2‐income households and competing commitments.[29] Priorities may even be influenced by empirically observed gender differences in discussions of financial matters, governed by cultural norms. Such norms may implicitly sanction employers to offer women less pay than men for the same or similar work. Women may disadvantage themselves by negotiating less or less well than men for higher starting and promotion salaries. They may be perceived more negatively than men when they do negotiate pay, leading to unintended negative consequences such as loss of social networks, decreased likability, and even loss of job offers.[29, 30, 31, 32]

More women prioritized optimal variety of tasks (6th most prevalent among women and 10th among men). Women who highly rate optimal variety of tasks as a job satisfier may choose positions in which they teach, perform research, and participate in hospital committees and quality‐improvement work, but offer lower pay. Yet hours per month doing nonclinical work was not significantly different between men and women, nor associated with earnings differences in our earnings models. Understanding whether women self‐select into hospitalist jobs with like‐minded colleagues to achieve complementary fit or end up supplementing their skills with hospitalists with different priorities may inform strategies to reduce the gender income disparity.[5] Unlike disparities between various hospital medicine groups, systematic disparities within practices risk generating low levels of organizational fairness and burnout among employees.

Not surprisingly, productivity was positively associated with earnings but did not fully account for the gender earnings gap. Our data demonstrated that women, on average, were associated with work characteristics that expectedly generate less compensation. For example, women were younger, more often part time, academic, pediatric, less often leaders, and reported fewer billable encounters compared to men. These differences account for some of the earnings gap between men and women, but these factors were controlled for in the earnings model. In addition, our analysis may have underestimated the gap by not incorporating loss of fringe benefits from part‐time status and not comprehensively counting incentive pay associated with high productivity. Other work patterns more commonly associated with women suggest an imbalance in reimbursement. More women than men work nights that are often compensated at higher rates than daytime work, yet their average pay was less, suggesting that compensation for night work may need to be adjusted to reflect its unique burdens and responsibilities.[33]

Although the gender pay gap was not more extreme among leaders compared to frontline hospitalists in our data, the trend, nonetheless, underscores an important consideration. Whereas clinical work is paid for in mostly measurable ways, pay for leadership may be influenced by intangible factors such as reputation, negotiation, and confidence that may disadvantage women relative to men.[7, 19, 23, 34, 35, 36] Efforts to overcome implicit gender bias should be most effective when we consciously couple fair promotion of women to leadership with fair compensation commensurate with their male peers.[21]

Our data are vulnerable to nonresponse bias.[1, 4, 5] Post hoc analyses demonstrated that distributions of age, gender, practice model and region of our respondents were similar to other nationally representative cohorts of hospitalists. Consequently, we believe our data can make valid estimates about a nationally representative sample of hospitalists. However, we acknowledge several additional weaknesses of self‐reported data, including recall bias and accuracy of productivity figures, which were rounded to variable significant digits by respondents. Earnings analysis using this data was intended to be exploratory, but the findings echoed analyses using more authoritative data sources.[11] Still, we made inferences conservatively by adopting multiple imputation techniques for dealing with nonresponse surveys in adherence to established reporting guidelines.[25] We also note several limitations relevant to multiple imputations. The greater prevalence of missing data for survey items soliciting earnings and the number of billable encounters suggest they were not truly missing at random as assumed. However, we showed that missingness is unrelated to the variables under study, justifying use of the technique. The wider measures of variance derived from multiple imputations make us vulnerable to not detecting associations that may exist.

The gender earnings gap found in hospital medicine echoes the gap found in multiple medical specialties, including but not limited to pediatrics, academic medicine, gastroenterology, and plastic surgery.[7, 8, 9, 11, 12, 13, 37] Hospital medicine employment models and practice patterns have important structural differences compared to previously studied populations that could mitigate factors contributing to women physicians' lower earnings. However, despite well‐defined working hours, lack of control over the number of patient encounters per day and high prevalence of hospital‐employed practice models, the gender earnings gap persists. We showed that lower prioritization for pay may reflect the self‐selection of women into lower paying jobs. Unmeasured factors, including implicit bias and differences in negotiations, social networks and mentoring opportunities[38, 39] may also contribute to pay differences between men and women hospitalists. As hospital medicine tackles gender inequities and other disparities, strategies to assess and address fair physician compensation must be on the table.

Hospitalists are a growing workforce numbering over 40,000 physicians, one‐third of whom are women.[1] Flexibility of work schedules and control over personal time have been the traditional selling points of the specialty.[2] Multiple studies of physician work life reveal growing physician dissatisfaction and a high prevalence of burnout.[3] To mitigate burnout risk, leaders in hospital medicine recognize the importance of creating a sustainable profession that offers both job and career satisfaction as well as work‐life balance and, importantly, fairness within the work environment.[4] Although success in some of these endeavors has been realized sporadically, sustaining work‐life balance and fairness in the specialty remains a work in progress, whereas evidence of high job attrition and pay inequities remain.[5, 6]

Pay inequity for women relative to men continues to be pervasive in medicine, including among early‐career physicians, researchers, and various specialists.[6, 7, 8, 9, 10, 11, 12, 13] The earnings gap seems to persist for physicians, even as federal efforts such as the Fair Pay Act of 2013 and the Paycheck Fairness Act of 2014 aim to end wage discrimination.[11, 14] Differences in specialty, part‐time status, and practice type do not mitigate the disparity.[8, 10, 15] Additional explanations have been proposed to explain the variability, including gender differences in negotiating skills, lack of opportunities to join networks of influence within organizations, and implicit or explicit bias and discrimination.[12, 16, 17, 18, 19, 20]

The earnings gap is also a consequence of what is commonly called the glass ceiling.[18, 19] Most agree that obstacles to fair advancement of women include absence of collaborative environments and role models who have successfully achieved work‐life balance.[17, 20, 21, 22] Somewhat surprisingly, women leaders in medicine seem to suffer greater income disparity than nonleaders; this income gap is prevalent among leaders in other elite professions as well.[7, 23] It is unknown whether women physicians' emphasis on work‐life balance, seen repeatedly in surveys, explains any of the pay disparity.[24] Little research to date has examined whether work‐life priorities of women in hospital medicine differ from men.

In this study, we sought to examine differences in job priorities between men and women hospitalists. In particular, we examine the relative prioritization of substantial pay to job satisfaction. We also examined gender differences in work patterns and earnings to explore potential sources of the persistent gender earnings gap.

METHODS

We analyzed data from the 20092010 Hospital Medicine Physician Worklife Survey, the design of which is detailed elsewhere.[4] Briefly, a 118‐item survey was administered by mail to a stratified sample of hospitalists from the Society of Hospital Medicine database and 3 large multisite hospitalist groups. A single survey item asked respondents to identify up to 4 out of 12 most important domains to their satisfaction with a hospitalist job. The domains were distilled from focus groups of nationally representative hospitalists as described previously,[4] and the survey item allowed up to one‐third of these domains to be identified as respondents' personal priorities. The list included: optimal variety of tasks, optimal workload, substantial pay, collegiality with other physicians, recognition by leaders, rewarding relationships with patients, satisfaction with nurses, optimal autonomy, control over personal time, fairness within organization, ample availability of resources to do job, and organizational climate of trust and belonging. We tabulated and ranked the frequency with which respondents selected each satisfaction domain by gender. Due to the nonstandard format of the survey item, we a priori decided to analyze only responses that were completed as instructed.

We also used demographic data including detailed work characteristics, clinical and nonclinical workload, total pretax earnings in 2009 as a hospitalist, and self‐identification as leader of their hospital medicine group. Respondent characteristics were tabulated and gender differences were tested using the t test, rank sum test, and the Fischer exact test as appropriate. We also listed the number of nonrespondents for each item. In estimating gender differences in earnings, we opted to use multiple‐imputation techniques to more conservatively account for greater variance inherent in the presence of missing data. Consistent with existing guidelines,[25] we demonstrated that item responses were not missing monotonically by visually inspecting patterns of nonresponse. We further demonstrated that data were missing at random by showing that response patterns of completed survey items did not predict whether or not a given variable response was missing using logistic regression models. We found no significant differences between respondents with complete and missing data. We verified that appropriate regression models for each variable on every other variable converged. We used Stata 13.1 (StataCorp, College Station, TX) to perform multiple imputations using chain equations (mi impute chain) to create 10 imputed tables for 7 normally distributed continuous variables using the ordinary least squares method, 3 non‐normally distributed variables using the predictive mean matching method, 2 nonordinal categorical variables using the multinomial logit method, and 1 binary variable using the logit method.[26, 27] Gender, pediatric specialty status, region of practice, and whether or not respondents prioritized substantial pay for job satisfaction were used as regular variables without missing data points.

Differences in earnings were assessed using a multivariate ordinary linear regression model applied to the imputed datasets fitted by forward selection of explanatory variables using P < 0.20 in bivariate analysis for inclusion and manual backward elimination of all statistically nonsignificant variables. We tested the significance of the women leader interaction term in the final parsimonious model. We used the usual significance threshold of P < 0.05 for inferences. Our analysis of publicly available anonymous data was exempt from IRB review.

RESULTS

Of the 816 survey respondents (response rate 25.6%), 40 either omitted the item soliciting work priorities or completed it incorrectly. Data from the remaining 776 respondents were used for the present analysis. Respondent characteristics are tabulated in Table 1. The characteristics of hospitalists by age, gender, specialty, practice model, and practice region were representative of US hospitalists from other surveys.[28]

Several gender differences were seen in the characteristics of hospitalists and their work (Table 1). Women compared to men hospitalists were less likely to be leaders, more likely to be pediatricians, work in university settings, and practice in Western states. Women compared to men, on average, were younger by 3 years, worked fewer full‐time equivalents (FTEs), worked a greater percentage of nights, and reported fewer billable encounters per shift. They were also more likely to be divorced or separated.

Job satisfaction priorities differed for women and men hospitalists. Table 2 lists job satisfaction domains in descending order of the frequency prioritized by men. The largest proportion of women and men prioritized optimal workload. However, although substantial pay was prioritized next most frequently by men, more women prioritized collegiality and control over personal time than substantial pay.

Key differences in individual characteristics, work patterns, and indicating substantial pay as a priority were associated with self‐reported total earnings in 2009 from respondents' work as a hospitalist. As shown in Table 3, the inclusion of detailed productivity measures such as FTE, days of monthly clinical work, and estimated number of daily billable encounters yielded a model that explained 33% of variance in earnings. After adjusting for significant covariates including pediatric specialty, practice model, geography, and amount and type of clinical work, the estimated underpayment of women compared to men was $14,581. Hospitalists who prioritized substantial pay earned $10,771 more than those who did not. The female x leader interaction term testing the hypothesis that gender disparity is greater among leaders than frontline hospitalists was not statistically significant ($16,720, P = 0.087) and excluded from the final model.

DISCUSSION

In a national stratified sample of US hospitalists, we found gender differences in job satisfaction priorities and hospitalist work characteristics. We also confirmed the persistence of a substantial gender earnings disparity. Lower earnings among women compared to men hospitalists were present in our data after controlling for age, pediatric specialty, practice model, geography, type of clinical work, and productivity measures. The gender earnings disparity noted in 1999[6] persists, although it appears to have decreased, possibly indicating progress toward equity. We showed that women hospitalists' relative tendency not to prioritize pay explains a significant portion of the residual income gap.

Hoff examined hospitalist earnings in a large national survey of hospitalists in 1999. Our cohorts differed in age and experience (both lower in the Hoff study). An estimated $24,000 ($124,266 vs. $148,132) earnings gap between women and men was greater than our estimate of $14,581 following an interval of 10 years. Although survey items differed, both studies found that women were less interested in pay than men when considering a hospitalist job. Hoff also found that work setting and attitudes about pay and lifestyle were significantly related to earnings. We extended the previous analyses of gender differences in job satisfaction priorities, work, and demographic characteristics to explain the earnings gap and understand how it may be remedied.

When considering job satisfaction, we found that more men than women prioritized substantial pay and that prioritization of substantial pay was directly related to higher earnings. Therefore, fewer women prioritizing pay partly explains women's lower earnings. Reasons for why fewer women prioritize pay were not assessed in this study but may include factors like being part of 2‐income households and competing commitments.[29] Priorities may even be influenced by empirically observed gender differences in discussions of financial matters, governed by cultural norms. Such norms may implicitly sanction employers to offer women less pay than men for the same or similar work. Women may disadvantage themselves by negotiating less or less well than men for higher starting and promotion salaries. They may be perceived more negatively than men when they do negotiate pay, leading to unintended negative consequences such as loss of social networks, decreased likability, and even loss of job offers.[29, 30, 31, 32]

More women prioritized optimal variety of tasks (6th most prevalent among women and 10th among men). Women who highly rate optimal variety of tasks as a job satisfier may choose positions in which they teach, perform research, and participate in hospital committees and quality‐improvement work, but offer lower pay. Yet hours per month doing nonclinical work was not significantly different between men and women, nor associated with earnings differences in our earnings models. Understanding whether women self‐select into hospitalist jobs with like‐minded colleagues to achieve complementary fit or end up supplementing their skills with hospitalists with different priorities may inform strategies to reduce the gender income disparity.[5] Unlike disparities between various hospital medicine groups, systematic disparities within practices risk generating low levels of organizational fairness and burnout among employees.

Not surprisingly, productivity was positively associated with earnings but did not fully account for the gender earnings gap. Our data demonstrated that women, on average, were associated with work characteristics that expectedly generate less compensation. For example, women were younger, more often part time, academic, pediatric, less often leaders, and reported fewer billable encounters compared to men. These differences account for some of the earnings gap between men and women, but these factors were controlled for in the earnings model. In addition, our analysis may have underestimated the gap by not incorporating loss of fringe benefits from part‐time status and not comprehensively counting incentive pay associated with high productivity. Other work patterns more commonly associated with women suggest an imbalance in reimbursement. More women than men work nights that are often compensated at higher rates than daytime work, yet their average pay was less, suggesting that compensation for night work may need to be adjusted to reflect its unique burdens and responsibilities.[33]

Although the gender pay gap was not more extreme among leaders compared to frontline hospitalists in our data, the trend, nonetheless, underscores an important consideration. Whereas clinical work is paid for in mostly measurable ways, pay for leadership may be influenced by intangible factors such as reputation, negotiation, and confidence that may disadvantage women relative to men.[7, 19, 23, 34, 35, 36] Efforts to overcome implicit gender bias should be most effective when we consciously couple fair promotion of women to leadership with fair compensation commensurate with their male peers.[21]

Our data are vulnerable to nonresponse bias.[1, 4, 5] Post hoc analyses demonstrated that distributions of age, gender, practice model and region of our respondents were similar to other nationally representative cohorts of hospitalists. Consequently, we believe our data can make valid estimates about a nationally representative sample of hospitalists. However, we acknowledge several additional weaknesses of self‐reported data, including recall bias and accuracy of productivity figures, which were rounded to variable significant digits by respondents. Earnings analysis using this data was intended to be exploratory, but the findings echoed analyses using more authoritative data sources.[11] Still, we made inferences conservatively by adopting multiple imputation techniques for dealing with nonresponse surveys in adherence to established reporting guidelines.[25] We also note several limitations relevant to multiple imputations. The greater prevalence of missing data for survey items soliciting earnings and the number of billable encounters suggest they were not truly missing at random as assumed. However, we showed that missingness is unrelated to the variables under study, justifying use of the technique. The wider measures of variance derived from multiple imputations make us vulnerable to not detecting associations that may exist.

The gender earnings gap found in hospital medicine echoes the gap found in multiple medical specialties, including but not limited to pediatrics, academic medicine, gastroenterology, and plastic surgery.[7, 8, 9, 11, 12, 13, 37] Hospital medicine employment models and practice patterns have important structural differences compared to previously studied populations that could mitigate factors contributing to women physicians' lower earnings. However, despite well‐defined working hours, lack of control over the number of patient encounters per day and high prevalence of hospital‐employed practice models, the gender earnings gap persists. We showed that lower prioritization for pay may reflect the self‐selection of women into lower paying jobs. Unmeasured factors, including implicit bias and differences in negotiations, social networks and mentoring opportunities[38, 39] may also contribute to pay differences between men and women hospitalists. As hospital medicine tackles gender inequities and other disparities, strategies to assess and address fair physician compensation must be on the table.

From a new concept to 44,000 practitioners in just 18 years,[1] there is no doubt that the word hospitalist is synonymous with innovation, leadership, growth, and change. Yet 2 articles in this month's Journal of Hospital Medicine prove that even our new field faces age‐old problems. Although women comprise half of all academic hospitalist and general internal medicine faculty, Burden et al.[2] showed that female hospitalists are less likely than male hospitalists to be division or section heads of hospital medicine, speakers at national meetings, and first or last authors on both research publications and editorials. This is made more concerning given that women are more likely to choose academic hospital medicine careers,[3] as they represent one‐third of all hospitalists but half of the academic hospitalist workforce.[2, 3] Findings in general internal medicine were similar, except that equal numbers of women and men were national meeting speakers and first authors on research publications (but not editorials). Weaver et al.[4] shed even more light on this disparity, and found that female hospitalists made $14,581 less per year than their male counterparts, even after adjusting for relevant differences. Weaver and colleagues also found other gender‐specific differences: women worked more nights and had fewer billable encounters per hospitalist shift than men.

Unfortunately, these trends are not new or limited to hospital medicine. For decades, almost equal numbers of women and men have entered medical school,[5] yet women are under‐represented in high status specialties,[6] less likely to be first or senior authors on original research studies compared to men,[7] less likely to be promoted,[8] and women physicians are consistently paid less than men across specialties.[9, 10] Simple analyses have not yet explained these disparities. Compared with men, women have similar leadership aspirations[11, 12] and are at least as effective as leaders.[13, 14, 15] Yet equity has not been attained.

Implicit bias research suggests that gender stereotypes influence women at all career stages.[16, 17, 18] For example, an elegant study conducted by Correll et al. identified a motherhood penalty, where indicating membership in the elementary school parent‐teacher organization on one's curriculum vitae hurt women's chances of employment and pay, but actually helped men.[19] Gender stereotypes exist, even among those who do not support their content. The universal reinforcement of such stereotypes over time leads to implicit but prescriptive rules about how women and men should act.[20] In particular, communal behaviors, including being cooperative, kind, and understanding, are typically associated with women, and agentic behaviors, including being ambitious and acting as a leader, are considered appropriate for men.[21] This leads to the think leader, think male phenomena, where we automatically associate men with leadership and higher status tasks (like first authorship or speaker invitations).[22, 23] Furthermore, acting against the stereotype (eg, a woman showing anger[24] or negotiating for more pay[25] or a man showing sadness[26]) can negatively impact wage and employment. Expecting social censure for violating gender norms, women develop a fear of the backlash that alone may shape behavior such that women may not express interest in having a high salary or negotiate for a raise.[27, 28, 29]

The specific system and institutional barriers that prevent female hospitalists from receiving equal pay and opportunities for leadership are not known, but one can surmise they are similar to those found in other specialties.[10, 30, 31] The findings of the studies of Burden et al.[2] and Weaver et al.[4] invite investigation of new questions specific to hospital medicine. Why are women in hospital medicine working more night shifts? Does this impact leadership or scholarship opportunities? Why are women documenting less productivity? Are they spending more time with patients, as they do in other settings?[32] What influences their practice choice? We would like to believe that there is something about hospital medicine that can explain the gender differences identified in these 2 studies. However, these data should prompt a serious and thorough examination of our specialty. We must accept that despite being a new specialty and a change leader, hospital medicine may not have escaped systematic gender bias that constrains the full participation and advancement of women.

But we believe that hospitalistsinnovators and change leaders in medicinewill be spurred to action to address the possibility of gender inequities. We do not need to know all of the causes to begin to address disparities, of every type, on an individual, institutional, and national level. As individuals, we can acknowledge that there are implicit assumptions that influence our decision making. No matter how unintentional, and even conflicting with evidence, these assumptions can lead us to judge women as less capable leaders than men or to automatically envision a high salary for a woman and man as different amounts. However, these automatic gender biases function as habits of mind, so they can be broken like any other unwanted habit.[33] Institutionally, we can also hold ourselves accountable for transparency in mentorship, leadership, scholarship, promotions, and wages to ensure diverse representation. We should routinely examine our practices to ensure the equitable hiring, pay, and promotion of our workforce.[18] National organizations and their respective journals should actively pursue diverse representation in leadership and membership on boards and committees, award nominees and recipients, and opportunities for invited editorials. Hospital medicinebeing young, innovative, and committed to changeis uniquely well suited to lead the charge for workforce equity. We can, and will, show the rest of medicine how it is done.

From a new concept to 44,000 practitioners in just 18 years,[1] there is no doubt that the word hospitalist is synonymous with innovation, leadership, growth, and change. Yet 2 articles in this month's Journal of Hospital Medicine prove that even our new field faces age‐old problems. Although women comprise half of all academic hospitalist and general internal medicine faculty, Burden et al.[2] showed that female hospitalists are less likely than male hospitalists to be division or section heads of hospital medicine, speakers at national meetings, and first or last authors on both research publications and editorials. This is made more concerning given that women are more likely to choose academic hospital medicine careers,[3] as they represent one‐third of all hospitalists but half of the academic hospitalist workforce.[2, 3] Findings in general internal medicine were similar, except that equal numbers of women and men were national meeting speakers and first authors on research publications (but not editorials). Weaver et al.[4] shed even more light on this disparity, and found that female hospitalists made $14,581 less per year than their male counterparts, even after adjusting for relevant differences. Weaver and colleagues also found other gender‐specific differences: women worked more nights and had fewer billable encounters per hospitalist shift than men.

Unfortunately, these trends are not new or limited to hospital medicine. For decades, almost equal numbers of women and men have entered medical school,[5] yet women are under‐represented in high status specialties,[6] less likely to be first or senior authors on original research studies compared to men,[7] less likely to be promoted,[8] and women physicians are consistently paid less than men across specialties.[9, 10] Simple analyses have not yet explained these disparities. Compared with men, women have similar leadership aspirations[11, 12] and are at least as effective as leaders.[13, 14, 15] Yet equity has not been attained.

Implicit bias research suggests that gender stereotypes influence women at all career stages.[16, 17, 18] For example, an elegant study conducted by Correll et al. identified a motherhood penalty, where indicating membership in the elementary school parent‐teacher organization on one's curriculum vitae hurt women's chances of employment and pay, but actually helped men.[19] Gender stereotypes exist, even among those who do not support their content. The universal reinforcement of such stereotypes over time leads to implicit but prescriptive rules about how women and men should act.[20] In particular, communal behaviors, including being cooperative, kind, and understanding, are typically associated with women, and agentic behaviors, including being ambitious and acting as a leader, are considered appropriate for men.[21] This leads to the think leader, think male phenomena, where we automatically associate men with leadership and higher status tasks (like first authorship or speaker invitations).[22, 23] Furthermore, acting against the stereotype (eg, a woman showing anger[24] or negotiating for more pay[25] or a man showing sadness[26]) can negatively impact wage and employment. Expecting social censure for violating gender norms, women develop a fear of the backlash that alone may shape behavior such that women may not express interest in having a high salary or negotiate for a raise.[27, 28, 29]

The specific system and institutional barriers that prevent female hospitalists from receiving equal pay and opportunities for leadership are not known, but one can surmise they are similar to those found in other specialties.[10, 30, 31] The findings of the studies of Burden et al.[2] and Weaver et al.[4] invite investigation of new questions specific to hospital medicine. Why are women in hospital medicine working more night shifts? Does this impact leadership or scholarship opportunities? Why are women documenting less productivity? Are they spending more time with patients, as they do in other settings?[32] What influences their practice choice? We would like to believe that there is something about hospital medicine that can explain the gender differences identified in these 2 studies. However, these data should prompt a serious and thorough examination of our specialty. We must accept that despite being a new specialty and a change leader, hospital medicine may not have escaped systematic gender bias that constrains the full participation and advancement of women.

But we believe that hospitalistsinnovators and change leaders in medicinewill be spurred to action to address the possibility of gender inequities. We do not need to know all of the causes to begin to address disparities, of every type, on an individual, institutional, and national level. As individuals, we can acknowledge that there are implicit assumptions that influence our decision making. No matter how unintentional, and even conflicting with evidence, these assumptions can lead us to judge women as less capable leaders than men or to automatically envision a high salary for a woman and man as different amounts. However, these automatic gender biases function as habits of mind, so they can be broken like any other unwanted habit.[33] Institutionally, we can also hold ourselves accountable for transparency in mentorship, leadership, scholarship, promotions, and wages to ensure diverse representation. We should routinely examine our practices to ensure the equitable hiring, pay, and promotion of our workforce.[18] National organizations and their respective journals should actively pursue diverse representation in leadership and membership on boards and committees, award nominees and recipients, and opportunities for invited editorials. Hospital medicinebeing young, innovative, and committed to changeis uniquely well suited to lead the charge for workforce equity. We can, and will, show the rest of medicine how it is done.

From a new concept to 44,000 practitioners in just 18 years,[1] there is no doubt that the word hospitalist is synonymous with innovation, leadership, growth, and change. Yet 2 articles in this month's Journal of Hospital Medicine prove that even our new field faces age‐old problems. Although women comprise half of all academic hospitalist and general internal medicine faculty, Burden et al.[2] showed that female hospitalists are less likely than male hospitalists to be division or section heads of hospital medicine, speakers at national meetings, and first or last authors on both research publications and editorials. This is made more concerning given that women are more likely to choose academic hospital medicine careers,[3] as they represent one‐third of all hospitalists but half of the academic hospitalist workforce.[2, 3] Findings in general internal medicine were similar, except that equal numbers of women and men were national meeting speakers and first authors on research publications (but not editorials). Weaver et al.[4] shed even more light on this disparity, and found that female hospitalists made $14,581 less per year than their male counterparts, even after adjusting for relevant differences. Weaver and colleagues also found other gender‐specific differences: women worked more nights and had fewer billable encounters per hospitalist shift than men.

Unfortunately, these trends are not new or limited to hospital medicine. For decades, almost equal numbers of women and men have entered medical school,[5] yet women are under‐represented in high status specialties,[6] less likely to be first or senior authors on original research studies compared to men,[7] less likely to be promoted,[8] and women physicians are consistently paid less than men across specialties.[9, 10] Simple analyses have not yet explained these disparities. Compared with men, women have similar leadership aspirations[11, 12] and are at least as effective as leaders.[13, 14, 15] Yet equity has not been attained.

Implicit bias research suggests that gender stereotypes influence women at all career stages.[16, 17, 18] For example, an elegant study conducted by Correll et al. identified a motherhood penalty, where indicating membership in the elementary school parent‐teacher organization on one's curriculum vitae hurt women's chances of employment and pay, but actually helped men.[19] Gender stereotypes exist, even among those who do not support their content. The universal reinforcement of such stereotypes over time leads to implicit but prescriptive rules about how women and men should act.[20] In particular, communal behaviors, including being cooperative, kind, and understanding, are typically associated with women, and agentic behaviors, including being ambitious and acting as a leader, are considered appropriate for men.[21] This leads to the think leader, think male phenomena, where we automatically associate men with leadership and higher status tasks (like first authorship or speaker invitations).[22, 23] Furthermore, acting against the stereotype (eg, a woman showing anger[24] or negotiating for more pay[25] or a man showing sadness[26]) can negatively impact wage and employment. Expecting social censure for violating gender norms, women develop a fear of the backlash that alone may shape behavior such that women may not express interest in having a high salary or negotiate for a raise.[27, 28, 29]

The specific system and institutional barriers that prevent female hospitalists from receiving equal pay and opportunities for leadership are not known, but one can surmise they are similar to those found in other specialties.[10, 30, 31] The findings of the studies of Burden et al.[2] and Weaver et al.[4] invite investigation of new questions specific to hospital medicine. Why are women in hospital medicine working more night shifts? Does this impact leadership or scholarship opportunities? Why are women documenting less productivity? Are they spending more time with patients, as they do in other settings?[32] What influences their practice choice? We would like to believe that there is something about hospital medicine that can explain the gender differences identified in these 2 studies. However, these data should prompt a serious and thorough examination of our specialty. We must accept that despite being a new specialty and a change leader, hospital medicine may not have escaped systematic gender bias that constrains the full participation and advancement of women.

But we believe that hospitalistsinnovators and change leaders in medicinewill be spurred to action to address the possibility of gender inequities. We do not need to know all of the causes to begin to address disparities, of every type, on an individual, institutional, and national level. As individuals, we can acknowledge that there are implicit assumptions that influence our decision making. No matter how unintentional, and even conflicting with evidence, these assumptions can lead us to judge women as less capable leaders than men or to automatically envision a high salary for a woman and man as different amounts. However, these automatic gender biases function as habits of mind, so they can be broken like any other unwanted habit.[33] Institutionally, we can also hold ourselves accountable for transparency in mentorship, leadership, scholarship, promotions, and wages to ensure diverse representation. We should routinely examine our practices to ensure the equitable hiring, pay, and promotion of our workforce.[18] National organizations and their respective journals should actively pursue diverse representation in leadership and membership on boards and committees, award nominees and recipients, and opportunities for invited editorials. Hospital medicinebeing young, innovative, and committed to changeis uniquely well suited to lead the charge for workforce equity. We can, and will, show the rest of medicine how it is done.