Lee A. Biblo, MD

Localizing inpatient general medical teams to nursing units has high intuitive validity for improving physician productivity, hospital efficiency, and patient outcomes. Motion or the moving of personnel between tasksso prominent if teams are not localizedis 1 of the 7 wastes in lean thinking.1 In a timemotion study, where hospitalists cared for patients on up to 5 different wards, O'Leary et al2 have reported large parts of hospitalists' workdays spent in indirect patient care (69%), paging (13%), and travel (3%). Localization could increase the amount of time available for direct patient care, decrease time spent for (and interruptions due to) paging, and decrease travel time, all leading to greater productivity.

O'Leary et al3 have also reported the beneficial effects of localization of medical inpatients on communication between nurses and physicians, who could identify each other more often, and reported greater communication (specifically face‐to‐face communication) with each other following localization. This improvement in communication and effective multidisciplinary rounds could lead to safer care4 and better outcomes.

Further investigations about the effect of localization are limited. Roy et al5 have compared the outcomes of patients localized to 2 inpatient pods medically staffed by hospitalists and physician assistants (PAs) to geographically dispersed, but structurally different, house staff teams. They noticed significantly lower costs, slight but nonsignificant increase in length of stay, and no difference in mortality or readmissions, but it is impossible to tease out the affect of localization versus the affect of team composition. In a before‐and‐after study, Findlay et al6 have reported a decrease in mortality and complication rates in clinically homogenous surgical patients (proximal hip fractures) when cared for by junior trainee physicians localized to a unit, but their experience cannot be extrapolated to the much more diverse general medical population.

In our hospital, each general medical team could admit patients dispersed over 14 different units. An internal group, commissioned to evaluate our hospitalist practice, recommended reducing this dispersal to improve physician productivity, hospital efficiency, and outcomes of care. We therefore conducted a project to evaluate the impact of localizing general medical inpatient teams to a single nursing unit.

METHODS

RESULTS

DISCUSSION

We found that general medical patients admitted to H‐PA teams and localized to a single nursing unit had similar risk of 30‐day readmission and charges, but may have had a higher length of stay compared to historical and concurrent controls. The localized teams received far fewer pages, had more patient encounters, generated more RVUs, and walked less during their work day. Taken together, these findings imply that in our study, localization led to greater team productivity and a possible decrease in hospital efficiency, with no significant impact on readmissions or charges incurred.

The higher productivity was likely mediated by the preferential assignments of more patients to the localized teams, and improvements in workflow (such as fewer pages and fewer steps walked), which allowed them to provide more care with the same resources as the control teams. Kocher and Sahni7 recently pointed out that the healthcare sector has experienced no gains in labor productivity in the past 20 years. Our intervention fits their prescription for redesigning healthcare delivery models to achieve higher productivity.

The possibility of a higher LOS associated with localization was a counterintuitive finding, and similar to that reported by Roy et al.5 We propose 3 hypotheses to explain this:

• 1

  Selection bias: Higher workload of the localized teams led to compromised efficiency and a higher length of stay (eg, localized teams had fewer observation admissions, more hospitalizations with an ICU stay, and the AMO was asked to preferentially admit patients to localized teams).

• 2

  Localization provided teams the opportunity to spend more time with their patients (by decreasing nonvalue‐added tasks) and to consequently address more issues before transitioning to outpatient care, or to provide higher quality of care.

• 3

  Gaming: By having a hard cap on total number of occupied beds, we provided a perverse incentive to the localized teams to retain patients longer to keep assigned beds occupied, thereby delaying new admissions to avoid higher workload.

Our study cannot tell us which of these hypotheses represents the dominant phenomenon that led to this surprising finding. Hypothesis 3 is most worrying, and we suggest that others looking to localize their medical teams consider the possibility of unintended perverse incentives.

Differences were more pronounced between the historical control group and the intervention group, as opposed to the intervention group and concurrent controls. This may have occurred if we contaminated the concurrent control by decreasing the number of units they had to go to, by sequestering 1 unit for the intervention team.

Our report has limitations. It is a nonrandomized, quasi‐experimental investigation using a single institution's administrative databases. Our intervention was small in scale (localizing 2 out of 10 general medical teams on 1 out of 14 nursing units). What impact a wider implementation of localization may have on emergency department throughput and hospital occupancy remains to be studied. Nevertheless, our research is the first report, to our knowledge, investigating a wide variety of outcomes of localizing inpatient medical teams, and adds significantly to the limited research on this topic. It also provides significant operational details for other institutions to use when localizing medical teams.

We conclude that our intervention of localization of medical teams to a single nursing unit led to higher productivity and better workflow, but did not impact readmissions or charges incurred. We caution others designing similar localization interventions to protect against possible perverse incentives for inefficient care.

Localizing inpatient general medical teams to nursing units has high intuitive validity for improving physician productivity, hospital efficiency, and patient outcomes. Motion or the moving of personnel between tasksso prominent if teams are not localizedis 1 of the 7 wastes in lean thinking.1 In a timemotion study, where hospitalists cared for patients on up to 5 different wards, O'Leary et al2 have reported large parts of hospitalists' workdays spent in indirect patient care (69%), paging (13%), and travel (3%). Localization could increase the amount of time available for direct patient care, decrease time spent for (and interruptions due to) paging, and decrease travel time, all leading to greater productivity.

O'Leary et al3 have also reported the beneficial effects of localization of medical inpatients on communication between nurses and physicians, who could identify each other more often, and reported greater communication (specifically face‐to‐face communication) with each other following localization. This improvement in communication and effective multidisciplinary rounds could lead to safer care4 and better outcomes.

Further investigations about the effect of localization are limited. Roy et al5 have compared the outcomes of patients localized to 2 inpatient pods medically staffed by hospitalists and physician assistants (PAs) to geographically dispersed, but structurally different, house staff teams. They noticed significantly lower costs, slight but nonsignificant increase in length of stay, and no difference in mortality or readmissions, but it is impossible to tease out the affect of localization versus the affect of team composition. In a before‐and‐after study, Findlay et al6 have reported a decrease in mortality and complication rates in clinically homogenous surgical patients (proximal hip fractures) when cared for by junior trainee physicians localized to a unit, but their experience cannot be extrapolated to the much more diverse general medical population.

In our hospital, each general medical team could admit patients dispersed over 14 different units. An internal group, commissioned to evaluate our hospitalist practice, recommended reducing this dispersal to improve physician productivity, hospital efficiency, and outcomes of care. We therefore conducted a project to evaluate the impact of localizing general medical inpatient teams to a single nursing unit.

METHODS

RESULTS

DISCUSSION

We found that general medical patients admitted to H‐PA teams and localized to a single nursing unit had similar risk of 30‐day readmission and charges, but may have had a higher length of stay compared to historical and concurrent controls. The localized teams received far fewer pages, had more patient encounters, generated more RVUs, and walked less during their work day. Taken together, these findings imply that in our study, localization led to greater team productivity and a possible decrease in hospital efficiency, with no significant impact on readmissions or charges incurred.

The higher productivity was likely mediated by the preferential assignments of more patients to the localized teams, and improvements in workflow (such as fewer pages and fewer steps walked), which allowed them to provide more care with the same resources as the control teams. Kocher and Sahni7 recently pointed out that the healthcare sector has experienced no gains in labor productivity in the past 20 years. Our intervention fits their prescription for redesigning healthcare delivery models to achieve higher productivity.

The possibility of a higher LOS associated with localization was a counterintuitive finding, and similar to that reported by Roy et al.5 We propose 3 hypotheses to explain this:

• 1

  Selection bias: Higher workload of the localized teams led to compromised efficiency and a higher length of stay (eg, localized teams had fewer observation admissions, more hospitalizations with an ICU stay, and the AMO was asked to preferentially admit patients to localized teams).

• 2

  Localization provided teams the opportunity to spend more time with their patients (by decreasing nonvalue‐added tasks) and to consequently address more issues before transitioning to outpatient care, or to provide higher quality of care.

• 3

  Gaming: By having a hard cap on total number of occupied beds, we provided a perverse incentive to the localized teams to retain patients longer to keep assigned beds occupied, thereby delaying new admissions to avoid higher workload.

Our study cannot tell us which of these hypotheses represents the dominant phenomenon that led to this surprising finding. Hypothesis 3 is most worrying, and we suggest that others looking to localize their medical teams consider the possibility of unintended perverse incentives.

Differences were more pronounced between the historical control group and the intervention group, as opposed to the intervention group and concurrent controls. This may have occurred if we contaminated the concurrent control by decreasing the number of units they had to go to, by sequestering 1 unit for the intervention team.

Our report has limitations. It is a nonrandomized, quasi‐experimental investigation using a single institution's administrative databases. Our intervention was small in scale (localizing 2 out of 10 general medical teams on 1 out of 14 nursing units). What impact a wider implementation of localization may have on emergency department throughput and hospital occupancy remains to be studied. Nevertheless, our research is the first report, to our knowledge, investigating a wide variety of outcomes of localizing inpatient medical teams, and adds significantly to the limited research on this topic. It also provides significant operational details for other institutions to use when localizing medical teams.

We conclude that our intervention of localization of medical teams to a single nursing unit led to higher productivity and better workflow, but did not impact readmissions or charges incurred. We caution others designing similar localization interventions to protect against possible perverse incentives for inefficient care.

Localizing inpatient general medical teams to nursing units has high intuitive validity for improving physician productivity, hospital efficiency, and patient outcomes. Motion or the moving of personnel between tasksso prominent if teams are not localizedis 1 of the 7 wastes in lean thinking.1 In a timemotion study, where hospitalists cared for patients on up to 5 different wards, O'Leary et al2 have reported large parts of hospitalists' workdays spent in indirect patient care (69%), paging (13%), and travel (3%). Localization could increase the amount of time available for direct patient care, decrease time spent for (and interruptions due to) paging, and decrease travel time, all leading to greater productivity.

O'Leary et al3 have also reported the beneficial effects of localization of medical inpatients on communication between nurses and physicians, who could identify each other more often, and reported greater communication (specifically face‐to‐face communication) with each other following localization. This improvement in communication and effective multidisciplinary rounds could lead to safer care4 and better outcomes.

Further investigations about the effect of localization are limited. Roy et al5 have compared the outcomes of patients localized to 2 inpatient pods medically staffed by hospitalists and physician assistants (PAs) to geographically dispersed, but structurally different, house staff teams. They noticed significantly lower costs, slight but nonsignificant increase in length of stay, and no difference in mortality or readmissions, but it is impossible to tease out the affect of localization versus the affect of team composition. In a before‐and‐after study, Findlay et al6 have reported a decrease in mortality and complication rates in clinically homogenous surgical patients (proximal hip fractures) when cared for by junior trainee physicians localized to a unit, but their experience cannot be extrapolated to the much more diverse general medical population.

In our hospital, each general medical team could admit patients dispersed over 14 different units. An internal group, commissioned to evaluate our hospitalist practice, recommended reducing this dispersal to improve physician productivity, hospital efficiency, and outcomes of care. We therefore conducted a project to evaluate the impact of localizing general medical inpatient teams to a single nursing unit.

METHODS

RESULTS

DISCUSSION

We found that general medical patients admitted to H‐PA teams and localized to a single nursing unit had similar risk of 30‐day readmission and charges, but may have had a higher length of stay compared to historical and concurrent controls. The localized teams received far fewer pages, had more patient encounters, generated more RVUs, and walked less during their work day. Taken together, these findings imply that in our study, localization led to greater team productivity and a possible decrease in hospital efficiency, with no significant impact on readmissions or charges incurred.

The higher productivity was likely mediated by the preferential assignments of more patients to the localized teams, and improvements in workflow (such as fewer pages and fewer steps walked), which allowed them to provide more care with the same resources as the control teams. Kocher and Sahni7 recently pointed out that the healthcare sector has experienced no gains in labor productivity in the past 20 years. Our intervention fits their prescription for redesigning healthcare delivery models to achieve higher productivity.

The possibility of a higher LOS associated with localization was a counterintuitive finding, and similar to that reported by Roy et al.5 We propose 3 hypotheses to explain this:

• 1

  Selection bias: Higher workload of the localized teams led to compromised efficiency and a higher length of stay (eg, localized teams had fewer observation admissions, more hospitalizations with an ICU stay, and the AMO was asked to preferentially admit patients to localized teams).

• 2

  Localization provided teams the opportunity to spend more time with their patients (by decreasing nonvalue‐added tasks) and to consequently address more issues before transitioning to outpatient care, or to provide higher quality of care.

• 3

  Gaming: By having a hard cap on total number of occupied beds, we provided a perverse incentive to the localized teams to retain patients longer to keep assigned beds occupied, thereby delaying new admissions to avoid higher workload.

Our study cannot tell us which of these hypotheses represents the dominant phenomenon that led to this surprising finding. Hypothesis 3 is most worrying, and we suggest that others looking to localize their medical teams consider the possibility of unintended perverse incentives.

Differences were more pronounced between the historical control group and the intervention group, as opposed to the intervention group and concurrent controls. This may have occurred if we contaminated the concurrent control by decreasing the number of units they had to go to, by sequestering 1 unit for the intervention team.

Our report has limitations. It is a nonrandomized, quasi‐experimental investigation using a single institution's administrative databases. Our intervention was small in scale (localizing 2 out of 10 general medical teams on 1 out of 14 nursing units). What impact a wider implementation of localization may have on emergency department throughput and hospital occupancy remains to be studied. Nevertheless, our research is the first report, to our knowledge, investigating a wide variety of outcomes of localizing inpatient medical teams, and adds significantly to the limited research on this topic. It also provides significant operational details for other institutions to use when localizing medical teams.

We conclude that our intervention of localization of medical teams to a single nursing unit led to higher productivity and better workflow, but did not impact readmissions or charges incurred. We caution others designing similar localization interventions to protect against possible perverse incentives for inefficient care.

In 2003 the Accreditation Council for Graduate Medical Education (ACGME) prescribed residency reform in the form of work hour restrictions without prescribing alternatives to resident based care.1 As a response, many academic medical centers have developed innovative models for providing inpatient care, some of which incorporate Physician Assistants (PAs).2 With further restrictions in resident work hours possible,3 teaching hospitals may increase use of these alternate models to provide inpatient care. Widespread implementation of such new and untested models could impact the care of the approximately 20 million hospitalizations that occur every year in US teaching hospitals.4

Few reports have compared the care delivered by these alternate models with the care provided by traditional resident‐based models of care.58 Roy et al.8 have provided the only recent comparison of a PA‐based model of care with a resident‐based model. They showed lower adjusted costs of inpatient care associated with PA based care but other outcomes were similar to resident‐based teams.

The objective of this study is to provide a valid and usable comparison of the outcomes of a hospitalist‐PA (H‐PA) model of inpatient care with the traditional resident‐based model. This will add to the quantity and quality of the limited research on PA‐based inpatient care, and informs the anticipated increase in the involvement of PAs in this arena.

Methods

Results

Study Population

Of the 52,391 hospitalizations to our hospital during the study period, 13,058 were admitted to general medicine. We excluded 3102 weekend admissions and 209 who met other exclusion criteria. We could not determine the team assignment for 66. Of the remaining 9681 hospitalizations, we assigned 2171 to H‐PA teams and 7510 to RES teams (Figure 1).

Figure 1

Interactions

On adding interaction terms between the team assignment and the fixed effect variables in each model we detected that the effect of H‐PA care on LOS (P < 0.001) and charges (P < 0.001) varied by time of admission (Figure 2a and b). Hospitalizations to H‐PA teams from 6.00 _PM to 6.00 _AM had greater relative increases in LOS as compared to hospitalizations to RES teams during those times. Similarly, hospitalizations during the period 3.00 _PM to 3.00 _AM had relatively higher charges associated with H‐PA care compared to RES care.

Figure 2

Discussion

We found that hospitalizations to our H‐PA teams had longer LOS but similar charges, readmission rates, and mortality as compared to traditional resident‐based teams. These findings were robust to multiple sensitivity and subgroup analyses but when we examined times when both types of teams could receive admissions, the difference in LOS was markedly attenuated and nonsignificant.

We note that most prior reports comparing PA‐based models of inpatient care predate the ACGME work hour regulations. In a randomized control trial (1987‐1988) Simmer et al.5 showed lower lengths of stay and charges but possibly higher risk of readmission for PA based teams as compared to resident based teams. Van Rhee et al.7 conducted a nonrandomized retrospective cohort study (1994‐1995) using administrative data which showed lower resource utilization for PA‐based inpatient care. Our results from 2005 to 2006 reflect the important changes in the organization and delivery of inpatient care since these previous investigations.

Roy et al.8 report the only previously published comparison of PA and resident based GM inpatient care after the ACGME mandated work hour regulations. They found PA‐based care was associated with lower costs, whereas we found similar charges for admissions to RES and H‐PA teams. They also found that LOS was similar for PA and resident‐based care, while we found a higher LOS for admissions to our H‐PA team. We note that although the design of Roy's study was similar to our own, patients cared for by PA‐based teams were geographically localized in their model. This may contribute to the differences in results noted between our studies.

Despite no designed differences in patients assigned to either type of team other than time of admission we noted some differences between the H‐PA and RES teams in the descriptive analysis. These differences, such as a higher proportion of hospitalizations to H‐PA teams being admitted from the ER, residing on nonmedicine wards or having an ICU stay are likely a result of our system of assigning admissions to H‐PA teams early during the workday. For example patients on H‐PA teams were more often located on nonmedicine wards as a result of later discharges and bed availability on medicine wards. The difference that deserves special comment is the much higher proportion (13.8% vs. 6.7%) of hospitalizations with an ICU stay on the H‐PA teams. Hospitalizations directly to the ICU were excluded from our study which means that the hospitalizations with an ICU stay in our study were initially admitted to either H‐PA or RES teams and then transferred to the ICU. Transfers out of the ICU usually occur early in the workday when H‐PA teams accepted patients per our admission schedule. These patients may have been preferentially assigned to H‐PA teams, if on returning from the ICU the original team's resident had changed (and the bounce back rule was not in effect). Importantly, the conclusions of our research are not altered on controlling for this difference in the teams by excluding hospitalizations with an ICU stay.

Hospitalizations to H‐PA teams were associated with higher resource utilization if they occurred later in the day or overnight (Figure 2a and b). During these times a transition of care occurred shortly after admission. For a late day admission the H‐PA teams would transfer care for overnight cross cover soon after the admission and for patients admitted overnight as overflow they would assume care of a patient from the nighttime covering physician performing the admission. On the other hand, on RES teams, interns admitting patients overnight continued to care for their patients for part of the following day (30‐hour call). Similar findings of higher resource utilization associated with transfer of care after admission in the daytime11 and nighttime12 have been previously reported. An alternative hypothesis for our findings is that the hospital maybe busier and thus less efficient during times when H‐PA teams had to admit later in the day or accept patients admitted overnight as overflow. Future research to determine the cause of this significant interaction between team assignment and time of admission on resource utilization is important as the large increases in LOS (up to 30%) and charges (up to 50%) noted, could have a potentially large impact if a higher proportion of hospitalizations were affected by this phenomenon.

Our H‐PA teams were assigned equally complex patients as our RES teams, in contrast to previous reports.8, 13 This was accomplished while improving the resident's educational experience and we have previously reported increases in our resident's board pass rates and in‐service training exam scores with that introduction of our H‐PA teams.14 We thus believe that selection of less complex patients to H‐PA teams such as ours is unnecessary and may give them a second tier status in academic settings.

Our report has limitations. It is a retrospective, nonrandomized investigation using a single institution's administrative database and has the limitations of not being able to account for unmeasured confounders, severity of illness, errors in the database, selection bias and has limited generalizability. We measured charges not actual costs,15 but we feel charges are a true reflection of relative resource use when compared between similar patients within a single institution. We also did not account for the readmissions that occur to other hospitals16 and our results do not reflect resource utilization for the healthcare system in total. For example, we could not tell if higher LOS on H‐PA teams resulted in lower readmissions for their patients in all hospitals in the region, which may reveal an overall resource savings. Additionally, we measured in‐hospital mortality and could not capture deaths related to hospital care that may occur shortly after discharge.

ACGME has proposed revised standards that may further restrict resident duty hours when they take effect in July 2011.3 This may lead to further decreases in resident‐based inpatient care. Teaching hospitals will need to continue to develop alternate models for inpatient care that do not depend on house staff. Our findings provide important evidence to inform the development of such models. Our study shows that one such model: PAs paired with hospitalists, accepting admissions early in the workday, with hospitalist coverage over the weekend and nights can care for GM inpatients as complex as those cared for by resident‐based teams without increasing readmission rates, inpatient mortality, or charges but at the cost of slightly higher LOS.

In 2003 the Accreditation Council for Graduate Medical Education (ACGME) prescribed residency reform in the form of work hour restrictions without prescribing alternatives to resident based care.1 As a response, many academic medical centers have developed innovative models for providing inpatient care, some of which incorporate Physician Assistants (PAs).2 With further restrictions in resident work hours possible,3 teaching hospitals may increase use of these alternate models to provide inpatient care. Widespread implementation of such new and untested models could impact the care of the approximately 20 million hospitalizations that occur every year in US teaching hospitals.4

Few reports have compared the care delivered by these alternate models with the care provided by traditional resident‐based models of care.58 Roy et al.8 have provided the only recent comparison of a PA‐based model of care with a resident‐based model. They showed lower adjusted costs of inpatient care associated with PA based care but other outcomes were similar to resident‐based teams.

The objective of this study is to provide a valid and usable comparison of the outcomes of a hospitalist‐PA (H‐PA) model of inpatient care with the traditional resident‐based model. This will add to the quantity and quality of the limited research on PA‐based inpatient care, and informs the anticipated increase in the involvement of PAs in this arena.

Methods

Results

Study Population

Of the 52,391 hospitalizations to our hospital during the study period, 13,058 were admitted to general medicine. We excluded 3102 weekend admissions and 209 who met other exclusion criteria. We could not determine the team assignment for 66. Of the remaining 9681 hospitalizations, we assigned 2171 to H‐PA teams and 7510 to RES teams (Figure 1).

Figure 1

Interactions

On adding interaction terms between the team assignment and the fixed effect variables in each model we detected that the effect of H‐PA care on LOS (P < 0.001) and charges (P < 0.001) varied by time of admission (Figure 2a and b). Hospitalizations to H‐PA teams from 6.00 _PM to 6.00 _AM had greater relative increases in LOS as compared to hospitalizations to RES teams during those times. Similarly, hospitalizations during the period 3.00 _PM to 3.00 _AM had relatively higher charges associated with H‐PA care compared to RES care.

Figure 2

Discussion

We found that hospitalizations to our H‐PA teams had longer LOS but similar charges, readmission rates, and mortality as compared to traditional resident‐based teams. These findings were robust to multiple sensitivity and subgroup analyses but when we examined times when both types of teams could receive admissions, the difference in LOS was markedly attenuated and nonsignificant.

We note that most prior reports comparing PA‐based models of inpatient care predate the ACGME work hour regulations. In a randomized control trial (1987‐1988) Simmer et al.5 showed lower lengths of stay and charges but possibly higher risk of readmission for PA based teams as compared to resident based teams. Van Rhee et al.7 conducted a nonrandomized retrospective cohort study (1994‐1995) using administrative data which showed lower resource utilization for PA‐based inpatient care. Our results from 2005 to 2006 reflect the important changes in the organization and delivery of inpatient care since these previous investigations.

Roy et al.8 report the only previously published comparison of PA and resident based GM inpatient care after the ACGME mandated work hour regulations. They found PA‐based care was associated with lower costs, whereas we found similar charges for admissions to RES and H‐PA teams. They also found that LOS was similar for PA and resident‐based care, while we found a higher LOS for admissions to our H‐PA team. We note that although the design of Roy's study was similar to our own, patients cared for by PA‐based teams were geographically localized in their model. This may contribute to the differences in results noted between our studies.

Despite no designed differences in patients assigned to either type of team other than time of admission we noted some differences between the H‐PA and RES teams in the descriptive analysis. These differences, such as a higher proportion of hospitalizations to H‐PA teams being admitted from the ER, residing on nonmedicine wards or having an ICU stay are likely a result of our system of assigning admissions to H‐PA teams early during the workday. For example patients on H‐PA teams were more often located on nonmedicine wards as a result of later discharges and bed availability on medicine wards. The difference that deserves special comment is the much higher proportion (13.8% vs. 6.7%) of hospitalizations with an ICU stay on the H‐PA teams. Hospitalizations directly to the ICU were excluded from our study which means that the hospitalizations with an ICU stay in our study were initially admitted to either H‐PA or RES teams and then transferred to the ICU. Transfers out of the ICU usually occur early in the workday when H‐PA teams accepted patients per our admission schedule. These patients may have been preferentially assigned to H‐PA teams, if on returning from the ICU the original team's resident had changed (and the bounce back rule was not in effect). Importantly, the conclusions of our research are not altered on controlling for this difference in the teams by excluding hospitalizations with an ICU stay.

Hospitalizations to H‐PA teams were associated with higher resource utilization if they occurred later in the day or overnight (Figure 2a and b). During these times a transition of care occurred shortly after admission. For a late day admission the H‐PA teams would transfer care for overnight cross cover soon after the admission and for patients admitted overnight as overflow they would assume care of a patient from the nighttime covering physician performing the admission. On the other hand, on RES teams, interns admitting patients overnight continued to care for their patients for part of the following day (30‐hour call). Similar findings of higher resource utilization associated with transfer of care after admission in the daytime11 and nighttime12 have been previously reported. An alternative hypothesis for our findings is that the hospital maybe busier and thus less efficient during times when H‐PA teams had to admit later in the day or accept patients admitted overnight as overflow. Future research to determine the cause of this significant interaction between team assignment and time of admission on resource utilization is important as the large increases in LOS (up to 30%) and charges (up to 50%) noted, could have a potentially large impact if a higher proportion of hospitalizations were affected by this phenomenon.

Our H‐PA teams were assigned equally complex patients as our RES teams, in contrast to previous reports.8, 13 This was accomplished while improving the resident's educational experience and we have previously reported increases in our resident's board pass rates and in‐service training exam scores with that introduction of our H‐PA teams.14 We thus believe that selection of less complex patients to H‐PA teams such as ours is unnecessary and may give them a second tier status in academic settings.

Our report has limitations. It is a retrospective, nonrandomized investigation using a single institution's administrative database and has the limitations of not being able to account for unmeasured confounders, severity of illness, errors in the database, selection bias and has limited generalizability. We measured charges not actual costs,15 but we feel charges are a true reflection of relative resource use when compared between similar patients within a single institution. We also did not account for the readmissions that occur to other hospitals16 and our results do not reflect resource utilization for the healthcare system in total. For example, we could not tell if higher LOS on H‐PA teams resulted in lower readmissions for their patients in all hospitals in the region, which may reveal an overall resource savings. Additionally, we measured in‐hospital mortality and could not capture deaths related to hospital care that may occur shortly after discharge.

ACGME has proposed revised standards that may further restrict resident duty hours when they take effect in July 2011.3 This may lead to further decreases in resident‐based inpatient care. Teaching hospitals will need to continue to develop alternate models for inpatient care that do not depend on house staff. Our findings provide important evidence to inform the development of such models. Our study shows that one such model: PAs paired with hospitalists, accepting admissions early in the workday, with hospitalist coverage over the weekend and nights can care for GM inpatients as complex as those cared for by resident‐based teams without increasing readmission rates, inpatient mortality, or charges but at the cost of slightly higher LOS.

In 2003 the Accreditation Council for Graduate Medical Education (ACGME) prescribed residency reform in the form of work hour restrictions without prescribing alternatives to resident based care.1 As a response, many academic medical centers have developed innovative models for providing inpatient care, some of which incorporate Physician Assistants (PAs).2 With further restrictions in resident work hours possible,3 teaching hospitals may increase use of these alternate models to provide inpatient care. Widespread implementation of such new and untested models could impact the care of the approximately 20 million hospitalizations that occur every year in US teaching hospitals.4

Few reports have compared the care delivered by these alternate models with the care provided by traditional resident‐based models of care.58 Roy et al.8 have provided the only recent comparison of a PA‐based model of care with a resident‐based model. They showed lower adjusted costs of inpatient care associated with PA based care but other outcomes were similar to resident‐based teams.

The objective of this study is to provide a valid and usable comparison of the outcomes of a hospitalist‐PA (H‐PA) model of inpatient care with the traditional resident‐based model. This will add to the quantity and quality of the limited research on PA‐based inpatient care, and informs the anticipated increase in the involvement of PAs in this arena.

Methods

Results

Study Population

Of the 52,391 hospitalizations to our hospital during the study period, 13,058 were admitted to general medicine. We excluded 3102 weekend admissions and 209 who met other exclusion criteria. We could not determine the team assignment for 66. Of the remaining 9681 hospitalizations, we assigned 2171 to H‐PA teams and 7510 to RES teams (Figure 1).

Figure 1

Interactions

On adding interaction terms between the team assignment and the fixed effect variables in each model we detected that the effect of H‐PA care on LOS (P < 0.001) and charges (P < 0.001) varied by time of admission (Figure 2a and b). Hospitalizations to H‐PA teams from 6.00 _PM to 6.00 _AM had greater relative increases in LOS as compared to hospitalizations to RES teams during those times. Similarly, hospitalizations during the period 3.00 _PM to 3.00 _AM had relatively higher charges associated with H‐PA care compared to RES care.

Figure 2

Discussion

We found that hospitalizations to our H‐PA teams had longer LOS but similar charges, readmission rates, and mortality as compared to traditional resident‐based teams. These findings were robust to multiple sensitivity and subgroup analyses but when we examined times when both types of teams could receive admissions, the difference in LOS was markedly attenuated and nonsignificant.

We note that most prior reports comparing PA‐based models of inpatient care predate the ACGME work hour regulations. In a randomized control trial (1987‐1988) Simmer et al.5 showed lower lengths of stay and charges but possibly higher risk of readmission for PA based teams as compared to resident based teams. Van Rhee et al.7 conducted a nonrandomized retrospective cohort study (1994‐1995) using administrative data which showed lower resource utilization for PA‐based inpatient care. Our results from 2005 to 2006 reflect the important changes in the organization and delivery of inpatient care since these previous investigations.

Roy et al.8 report the only previously published comparison of PA and resident based GM inpatient care after the ACGME mandated work hour regulations. They found PA‐based care was associated with lower costs, whereas we found similar charges for admissions to RES and H‐PA teams. They also found that LOS was similar for PA and resident‐based care, while we found a higher LOS for admissions to our H‐PA team. We note that although the design of Roy's study was similar to our own, patients cared for by PA‐based teams were geographically localized in their model. This may contribute to the differences in results noted between our studies.

Despite no designed differences in patients assigned to either type of team other than time of admission we noted some differences between the H‐PA and RES teams in the descriptive analysis. These differences, such as a higher proportion of hospitalizations to H‐PA teams being admitted from the ER, residing on nonmedicine wards or having an ICU stay are likely a result of our system of assigning admissions to H‐PA teams early during the workday. For example patients on H‐PA teams were more often located on nonmedicine wards as a result of later discharges and bed availability on medicine wards. The difference that deserves special comment is the much higher proportion (13.8% vs. 6.7%) of hospitalizations with an ICU stay on the H‐PA teams. Hospitalizations directly to the ICU were excluded from our study which means that the hospitalizations with an ICU stay in our study were initially admitted to either H‐PA or RES teams and then transferred to the ICU. Transfers out of the ICU usually occur early in the workday when H‐PA teams accepted patients per our admission schedule. These patients may have been preferentially assigned to H‐PA teams, if on returning from the ICU the original team's resident had changed (and the bounce back rule was not in effect). Importantly, the conclusions of our research are not altered on controlling for this difference in the teams by excluding hospitalizations with an ICU stay.

Hospitalizations to H‐PA teams were associated with higher resource utilization if they occurred later in the day or overnight (Figure 2a and b). During these times a transition of care occurred shortly after admission. For a late day admission the H‐PA teams would transfer care for overnight cross cover soon after the admission and for patients admitted overnight as overflow they would assume care of a patient from the nighttime covering physician performing the admission. On the other hand, on RES teams, interns admitting patients overnight continued to care for their patients for part of the following day (30‐hour call). Similar findings of higher resource utilization associated with transfer of care after admission in the daytime11 and nighttime12 have been previously reported. An alternative hypothesis for our findings is that the hospital maybe busier and thus less efficient during times when H‐PA teams had to admit later in the day or accept patients admitted overnight as overflow. Future research to determine the cause of this significant interaction between team assignment and time of admission on resource utilization is important as the large increases in LOS (up to 30%) and charges (up to 50%) noted, could have a potentially large impact if a higher proportion of hospitalizations were affected by this phenomenon.

Our H‐PA teams were assigned equally complex patients as our RES teams, in contrast to previous reports.8, 13 This was accomplished while improving the resident's educational experience and we have previously reported increases in our resident's board pass rates and in‐service training exam scores with that introduction of our H‐PA teams.14 We thus believe that selection of less complex patients to H‐PA teams such as ours is unnecessary and may give them a second tier status in academic settings.

Our report has limitations. It is a retrospective, nonrandomized investigation using a single institution's administrative database and has the limitations of not being able to account for unmeasured confounders, severity of illness, errors in the database, selection bias and has limited generalizability. We measured charges not actual costs,15 but we feel charges are a true reflection of relative resource use when compared between similar patients within a single institution. We also did not account for the readmissions that occur to other hospitals16 and our results do not reflect resource utilization for the healthcare system in total. For example, we could not tell if higher LOS on H‐PA teams resulted in lower readmissions for their patients in all hospitals in the region, which may reveal an overall resource savings. Additionally, we measured in‐hospital mortality and could not capture deaths related to hospital care that may occur shortly after discharge.

ACGME has proposed revised standards that may further restrict resident duty hours when they take effect in July 2011.3 This may lead to further decreases in resident‐based inpatient care. Teaching hospitals will need to continue to develop alternate models for inpatient care that do not depend on house staff. Our findings provide important evidence to inform the development of such models. Our study shows that one such model: PAs paired with hospitalists, accepting admissions early in the workday, with hospitalist coverage over the weekend and nights can care for GM inpatients as complex as those cared for by resident‐based teams without increasing readmission rates, inpatient mortality, or charges but at the cost of slightly higher LOS.