Staphylococcus aureus is one the most common pathogens isolated in nosocomial and community‐onset bloodstream infections (BSI) in the United States.[1, 2] S aureus bacteremia (SAB) has been reported in the literature to have substantial morbidity and mortality, with rates ranging between 15% and 60% worldwide.[3, 4, 5, 6] In the United States, patients with infections due to S aureus have on average 3 times the length of hospital stay than inpatients without these infections (14.3 days vs 4.5 days; P<0.01).[7] Healthcare costs are negatively impacted by these infections. In a recent meta‐analysis, Zimlichman et al.[8] reported that central‐line BSI (CLABSI) and surgical‐site infection (SSI) caused by methicillin‐resistant S aureus (MRSA) resulted in the highest estimated costs associated with hospital‐acquired infections in the United States ($58,614 [95% CI: $16,760‐$174,755] for CLABSI and $42,300 [95% CI: $4,005‐$82,670] for SSIs).

Appropriate management of SAB includes not only selecting the correct antimicrobial based on susceptibilities but also timely control of the source of infection, appropriate use of ancillary studies when indicated, and pharmacokinetic and pharmacodynamic therapeutic monitoring of antimicrobial therapy when vancomycin is used.[9] Consultation with an infectious diseases (ID) specialist has been associated with increased compliance with evidence‐based strategies in the management of SAB,[10, 11, 12, 13, 14] such as appropriate antibiotic choice, optimized duration of treatment, removal of the source of infection, and better use of cardiac echocardiography, resulting in improved outcomes.[13, 14]

Some, but not all, institutions have adopted bundles,[14] mandatory ID consultation[10] or daily prospective audit and feedback review[15] as part of antimicrobial stewardship program (ASP) interventions aiming to optimize the management of SABs. As part of our ASP quality improvement activities we performed the present study to determine our institutional rate of clinical failure in the treatment of SAB, to identify current practice patterns in the delivery of processes of care, and evaluate their association with clinical outcomes of hospitalized patients with SAB to identify future areas of improvement.

METHODS

A retrospective cohort study was performed at a 1558 licensed‐bed tertiary teaching hospital in Miami, Florida. All hospitalized patients 18 years of age or older with at least 1 positive blood culture with MRSA or methicillin‐susceptible S aureus (MSSA) between January 1, 2012 and April 30, 2013 were included. Patients were identified from the electronic microbiology laboratory database. For the purposes of this study, only the first episode of SAB was included in the analysis. Patients were excluded if aged younger than 18 years or if SAB was detected in an outpatient setting. The primary outcome was clinical failure, defined as a composite endpoint of in‐hospital mortality or persistent bacteremia; persistent bacteremia was defined as bacteremia for 7 or more days after the first positive blood culture. S aureus isolates were identified by standard methods.[16] Species identification was performed by latex agglutination. Antimicrobial susceptibility testing was performed using an automated system (Vitek 2; bioMerieux, Durham, NC) according to standard guidelines.

Data collected included baseline demographics, comorbidities, and treating healthcare provider's service; provider's service was categorized into 1 of 5 groups: internal medicine (academic), internal medicine (hospitalist), surgery, trauma, or neurosurgery. Duration of bacteremia was recorded and defined as the time between first positive and first negative blood culture. The time of first positive culture was defined as the date in which the culture was obtained. Patients who failed to have at least 1 follow‐up blood culture were not counted toward the main outcome. Additionally, presence of a foreign body (cardiac device, orthopedic prosthesis, tunneled catheter, nontunneled catheter) and presumed source of infection as documented in the electronic medical record by the treating service was also collected. Infections were considered community associated when onset of bacteremia occurred within the first 72 hours of admission, and hospital associated if onset of bacteremia occurred after 72 hours of admission.

Based on current practice guidelines,[9] the variables considered processes of care were the time to obtain the first follow‐up blood culture, time from first positive blood culture to initiation of appropriate antibiotic therapy (defined as a loading dose of vancomycin of 15 mg/kg, or a ‐lactam if the organism was susceptible), time to obtain the first vancomycin trough (when indicated), time from first positive blood culture to consultation with ID specialist, appropriate antibiotic de‐escalation (vancomycin to ‐lactam antibiotic if the organism was susceptible and the patient had no allergies or contraindications), and obtaining an echocardiographic study (transthoracic echocardiogram or transesophageal echocardiogram).

Statistical analyses were performed using SAS 9.2 (SAS Institute, Cary, NC). Differences in proportions were analyzed with ² or Fisher exact test, accordingly. Differences in means among continuous variables were evaluated using independent samples of paired samples t tests as appropriate for the analysis. Continuous variables were dichotomized using a clinically established cutoff to determine relative risk (RR). A univariate analysis of risk factors associated with clinical failure was performed. Multivariable analyses were performed using logistic regression. Models were created using the backward stepwise approach and included all variables found to be statistically significant at less than 0.05 level in the univariate model and those of clinical significance. The study was reviewed and approved by the institutional review boards at the University of Miami and Jackson Memorial Hospital.

RESULTS

During the study period, 241 patients with a first episode of SAB were identified. MRSA and MSSA were isolated in 124 (51.4%) and 117 (48.5%) patients, respectively. Demographic and clinical characteristics of the study population based on isolate are summarized in Table 1. One hundred seventy‐nine (74.3%) patients were under the care of internal medicine services. There was no association between treating service (medical vs surgical) and clinical failure.

The onset of infection occurred in the community in 77 (62.1%) patients with MRSA and in 77 (65.8%) patients with MSSA. The documented source of bacteremia was unknown in 30% of patients with MRSA and 44% of those with MSSA BSI. When ID specialists were consulted, patients were more likely to have a source of infection identified (RR: 1.5; 95% confidence interval [CI]: 1.2‐1.8; P<0.0001). The most commonly documented sources of infection were CLABSI, which occurred in 32 (25.8%) patients with MRSA and 21 (17.9%) patients with MSSA, followed by skin and soft tissue infections in 24 (19.3%) patients with MRSA BSI and 20 (17.1%) patients with MSSA BSI. All patients with CLABSI had documentation of catheter removal.

Clinical failure (defined as in‐hospital mortality or persistent bacteremia) occurred in 78 (32.4%) patients. Of these, 50 (20.7%) represented in‐hospital mortality, and 31 (12.9%) had persistent bacteremia. Table 2 summarizes the demographic and clinical characteristics associated with clinical failure. In the univariate analysis, the variables statistically significantly associated with clinical failure were: age greater than 60 years (RR: 1.4; 95% CI: 1.1‐1.8; P=0.001), bacteremia due to MRSA (RR: 1.7; 95% CI: 1.1‐2.5; P=0.008), white race (RR: 0.7; 95% CI: 0.6‐1; P=0.03), acute kidney injury during admission (RR: 2.2; 95% CI: 1.3‐3.7; P=0.004), presence of nontunneled central venous catheters at the onset of bacteremia (RR: 1.9; 95% CI: 1.3‐2.7; P=0.004), and endocarditis (RR: 2.9; 95% CI: 2.1‐3.9; P<0.0001). In the multivariable analysis, age greater than 60 years and endocarditis were found to be independent risk factors for the development of clinical failure.

DISCUSSION

Our study showed a significant rate of morbidity associated with S aureus bacteremia and identified processes of care in the management of SAB that impact patient outcomes.

Our results show that early consultation with an ID specialist was associated with a decreased risk of developing clinical failure, increased likelihood of identification of a source of infection, and positively impacted administration of appropriate antibiotic therapy, especially in cases of MSSA BSI, with overall improvement in patient outcomes. However, consultation with an ID specialist was only obtained in 40.2% of our cases, which is consistent with published data.[10, 11, 12, 13] Consultation with an ID specialist itself did not impact clinical failure, but rather timeliness in obtaining expert guidance was associated with better outcomes. As shown in previous studies,[10, 11, 12, 13, 14] compliance with the standards of care and patient prognosis are improved when ID specialists are involved in the management of SAB. Our study reiterates that early consultation with an ID specialist has a positive outcome in patient care, as opposed to delaying consultation once the patient has persistent bacteremia for more than 7 days. This association could be explained by considering that the majority of the standards of care are time sensitive, which include: obtaining surveillance blood cultures 48 to 96 hours after initial detection[10] or initiating therapy,[11, 14] removal of foci of infection,[10, 11, 12, 14] use of parenteral ‐lactams for the treatment of MSSA,[10, 11, 13, 14] performing echocardiography when clinically indicated,[10, 11, 13, 14] and appropriate duration of therapy.[10, 13, 14] Importantly, studies have shown that when ID specialists' recommendations are followed, patients are more likely to be cured,[10, 11, 13] and are less likely to relapse.[10, 11, 12] Given the complexities of treating patients with SAB and high rates of clinical failures, routine guidance could be beneficial to healthcare providers as part of a multidisciplinary structured strategy that is set in motion the moment a patient with SAB is identified by the microbiology laboratory. The processes of care outlined in this this study can serve as quality of care indicators and be integrated into a structured strategy to optimize the management of SAB.

Regarding optimal timing for follow‐up blood cultures, our results show that delays in obtaining follow‐up blood cultures (more than 4 days from onset of bacteremia) was independently associated with increased risk of clinical failure. Timely follow‐up blood cultures have been previously identified as quality of care indicators.[10, 11, 13, 14] Compliance with obtaining follow‐up blood cultures improves when this step is integrated into a bundle of care.[14]

Antimicrobial therapy was promptly initiated in the majority of the patients in our study. However, areas for improvement were identified. Vancomycin was the empirical therapy of choice in most of the cases, but an appropriate dose was only received by 65% of the patients, and vancomycin levels after the fourth dose were obtained in 85.9% of instances when indicated. Although in our cohort these results were not significantly associated with clinical failure, previous studies have described attainment of a target therapeutic vancomycin trough (1520 mg/dL) as a factor for treatment success.[17, 18] This problem could be addressed through physician education on therapeutic drug monitoring,[19] as well as through an ASP intervention, which have successfully led efforts to improve vancomycin utilization and dosing.[20] Among patients with MSSA BSI, therapy with ‐lactams was associated with improved outcomes, and was more likely to be administered when an ID specialist was consulted. This is in accordance with previous studies that have shown that higher rates of appropriate antimicrobial therapy are achieved when ID specialists are involved in management of SAB.[10, 11, 13, 14] The use of ‐lactams for treatment of MSSA BSI has been consistently associated with lower SAB‐related mortality and relapse.[21, 22, 23, 24, 25, 26]

Echocardiographic studies were obtained in only half of the patients in our cohort, and they were twice more likely to be obtained when an ID specialist was consulted. Although we did not evaluate the appropriateness of the echocardiographic study, the increased proportion of studies performed when ID specialists were consulted could indicate a more in‐depth evaluation of the case. Moreover, in our cohort, when ID specialists where involved in direct patient care, a source of infection was more likely to be identified. This is in accordance with previous studies proposing that because evaluation by ID specialists are more detailed, they lead to increased use in ancillary studies and recognition of complicated cases.[10, 12]

Limitations of this study include its retrospective design and the fact that it was performed in a single institution. The source of infection was defined as documented by treating providers and not by independent diagnostic criteria. Antibiotic use was collected throughout duration of admission, and was not followed after patients were discharged, as these data were not available on the electronic medical record for all patients. Deaths that may have occurred after hospital discharge were not included. We did not account for elevated vancomycin minimum inhibitory concentration as a risk factor for the main outcome, and adjustment of vancomycin based on serum levels was not factored in. Acute kidney injury was accounted for anytime during hospitalization, but not in relation to antimicrobial administration. Despite the limitations, our study has strengths that make our results generalizable. Although our institution is a single medical center, it serves a large and diverse population as reflected in our cases. Even though this is a retrospective cohort study, the use of a centralized electronic medical record allowed us to identify each aspect of the management of SAB, as implemented by different treating services (medical and surgical), as continuous variables (days) rather than only in a dichotomous fashion. Moreover, by being a community teaching hospital, we were able to explore aspects of the practice of physicians in training versus practicing clinicians. These results could be extrapolated to other healthcare facilities aiming to improve the management of SAB.

CONCLUSIONS

Our results suggest that obtaining timely follow‐up blood cultures, use of ‐lactams in patients with MSSA BSI, and early consultation with infectious diseases are the processes of care that could serve as quality and patient‐safety indicators for the management of SAB. These results contribute to a growing body of evidence supporting the implementation of structured processes of care to optimize the management and clinical outcomes of hospitalized patients with SAB.

Disclosure: Nothing to report.

Staphylococcus aureus is one the most common pathogens isolated in nosocomial and community‐onset bloodstream infections (BSI) in the United States.[1, 2] S aureus bacteremia (SAB) has been reported in the literature to have substantial morbidity and mortality, with rates ranging between 15% and 60% worldwide.[3, 4, 5, 6] In the United States, patients with infections due to S aureus have on average 3 times the length of hospital stay than inpatients without these infections (14.3 days vs 4.5 days; P<0.01).[7] Healthcare costs are negatively impacted by these infections. In a recent meta‐analysis, Zimlichman et al.[8] reported that central‐line BSI (CLABSI) and surgical‐site infection (SSI) caused by methicillin‐resistant S aureus (MRSA) resulted in the highest estimated costs associated with hospital‐acquired infections in the United States ($58,614 [95% CI: $16,760‐$174,755] for CLABSI and $42,300 [95% CI: $4,005‐$82,670] for SSIs).

Appropriate management of SAB includes not only selecting the correct antimicrobial based on susceptibilities but also timely control of the source of infection, appropriate use of ancillary studies when indicated, and pharmacokinetic and pharmacodynamic therapeutic monitoring of antimicrobial therapy when vancomycin is used.[9] Consultation with an infectious diseases (ID) specialist has been associated with increased compliance with evidence‐based strategies in the management of SAB,[10, 11, 12, 13, 14] such as appropriate antibiotic choice, optimized duration of treatment, removal of the source of infection, and better use of cardiac echocardiography, resulting in improved outcomes.[13, 14]

Some, but not all, institutions have adopted bundles,[14] mandatory ID consultation[10] or daily prospective audit and feedback review[15] as part of antimicrobial stewardship program (ASP) interventions aiming to optimize the management of SABs. As part of our ASP quality improvement activities we performed the present study to determine our institutional rate of clinical failure in the treatment of SAB, to identify current practice patterns in the delivery of processes of care, and evaluate their association with clinical outcomes of hospitalized patients with SAB to identify future areas of improvement.

METHODS

A retrospective cohort study was performed at a 1558 licensed‐bed tertiary teaching hospital in Miami, Florida. All hospitalized patients 18 years of age or older with at least 1 positive blood culture with MRSA or methicillin‐susceptible S aureus (MSSA) between January 1, 2012 and April 30, 2013 were included. Patients were identified from the electronic microbiology laboratory database. For the purposes of this study, only the first episode of SAB was included in the analysis. Patients were excluded if aged younger than 18 years or if SAB was detected in an outpatient setting. The primary outcome was clinical failure, defined as a composite endpoint of in‐hospital mortality or persistent bacteremia; persistent bacteremia was defined as bacteremia for 7 or more days after the first positive blood culture. S aureus isolates were identified by standard methods.[16] Species identification was performed by latex agglutination. Antimicrobial susceptibility testing was performed using an automated system (Vitek 2; bioMerieux, Durham, NC) according to standard guidelines.

Data collected included baseline demographics, comorbidities, and treating healthcare provider's service; provider's service was categorized into 1 of 5 groups: internal medicine (academic), internal medicine (hospitalist), surgery, trauma, or neurosurgery. Duration of bacteremia was recorded and defined as the time between first positive and first negative blood culture. The time of first positive culture was defined as the date in which the culture was obtained. Patients who failed to have at least 1 follow‐up blood culture were not counted toward the main outcome. Additionally, presence of a foreign body (cardiac device, orthopedic prosthesis, tunneled catheter, nontunneled catheter) and presumed source of infection as documented in the electronic medical record by the treating service was also collected. Infections were considered community associated when onset of bacteremia occurred within the first 72 hours of admission, and hospital associated if onset of bacteremia occurred after 72 hours of admission.

Based on current practice guidelines,[9] the variables considered processes of care were the time to obtain the first follow‐up blood culture, time from first positive blood culture to initiation of appropriate antibiotic therapy (defined as a loading dose of vancomycin of 15 mg/kg, or a ‐lactam if the organism was susceptible), time to obtain the first vancomycin trough (when indicated), time from first positive blood culture to consultation with ID specialist, appropriate antibiotic de‐escalation (vancomycin to ‐lactam antibiotic if the organism was susceptible and the patient had no allergies or contraindications), and obtaining an echocardiographic study (transthoracic echocardiogram or transesophageal echocardiogram).

Statistical analyses were performed using SAS 9.2 (SAS Institute, Cary, NC). Differences in proportions were analyzed with ² or Fisher exact test, accordingly. Differences in means among continuous variables were evaluated using independent samples of paired samples t tests as appropriate for the analysis. Continuous variables were dichotomized using a clinically established cutoff to determine relative risk (RR). A univariate analysis of risk factors associated with clinical failure was performed. Multivariable analyses were performed using logistic regression. Models were created using the backward stepwise approach and included all variables found to be statistically significant at less than 0.05 level in the univariate model and those of clinical significance. The study was reviewed and approved by the institutional review boards at the University of Miami and Jackson Memorial Hospital.

RESULTS

During the study period, 241 patients with a first episode of SAB were identified. MRSA and MSSA were isolated in 124 (51.4%) and 117 (48.5%) patients, respectively. Demographic and clinical characteristics of the study population based on isolate are summarized in Table 1. One hundred seventy‐nine (74.3%) patients were under the care of internal medicine services. There was no association between treating service (medical vs surgical) and clinical failure.

The onset of infection occurred in the community in 77 (62.1%) patients with MRSA and in 77 (65.8%) patients with MSSA. The documented source of bacteremia was unknown in 30% of patients with MRSA and 44% of those with MSSA BSI. When ID specialists were consulted, patients were more likely to have a source of infection identified (RR: 1.5; 95% confidence interval [CI]: 1.2‐1.8; P<0.0001). The most commonly documented sources of infection were CLABSI, which occurred in 32 (25.8%) patients with MRSA and 21 (17.9%) patients with MSSA, followed by skin and soft tissue infections in 24 (19.3%) patients with MRSA BSI and 20 (17.1%) patients with MSSA BSI. All patients with CLABSI had documentation of catheter removal.

Clinical failure (defined as in‐hospital mortality or persistent bacteremia) occurred in 78 (32.4%) patients. Of these, 50 (20.7%) represented in‐hospital mortality, and 31 (12.9%) had persistent bacteremia. Table 2 summarizes the demographic and clinical characteristics associated with clinical failure. In the univariate analysis, the variables statistically significantly associated with clinical failure were: age greater than 60 years (RR: 1.4; 95% CI: 1.1‐1.8; P=0.001), bacteremia due to MRSA (RR: 1.7; 95% CI: 1.1‐2.5; P=0.008), white race (RR: 0.7; 95% CI: 0.6‐1; P=0.03), acute kidney injury during admission (RR: 2.2; 95% CI: 1.3‐3.7; P=0.004), presence of nontunneled central venous catheters at the onset of bacteremia (RR: 1.9; 95% CI: 1.3‐2.7; P=0.004), and endocarditis (RR: 2.9; 95% CI: 2.1‐3.9; P<0.0001). In the multivariable analysis, age greater than 60 years and endocarditis were found to be independent risk factors for the development of clinical failure.

DISCUSSION

Our study showed a significant rate of morbidity associated with S aureus bacteremia and identified processes of care in the management of SAB that impact patient outcomes.

Our results show that early consultation with an ID specialist was associated with a decreased risk of developing clinical failure, increased likelihood of identification of a source of infection, and positively impacted administration of appropriate antibiotic therapy, especially in cases of MSSA BSI, with overall improvement in patient outcomes. However, consultation with an ID specialist was only obtained in 40.2% of our cases, which is consistent with published data.[10, 11, 12, 13] Consultation with an ID specialist itself did not impact clinical failure, but rather timeliness in obtaining expert guidance was associated with better outcomes. As shown in previous studies,[10, 11, 12, 13, 14] compliance with the standards of care and patient prognosis are improved when ID specialists are involved in the management of SAB. Our study reiterates that early consultation with an ID specialist has a positive outcome in patient care, as opposed to delaying consultation once the patient has persistent bacteremia for more than 7 days. This association could be explained by considering that the majority of the standards of care are time sensitive, which include: obtaining surveillance blood cultures 48 to 96 hours after initial detection[10] or initiating therapy,[11, 14] removal of foci of infection,[10, 11, 12, 14] use of parenteral ‐lactams for the treatment of MSSA,[10, 11, 13, 14] performing echocardiography when clinically indicated,[10, 11, 13, 14] and appropriate duration of therapy.[10, 13, 14] Importantly, studies have shown that when ID specialists' recommendations are followed, patients are more likely to be cured,[10, 11, 13] and are less likely to relapse.[10, 11, 12] Given the complexities of treating patients with SAB and high rates of clinical failures, routine guidance could be beneficial to healthcare providers as part of a multidisciplinary structured strategy that is set in motion the moment a patient with SAB is identified by the microbiology laboratory. The processes of care outlined in this this study can serve as quality of care indicators and be integrated into a structured strategy to optimize the management of SAB.

Regarding optimal timing for follow‐up blood cultures, our results show that delays in obtaining follow‐up blood cultures (more than 4 days from onset of bacteremia) was independently associated with increased risk of clinical failure. Timely follow‐up blood cultures have been previously identified as quality of care indicators.[10, 11, 13, 14] Compliance with obtaining follow‐up blood cultures improves when this step is integrated into a bundle of care.[14]

Antimicrobial therapy was promptly initiated in the majority of the patients in our study. However, areas for improvement were identified. Vancomycin was the empirical therapy of choice in most of the cases, but an appropriate dose was only received by 65% of the patients, and vancomycin levels after the fourth dose were obtained in 85.9% of instances when indicated. Although in our cohort these results were not significantly associated with clinical failure, previous studies have described attainment of a target therapeutic vancomycin trough (1520 mg/dL) as a factor for treatment success.[17, 18] This problem could be addressed through physician education on therapeutic drug monitoring,[19] as well as through an ASP intervention, which have successfully led efforts to improve vancomycin utilization and dosing.[20] Among patients with MSSA BSI, therapy with ‐lactams was associated with improved outcomes, and was more likely to be administered when an ID specialist was consulted. This is in accordance with previous studies that have shown that higher rates of appropriate antimicrobial therapy are achieved when ID specialists are involved in management of SAB.[10, 11, 13, 14] The use of ‐lactams for treatment of MSSA BSI has been consistently associated with lower SAB‐related mortality and relapse.[21, 22, 23, 24, 25, 26]

Echocardiographic studies were obtained in only half of the patients in our cohort, and they were twice more likely to be obtained when an ID specialist was consulted. Although we did not evaluate the appropriateness of the echocardiographic study, the increased proportion of studies performed when ID specialists were consulted could indicate a more in‐depth evaluation of the case. Moreover, in our cohort, when ID specialists where involved in direct patient care, a source of infection was more likely to be identified. This is in accordance with previous studies proposing that because evaluation by ID specialists are more detailed, they lead to increased use in ancillary studies and recognition of complicated cases.[10, 12]

Limitations of this study include its retrospective design and the fact that it was performed in a single institution. The source of infection was defined as documented by treating providers and not by independent diagnostic criteria. Antibiotic use was collected throughout duration of admission, and was not followed after patients were discharged, as these data were not available on the electronic medical record for all patients. Deaths that may have occurred after hospital discharge were not included. We did not account for elevated vancomycin minimum inhibitory concentration as a risk factor for the main outcome, and adjustment of vancomycin based on serum levels was not factored in. Acute kidney injury was accounted for anytime during hospitalization, but not in relation to antimicrobial administration. Despite the limitations, our study has strengths that make our results generalizable. Although our institution is a single medical center, it serves a large and diverse population as reflected in our cases. Even though this is a retrospective cohort study, the use of a centralized electronic medical record allowed us to identify each aspect of the management of SAB, as implemented by different treating services (medical and surgical), as continuous variables (days) rather than only in a dichotomous fashion. Moreover, by being a community teaching hospital, we were able to explore aspects of the practice of physicians in training versus practicing clinicians. These results could be extrapolated to other healthcare facilities aiming to improve the management of SAB.

CONCLUSIONS

Our results suggest that obtaining timely follow‐up blood cultures, use of ‐lactams in patients with MSSA BSI, and early consultation with infectious diseases are the processes of care that could serve as quality and patient‐safety indicators for the management of SAB. These results contribute to a growing body of evidence supporting the implementation of structured processes of care to optimize the management and clinical outcomes of hospitalized patients with SAB.

Disclosure: Nothing to report.

Staphylococcus aureus is one the most common pathogens isolated in nosocomial and community‐onset bloodstream infections (BSI) in the United States.[1, 2] S aureus bacteremia (SAB) has been reported in the literature to have substantial morbidity and mortality, with rates ranging between 15% and 60% worldwide.[3, 4, 5, 6] In the United States, patients with infections due to S aureus have on average 3 times the length of hospital stay than inpatients without these infections (14.3 days vs 4.5 days; P<0.01).[7] Healthcare costs are negatively impacted by these infections. In a recent meta‐analysis, Zimlichman et al.[8] reported that central‐line BSI (CLABSI) and surgical‐site infection (SSI) caused by methicillin‐resistant S aureus (MRSA) resulted in the highest estimated costs associated with hospital‐acquired infections in the United States ($58,614 [95% CI: $16,760‐$174,755] for CLABSI and $42,300 [95% CI: $4,005‐$82,670] for SSIs).

Appropriate management of SAB includes not only selecting the correct antimicrobial based on susceptibilities but also timely control of the source of infection, appropriate use of ancillary studies when indicated, and pharmacokinetic and pharmacodynamic therapeutic monitoring of antimicrobial therapy when vancomycin is used.[9] Consultation with an infectious diseases (ID) specialist has been associated with increased compliance with evidence‐based strategies in the management of SAB,[10, 11, 12, 13, 14] such as appropriate antibiotic choice, optimized duration of treatment, removal of the source of infection, and better use of cardiac echocardiography, resulting in improved outcomes.[13, 14]

Some, but not all, institutions have adopted bundles,[14] mandatory ID consultation[10] or daily prospective audit and feedback review[15] as part of antimicrobial stewardship program (ASP) interventions aiming to optimize the management of SABs. As part of our ASP quality improvement activities we performed the present study to determine our institutional rate of clinical failure in the treatment of SAB, to identify current practice patterns in the delivery of processes of care, and evaluate their association with clinical outcomes of hospitalized patients with SAB to identify future areas of improvement.

METHODS

A retrospective cohort study was performed at a 1558 licensed‐bed tertiary teaching hospital in Miami, Florida. All hospitalized patients 18 years of age or older with at least 1 positive blood culture with MRSA or methicillin‐susceptible S aureus (MSSA) between January 1, 2012 and April 30, 2013 were included. Patients were identified from the electronic microbiology laboratory database. For the purposes of this study, only the first episode of SAB was included in the analysis. Patients were excluded if aged younger than 18 years or if SAB was detected in an outpatient setting. The primary outcome was clinical failure, defined as a composite endpoint of in‐hospital mortality or persistent bacteremia; persistent bacteremia was defined as bacteremia for 7 or more days after the first positive blood culture. S aureus isolates were identified by standard methods.[16] Species identification was performed by latex agglutination. Antimicrobial susceptibility testing was performed using an automated system (Vitek 2; bioMerieux, Durham, NC) according to standard guidelines.

Data collected included baseline demographics, comorbidities, and treating healthcare provider's service; provider's service was categorized into 1 of 5 groups: internal medicine (academic), internal medicine (hospitalist), surgery, trauma, or neurosurgery. Duration of bacteremia was recorded and defined as the time between first positive and first negative blood culture. The time of first positive culture was defined as the date in which the culture was obtained. Patients who failed to have at least 1 follow‐up blood culture were not counted toward the main outcome. Additionally, presence of a foreign body (cardiac device, orthopedic prosthesis, tunneled catheter, nontunneled catheter) and presumed source of infection as documented in the electronic medical record by the treating service was also collected. Infections were considered community associated when onset of bacteremia occurred within the first 72 hours of admission, and hospital associated if onset of bacteremia occurred after 72 hours of admission.

Based on current practice guidelines,[9] the variables considered processes of care were the time to obtain the first follow‐up blood culture, time from first positive blood culture to initiation of appropriate antibiotic therapy (defined as a loading dose of vancomycin of 15 mg/kg, or a ‐lactam if the organism was susceptible), time to obtain the first vancomycin trough (when indicated), time from first positive blood culture to consultation with ID specialist, appropriate antibiotic de‐escalation (vancomycin to ‐lactam antibiotic if the organism was susceptible and the patient had no allergies or contraindications), and obtaining an echocardiographic study (transthoracic echocardiogram or transesophageal echocardiogram).

Statistical analyses were performed using SAS 9.2 (SAS Institute, Cary, NC). Differences in proportions were analyzed with ² or Fisher exact test, accordingly. Differences in means among continuous variables were evaluated using independent samples of paired samples t tests as appropriate for the analysis. Continuous variables were dichotomized using a clinically established cutoff to determine relative risk (RR). A univariate analysis of risk factors associated with clinical failure was performed. Multivariable analyses were performed using logistic regression. Models were created using the backward stepwise approach and included all variables found to be statistically significant at less than 0.05 level in the univariate model and those of clinical significance. The study was reviewed and approved by the institutional review boards at the University of Miami and Jackson Memorial Hospital.

RESULTS

During the study period, 241 patients with a first episode of SAB were identified. MRSA and MSSA were isolated in 124 (51.4%) and 117 (48.5%) patients, respectively. Demographic and clinical characteristics of the study population based on isolate are summarized in Table 1. One hundred seventy‐nine (74.3%) patients were under the care of internal medicine services. There was no association between treating service (medical vs surgical) and clinical failure.

The onset of infection occurred in the community in 77 (62.1%) patients with MRSA and in 77 (65.8%) patients with MSSA. The documented source of bacteremia was unknown in 30% of patients with MRSA and 44% of those with MSSA BSI. When ID specialists were consulted, patients were more likely to have a source of infection identified (RR: 1.5; 95% confidence interval [CI]: 1.2‐1.8; P<0.0001). The most commonly documented sources of infection were CLABSI, which occurred in 32 (25.8%) patients with MRSA and 21 (17.9%) patients with MSSA, followed by skin and soft tissue infections in 24 (19.3%) patients with MRSA BSI and 20 (17.1%) patients with MSSA BSI. All patients with CLABSI had documentation of catheter removal.

Clinical failure (defined as in‐hospital mortality or persistent bacteremia) occurred in 78 (32.4%) patients. Of these, 50 (20.7%) represented in‐hospital mortality, and 31 (12.9%) had persistent bacteremia. Table 2 summarizes the demographic and clinical characteristics associated with clinical failure. In the univariate analysis, the variables statistically significantly associated with clinical failure were: age greater than 60 years (RR: 1.4; 95% CI: 1.1‐1.8; P=0.001), bacteremia due to MRSA (RR: 1.7; 95% CI: 1.1‐2.5; P=0.008), white race (RR: 0.7; 95% CI: 0.6‐1; P=0.03), acute kidney injury during admission (RR: 2.2; 95% CI: 1.3‐3.7; P=0.004), presence of nontunneled central venous catheters at the onset of bacteremia (RR: 1.9; 95% CI: 1.3‐2.7; P=0.004), and endocarditis (RR: 2.9; 95% CI: 2.1‐3.9; P<0.0001). In the multivariable analysis, age greater than 60 years and endocarditis were found to be independent risk factors for the development of clinical failure.

DISCUSSION

Our study showed a significant rate of morbidity associated with S aureus bacteremia and identified processes of care in the management of SAB that impact patient outcomes.

Our results show that early consultation with an ID specialist was associated with a decreased risk of developing clinical failure, increased likelihood of identification of a source of infection, and positively impacted administration of appropriate antibiotic therapy, especially in cases of MSSA BSI, with overall improvement in patient outcomes. However, consultation with an ID specialist was only obtained in 40.2% of our cases, which is consistent with published data.[10, 11, 12, 13] Consultation with an ID specialist itself did not impact clinical failure, but rather timeliness in obtaining expert guidance was associated with better outcomes. As shown in previous studies,[10, 11, 12, 13, 14] compliance with the standards of care and patient prognosis are improved when ID specialists are involved in the management of SAB. Our study reiterates that early consultation with an ID specialist has a positive outcome in patient care, as opposed to delaying consultation once the patient has persistent bacteremia for more than 7 days. This association could be explained by considering that the majority of the standards of care are time sensitive, which include: obtaining surveillance blood cultures 48 to 96 hours after initial detection[10] or initiating therapy,[11, 14] removal of foci of infection,[10, 11, 12, 14] use of parenteral ‐lactams for the treatment of MSSA,[10, 11, 13, 14] performing echocardiography when clinically indicated,[10, 11, 13, 14] and appropriate duration of therapy.[10, 13, 14] Importantly, studies have shown that when ID specialists' recommendations are followed, patients are more likely to be cured,[10, 11, 13] and are less likely to relapse.[10, 11, 12] Given the complexities of treating patients with SAB and high rates of clinical failures, routine guidance could be beneficial to healthcare providers as part of a multidisciplinary structured strategy that is set in motion the moment a patient with SAB is identified by the microbiology laboratory. The processes of care outlined in this this study can serve as quality of care indicators and be integrated into a structured strategy to optimize the management of SAB.

Regarding optimal timing for follow‐up blood cultures, our results show that delays in obtaining follow‐up blood cultures (more than 4 days from onset of bacteremia) was independently associated with increased risk of clinical failure. Timely follow‐up blood cultures have been previously identified as quality of care indicators.[10, 11, 13, 14] Compliance with obtaining follow‐up blood cultures improves when this step is integrated into a bundle of care.[14]

Antimicrobial therapy was promptly initiated in the majority of the patients in our study. However, areas for improvement were identified. Vancomycin was the empirical therapy of choice in most of the cases, but an appropriate dose was only received by 65% of the patients, and vancomycin levels after the fourth dose were obtained in 85.9% of instances when indicated. Although in our cohort these results were not significantly associated with clinical failure, previous studies have described attainment of a target therapeutic vancomycin trough (1520 mg/dL) as a factor for treatment success.[17, 18] This problem could be addressed through physician education on therapeutic drug monitoring,[19] as well as through an ASP intervention, which have successfully led efforts to improve vancomycin utilization and dosing.[20] Among patients with MSSA BSI, therapy with ‐lactams was associated with improved outcomes, and was more likely to be administered when an ID specialist was consulted. This is in accordance with previous studies that have shown that higher rates of appropriate antimicrobial therapy are achieved when ID specialists are involved in management of SAB.[10, 11, 13, 14] The use of ‐lactams for treatment of MSSA BSI has been consistently associated with lower SAB‐related mortality and relapse.[21, 22, 23, 24, 25, 26]

Echocardiographic studies were obtained in only half of the patients in our cohort, and they were twice more likely to be obtained when an ID specialist was consulted. Although we did not evaluate the appropriateness of the echocardiographic study, the increased proportion of studies performed when ID specialists were consulted could indicate a more in‐depth evaluation of the case. Moreover, in our cohort, when ID specialists where involved in direct patient care, a source of infection was more likely to be identified. This is in accordance with previous studies proposing that because evaluation by ID specialists are more detailed, they lead to increased use in ancillary studies and recognition of complicated cases.[10, 12]

Limitations of this study include its retrospective design and the fact that it was performed in a single institution. The source of infection was defined as documented by treating providers and not by independent diagnostic criteria. Antibiotic use was collected throughout duration of admission, and was not followed after patients were discharged, as these data were not available on the electronic medical record for all patients. Deaths that may have occurred after hospital discharge were not included. We did not account for elevated vancomycin minimum inhibitory concentration as a risk factor for the main outcome, and adjustment of vancomycin based on serum levels was not factored in. Acute kidney injury was accounted for anytime during hospitalization, but not in relation to antimicrobial administration. Despite the limitations, our study has strengths that make our results generalizable. Although our institution is a single medical center, it serves a large and diverse population as reflected in our cases. Even though this is a retrospective cohort study, the use of a centralized electronic medical record allowed us to identify each aspect of the management of SAB, as implemented by different treating services (medical and surgical), as continuous variables (days) rather than only in a dichotomous fashion. Moreover, by being a community teaching hospital, we were able to explore aspects of the practice of physicians in training versus practicing clinicians. These results could be extrapolated to other healthcare facilities aiming to improve the management of SAB.

CONCLUSIONS

Our results suggest that obtaining timely follow‐up blood cultures, use of ‐lactams in patients with MSSA BSI, and early consultation with infectious diseases are the processes of care that could serve as quality and patient‐safety indicators for the management of SAB. These results contribute to a growing body of evidence supporting the implementation of structured processes of care to optimize the management and clinical outcomes of hospitalized patients with SAB.

Disclosure: Nothing to report.

A seminal 1996 New England Journal of Medicine article introduced the term hospitalist to describe the emerging trend of primary care physicians practicing in inpatient hospital settings.[1] Although physicians had practice patterns akin to hospitalists prior to the introduction of the term,[2] the field continues to grow and formalize as a unique specialty in medicine.

There is currently no board certification or specialty billing code associated with hospitalists. In 2009, the American Board of Internal Medicine and American Board of Family Medicine introduced a Focused Practice in Hospital Medicine optional recertification pathway.[3] However, absent a unique identifier, it remains difficult to identify the number of hospitalists practicing today. Issues with identification notwithstanding, published data consistently suggest that the number of hospitalists has grown dramatically over the last 2 decades.[4, 5, 6]

The Centers for Medicare and Medicaid Services (CMS), along with other payers, classify hospitalists based on their board certificationmost commonly internal medicine or family practice. Other approaches for more precise assessment utilized billing data or hospital designation. Saint et al. identified hospital‐based providers practicing in Washington State in 1994 using variable thresholds of billing for inpatient services.[2] In 2011, Welch et al. identified 25,787 hospitalists nationwide, using a 90% threshold of billing inpatient services in Medicare data.[6] That same year, an American Hospital Association survey identified 34,411 hospitalists based on self‐reporting.[4]

Building on the work of previous researchers, we applied an updated threshold of inpatient services in publicly available 2012 Medicare Provider Utilization and Payment Data to identify a range of hospitalists practicing in the United States. We also examine the codes billed by providers identified in different decile billing thresholds to assess the validity of using lower thresholds to identify hospitalists.

METHODS

RESULTS

The 2012 Medicare pay data included 664,253 physicians with unique NPIs. Of these, 169,317 had IM/FP specialty designations, whereas just under half (46.25%) of those physicians billed any of the inpatient HCPCS codes associated with our threshold.

Table 1 describes the range of number of hospitalists identified by varying the threshold of inpatient services. A total of 28,473 providers bill the threshold‐associated inpatient codes almost exclusively, whereas each descending decile increases in size by an average of 7.29%.

We also analyzed billing patterns of a subset of physicians who billed our threshold codes between 60% and 70% of the time to better characterize the remainder of clinical work they perform. This group included 2282 physicians and only 56 unique HCPCS codes with frequencies greater than 0.1%. After clustering related codes, we identified 4 common code groups that account for the majority of the remaining billing beyond inpatient threshold codes (Table 2).

DISCUSSION

Hospitalists make up approximately 5% of the practicing physicians nationwide, performing a critical role caring for hospitalized patients. Saint et al. defined a pure hospitalist as a physician who meets a 90% threshold of inpatient services.[2] This approach has been replicated in subsequent studies that used a 90% threshold to identify hospitalists.[5, 6] Our results with the same threshold reveal more than 28,000 hospitalists with nearly uniform practice patterns, a 10% growth in the number of hospitalists from the Welch et al. analysis in 2011.[6]

A threshold is not a perfect tool for identifying groups of practicing physicians, as it creates an arbitrary cutoff within a dataset. Undoubtedly our analysis could include providers who would not consider themselves hospitalists, or alternatively, appear to have a hospital‐based practice when they do not. Our results suggest that a 90% threshold may identify a majority of practicing hospitalists, but excludes providers who likely identify as hospitalists albeit with divergent practice and billing patterns.

A lower threshold may be more inclusive of the current realities of hospitalist practice, accounting for the myriad other services provided during, immediately prior to, or following a hospitalization. With hospitalists commonly practicing in diverse facility settings, rotating through rehabilitation or nursing home facilities, discharge clinics, and preoperative medicine practices, the continued use of a 90% threshold appears to exclude a sizable number of practicing hospitalists.

In the absence of a formal identifier, developing identification methodologies that account for the diversity of hospitalist practice is crucial. As physician payment transitions to value‐based reimbursement, systems must have the ability to account for and allocate the most efficient mix of providers for their patient populations. Because provider alignment and coordination are structural features of these programs, these systems‐based changes in effect require accurate identification of hospitalists, yet currently lack the tools to do so.

A seminal 1996 New England Journal of Medicine article introduced the term hospitalist to describe the emerging trend of primary care physicians practicing in inpatient hospital settings.[1] Although physicians had practice patterns akin to hospitalists prior to the introduction of the term,[2] the field continues to grow and formalize as a unique specialty in medicine.

There is currently no board certification or specialty billing code associated with hospitalists. In 2009, the American Board of Internal Medicine and American Board of Family Medicine introduced a Focused Practice in Hospital Medicine optional recertification pathway.[3] However, absent a unique identifier, it remains difficult to identify the number of hospitalists practicing today. Issues with identification notwithstanding, published data consistently suggest that the number of hospitalists has grown dramatically over the last 2 decades.[4, 5, 6]

The Centers for Medicare and Medicaid Services (CMS), along with other payers, classify hospitalists based on their board certificationmost commonly internal medicine or family practice. Other approaches for more precise assessment utilized billing data or hospital designation. Saint et al. identified hospital‐based providers practicing in Washington State in 1994 using variable thresholds of billing for inpatient services.[2] In 2011, Welch et al. identified 25,787 hospitalists nationwide, using a 90% threshold of billing inpatient services in Medicare data.[6] That same year, an American Hospital Association survey identified 34,411 hospitalists based on self‐reporting.[4]

Building on the work of previous researchers, we applied an updated threshold of inpatient services in publicly available 2012 Medicare Provider Utilization and Payment Data to identify a range of hospitalists practicing in the United States. We also examine the codes billed by providers identified in different decile billing thresholds to assess the validity of using lower thresholds to identify hospitalists.

METHODS

RESULTS

The 2012 Medicare pay data included 664,253 physicians with unique NPIs. Of these, 169,317 had IM/FP specialty designations, whereas just under half (46.25%) of those physicians billed any of the inpatient HCPCS codes associated with our threshold.

Table 1 describes the range of number of hospitalists identified by varying the threshold of inpatient services. A total of 28,473 providers bill the threshold‐associated inpatient codes almost exclusively, whereas each descending decile increases in size by an average of 7.29%.

We also analyzed billing patterns of a subset of physicians who billed our threshold codes between 60% and 70% of the time to better characterize the remainder of clinical work they perform. This group included 2282 physicians and only 56 unique HCPCS codes with frequencies greater than 0.1%. After clustering related codes, we identified 4 common code groups that account for the majority of the remaining billing beyond inpatient threshold codes (Table 2).

DISCUSSION

Hospitalists make up approximately 5% of the practicing physicians nationwide, performing a critical role caring for hospitalized patients. Saint et al. defined a pure hospitalist as a physician who meets a 90% threshold of inpatient services.[2] This approach has been replicated in subsequent studies that used a 90% threshold to identify hospitalists.[5, 6] Our results with the same threshold reveal more than 28,000 hospitalists with nearly uniform practice patterns, a 10% growth in the number of hospitalists from the Welch et al. analysis in 2011.[6]

A threshold is not a perfect tool for identifying groups of practicing physicians, as it creates an arbitrary cutoff within a dataset. Undoubtedly our analysis could include providers who would not consider themselves hospitalists, or alternatively, appear to have a hospital‐based practice when they do not. Our results suggest that a 90% threshold may identify a majority of practicing hospitalists, but excludes providers who likely identify as hospitalists albeit with divergent practice and billing patterns.

A lower threshold may be more inclusive of the current realities of hospitalist practice, accounting for the myriad other services provided during, immediately prior to, or following a hospitalization. With hospitalists commonly practicing in diverse facility settings, rotating through rehabilitation or nursing home facilities, discharge clinics, and preoperative medicine practices, the continued use of a 90% threshold appears to exclude a sizable number of practicing hospitalists.

In the absence of a formal identifier, developing identification methodologies that account for the diversity of hospitalist practice is crucial. As physician payment transitions to value‐based reimbursement, systems must have the ability to account for and allocate the most efficient mix of providers for their patient populations. Because provider alignment and coordination are structural features of these programs, these systems‐based changes in effect require accurate identification of hospitalists, yet currently lack the tools to do so.

A seminal 1996 New England Journal of Medicine article introduced the term hospitalist to describe the emerging trend of primary care physicians practicing in inpatient hospital settings.[1] Although physicians had practice patterns akin to hospitalists prior to the introduction of the term,[2] the field continues to grow and formalize as a unique specialty in medicine.

There is currently no board certification or specialty billing code associated with hospitalists. In 2009, the American Board of Internal Medicine and American Board of Family Medicine introduced a Focused Practice in Hospital Medicine optional recertification pathway.[3] However, absent a unique identifier, it remains difficult to identify the number of hospitalists practicing today. Issues with identification notwithstanding, published data consistently suggest that the number of hospitalists has grown dramatically over the last 2 decades.[4, 5, 6]

The Centers for Medicare and Medicaid Services (CMS), along with other payers, classify hospitalists based on their board certificationmost commonly internal medicine or family practice. Other approaches for more precise assessment utilized billing data or hospital designation. Saint et al. identified hospital‐based providers practicing in Washington State in 1994 using variable thresholds of billing for inpatient services.[2] In 2011, Welch et al. identified 25,787 hospitalists nationwide, using a 90% threshold of billing inpatient services in Medicare data.[6] That same year, an American Hospital Association survey identified 34,411 hospitalists based on self‐reporting.[4]

Building on the work of previous researchers, we applied an updated threshold of inpatient services in publicly available 2012 Medicare Provider Utilization and Payment Data to identify a range of hospitalists practicing in the United States. We also examine the codes billed by providers identified in different decile billing thresholds to assess the validity of using lower thresholds to identify hospitalists.

METHODS

RESULTS

The 2012 Medicare pay data included 664,253 physicians with unique NPIs. Of these, 169,317 had IM/FP specialty designations, whereas just under half (46.25%) of those physicians billed any of the inpatient HCPCS codes associated with our threshold.

Table 1 describes the range of number of hospitalists identified by varying the threshold of inpatient services. A total of 28,473 providers bill the threshold‐associated inpatient codes almost exclusively, whereas each descending decile increases in size by an average of 7.29%.

We also analyzed billing patterns of a subset of physicians who billed our threshold codes between 60% and 70% of the time to better characterize the remainder of clinical work they perform. This group included 2282 physicians and only 56 unique HCPCS codes with frequencies greater than 0.1%. After clustering related codes, we identified 4 common code groups that account for the majority of the remaining billing beyond inpatient threshold codes (Table 2).

DISCUSSION

Hospitalists make up approximately 5% of the practicing physicians nationwide, performing a critical role caring for hospitalized patients. Saint et al. defined a pure hospitalist as a physician who meets a 90% threshold of inpatient services.[2] This approach has been replicated in subsequent studies that used a 90% threshold to identify hospitalists.[5, 6] Our results with the same threshold reveal more than 28,000 hospitalists with nearly uniform practice patterns, a 10% growth in the number of hospitalists from the Welch et al. analysis in 2011.[6]

A threshold is not a perfect tool for identifying groups of practicing physicians, as it creates an arbitrary cutoff within a dataset. Undoubtedly our analysis could include providers who would not consider themselves hospitalists, or alternatively, appear to have a hospital‐based practice when they do not. Our results suggest that a 90% threshold may identify a majority of practicing hospitalists, but excludes providers who likely identify as hospitalists albeit with divergent practice and billing patterns.

A lower threshold may be more inclusive of the current realities of hospitalist practice, accounting for the myriad other services provided during, immediately prior to, or following a hospitalization. With hospitalists commonly practicing in diverse facility settings, rotating through rehabilitation or nursing home facilities, discharge clinics, and preoperative medicine practices, the continued use of a 90% threshold appears to exclude a sizable number of practicing hospitalists.

In the absence of a formal identifier, developing identification methodologies that account for the diversity of hospitalist practice is crucial. As physician payment transitions to value‐based reimbursement, systems must have the ability to account for and allocate the most efficient mix of providers for their patient populations. Because provider alignment and coordination are structural features of these programs, these systems‐based changes in effect require accurate identification of hospitalists, yet currently lack the tools to do so.

The hospitalized patient experience has become an area of increased focus for hospitals given the recent coupling of patient satisfaction to reimbursement rates for Medicare patients.[1] Although patient experiences are multifactorial, 1 component is the relationship that hospitalized patients develop with their inpatient physicians. In recognition of the importance of this relationship, several organizations including the Society of Hospital Medicine, Society of General Internal Medicine, American College of Physicians, the American College of Emergency Physicians, and the Accreditation Council for Graduate Medical Education have recommended that patients know and understand who is guiding their care at all times during their hospitalization.[2, 3] Unfortunately, previous studies have shown that hospitalized patients often lack the ability to identify[4, 5] and understand their course of care.[6, 7] This may be due to numerous clinical factors including lack of a prior relationship, rapid pace of clinical care, and the frequent transitions of care found in both hospitalists and general medicine teaching services.[5, 8, 9] Regardless of the cause, one could hypothesize that patients who are unable to identify or understand the role of their physician may be less informed about their hospitalization, which may lead to further confusion, dissatisfaction, and ultimately a poor experience.

Given the proliferation of nonteaching hospitalist services in teaching hospitals, it is important to understand if patient experiences differ between general medicine teaching and hospitalist services. Several reasons could explain why patient experiences may vary on these services. For example, patients on a hospitalist service will likely interact with a single physician caretaker, which may give a feeling of more personalized care. In contrast, patients on general medicine teaching services are cared for by larger teams of residents under the supervision of an attending physician. Residents are also subjected to duty‐hour restrictions, clinic responsibilities, and other educational requirements that may impede the continuity of care for hospitalized patients.[10, 11, 12] Although 1 study has shown that hospitalist‐intensive hospitals perform better on patient satisfaction measures,[13] no study to date has compared patient‐reported experiences on general medicine teaching and nonteaching hospitalist services. This study aimed to evaluate the hospitalized patient experience on both teaching and nonteaching hospitalist services by assessing several patient‐reported measures of their experience, namely their confidence in their ability to identify their physician(s), understand their roles, and their rating of both the coordination and overall care.

METHODS

RESULTS

In total, 14,855 patients were enrolled during their hospitalization with 57% and 61% completing the 30‐day follow‐up survey on the hospitalist and general medicine teaching service, respectively. In total, 4131 (69%) and 4322 (48%) of the hospitalist and general medicine services, respectively, either did not answer all survey questions, or were missing basic demographic data, and thus were excluded. Data from 4591 patients on the general medicine teaching (52% of those enrolled at hospitalization) and 1811 on the hospitalist service (31% of those enrolled at hospitalization) were used for final analysis (Figure 1). Respondents were predominantly female (61% and 56%), African American (75% and 63%), with a mean age of 56.2 (19.4) and 57.1 (16.1) years, for the general medicine teaching and hospitalist services, respectively. A majority of patients (71% and 66%) had a CCI of 0 to 3 on both services. There were differences in self‐reported comorbidities between the 2 groups, with hospitalist services having a higher prevalence of cancer (20% vs 7%), renal disease (25% vs 18%), and liver disease (23% vs 7%). Patients on the hospitalist service had a longer mean LOS (5.5 vs 4.8 days), a greater percentage of a hospitalization within 1 year (58% vs 52%), and a larger proportion who were admitted in 2011 to 2013 compared to 2007 to 2010 (75% vs 39%), when compared to the general medicine teaching services. Median LOS and interquartile ranges were similar between both groups. Although most baseline demographics were statistically different between the 2 groups (Table 1), these differences were likely clinically insignificant. Compared to those who responded to the follow‐up survey, nonresponders were more likely to be African American (73% and 64%, P < 0.001) and female (60% and 56%, P < 0.01). The nonresponders were more likely to be hospitalized in the past 1 year (62% and 53%, P < 0.001) and have a lower CCI (CCI 03 [75% and 80%, P < 0.001]) compared to responders. Demographics between responders and nonresponders were also statistically different from one another.

Figure 1

Unadjusted results revealed that patients on the hospitalist service were more confident in their abilities to identify their physician(s) (50% vs 45%, P < 0.001), perceived greater ability in understanding the role of their physician(s) (54% vs 50%, P < 0.001), and reported greater satisfaction with coordination and teamwork (68% vs 64%, P = 0.006) and with overall care (73% vs 67%, P < 0.001) (Figure 2).

Figure 2

From the mixed‐effects regression models it was discovered that admission to the hospitalist service was associated with a higher odds ratio (OR) of reporting overall care as excellent or very good (OR: 1.33; 95% confidence interval [CI]: 1.15‐1.47). There was no difference between services in patients' ability to identify their physician(s) (OR: 0.89; 95% CI: 0.61‐1.11), in patients reporting a better understanding of the role of their physician(s) (OR: 1.09; 95% CI: 0.94‐1.23), or in their rating of overall coordination and teamwork (OR: 0.71; 95% CI: 0.42‐1.89).

A subgroup analysis was performed on the 25% of hospitalist attendings in the general medicine teaching service comparing this cohort to the hospitalist services, and it was found that patients perceived better overall care on the hospitalist service (OR: 1.17; 95% CI: 1.01‐ 1.31) than on the general medicine service (Table 2). All other domains in the subgroup analysis were not statistically significant. Finally, an ordinal logistic regression was performed for each of these outcomes, but it did not show any major differences compared to the logistic regression of dichotomous outcomes.

DISCUSSION

This study is the first to directly compare measures of patient experience on hospitalist and general medicine teaching services in a large, multiyear comparison across multiple domains. In adjusted analysis, we found that patients on nonteaching hospitalist services rated their overall care better than those on general medicine teaching services, whereas no differences in patients' ability to identify their physician(s), understand their role in their care, or rating of coordination of care were found. Although the magnitude of the differences in rating of overall care may appear small, it remains noteworthy because of the recent focus on patient experience at the reimbursement level, where small differences in performance can lead to large changes in payment. Because of the observational design of this study, it is important to consider mechanisms that could account for our findings.

The first are the structural differences between the 2 services. Our subgroup analysis comparing patients rating of overall care on a general medicine service with a hospitalist attending to a pure hospitalist cohort found a significant difference between the groups, indicating that the structural differences between the 2 groups may be a significant contributor to patient satisfaction ratings. Under the care of a hospitalist service, a patient would only interact with a single physician on a daily basis, possibly leading to a more meaningful relationship and improved communication between patient and provider. Alternatively, while on a general medicine teaching service, patients would likely interact with multiple physicians, as a result making their confidence in their ability to identify and perception at understanding physicians' roles more challenging.[18] This dilemma is further compounded by duty hour restrictions, which have subsequently led to increased fragmentation in housestaff scheduling. The patient experience on the general medicine teaching service may be further complicated by recent data that show residents spend a minority of time in direct patient care,[19, 20] which could additionally contribute to patients' inability to understand who their physicians are and to the decreased satisfaction with their care. This combination of structural complexity, duty hour reform, and reduced direct patient interaction would likely decrease the chance a patient will interact with the same resident on a consistent basis,[5, 21] thus making the ability to truly understand who their caretakers are, and the role they play, more difficult.

Another contributing factor could be the use of NPAs on our hospitalist service. Given that these providers often see the patient on a more continual basis, hospitalized patients' exposure to a single, continuous caretaker may be a factor in our findings.[22] Furthermore, with studies showing that hospitalists also spend a small fraction of their day in direct patient care,[23, 24, 25] the use of NPAs may allow our hospitalists to spend greater amounts of time with their patients, thus improving patients' rating of their overall care and influencing their perceived ability to understand their physician's role.

Although there was no difference between general medicine teaching and hospitalist services with respect to patient understanding of their roles, our data suggest that both groups would benefit from interventions to target this area. Focused attempts at improving patient's ability to identify and explain the roles of their inpatient physician(s) have been performed. For example, previous studies have attempted to improve a patient's ability to identify their physician through physician facecards[8, 9] or the use of other simple interventions (ie, bedside whiteboards).[4, 26] Results from such interventions are mixed, as they have demonstrated the capacity to improve patients' ability to identify who their physician is, whereas few have shown any appreciable improvement in patient satisfaction.[26]

Although our findings suggest that structural differences in team composition may be a possible explanation, it is also important to consider how the quality of care a patient receives affects their experience. For instance, hospitalists have been shown to produce moderate improvements in patient‐centered outcomes such as 30‐day readmission[27] and hospital length of stay[14, 28, 29, 30, 31] when compared to other care providers, which in turn could be reflected in the patient's perception of their overall care. In a large national study of acute care hospitals using the Hospital Consumer Assessment of Healthcare Providers and Systems survey, Chen and colleagues found that for most measures of patient satisfaction, hospitals with greater use of hospitalist care were associated with better patient‐centered care.[13] These outcomes were in part driven by patient‐centered domains such as discharge planning, pain control, and medication management. It is possible that patients are sensitive to the improved outcomes that are associated with hospitalist services, and reflect this in their measures of patient satisfaction.

Last, because this is an observational study and not a randomized trial, it is possible that the clinical differences in the patients cared for by these services could have led to our findings. Although the clinical significance of the differences in patient demographics were small, patients seen on the hospitalist service were more likely to be older white males, with a slightly longer LOS, greater comorbidities, and more hospitalizations in the previous year than those seen on the general medicine teaching service. Additionally, our hospitalist service frequently cares for highly specific subpopulations (ie, liver and renal transplant patients, and oncology patients), which could have influenced our results. For example, transplant patients who may be very grateful for their second chance, are preferentially admitted to the hospitalist service, which could have biased our results in favor of hospitalists.[32] Unfortunately, we were unable to control for all such factors.

Although we hope that multivariable analysis can adjust for many of these differences, we are not able to account for possible unmeasured confounders such as time of day of admission, health literacy, personality differences, physician turnover, or nursing and other ancillary care that could contribute to these findings. In addition to its observational study design, our study has several other limitations. First, our study was performed at a single institution, thus limiting its generalizability. Second, as a retrospective study based on observational data, no definitive conclusions regarding causality can be made. Third, although our response rate was low, it is comparable to other studies that have examined underserved populations.[33, 34] Fourth, because our survey was performed 30 days after hospitalization, this may impart imprecision on our outcomes measures. Finally, we were not able to mitigate selection bias through imputation for missing data .

All together, given the small absolute differences between the groups in patients' ratings of their overall care compared to large differences in possible confounders, these findings call for further exploration into the significance and possible mechanisms of these outcomes. Our study raises the potential possibility that the structural component of a care team may play a role in overall patient satisfaction. If this is the case, future studies of team structure could help inform how best to optimize this component for the patient experience. On the other hand, if process differences are to explain our findings, it is important to distill the types of processes hospitalists are using to improve the patient experience and potentially export this to resident services.

Finally, if similar results were found in other institutions, these findings could have implications on how hospitals respond to new payment models that are linked to patient‐experience measures. For example, the Hospital Value‐Based Purchasing Program currently links the Centers for Medicare and Medicaid Services payments to a set of quality measures that consist of (1) clinical processes of care (70%) and (2) the patient experience (30%).[1] Given this linkage, any small changes in the domain of patient satisfaction could have large payment implications on a national level.

CONCLUSION

In summary, in this large‐scale multiyear study, patients cared for by a nonteaching hospitalist service reported greater satisfaction with their overall care than patients cared for by a general medicine teaching service. This difference could be mediated by the structural differences between these 2 services. As hospitals seek to optimize patient experiences in an era where reimbursement models are now being linked to patient‐experience measures, future work should focus on further understanding the mechanisms for these findings.

The hospitalized patient experience has become an area of increased focus for hospitals given the recent coupling of patient satisfaction to reimbursement rates for Medicare patients.[1] Although patient experiences are multifactorial, 1 component is the relationship that hospitalized patients develop with their inpatient physicians. In recognition of the importance of this relationship, several organizations including the Society of Hospital Medicine, Society of General Internal Medicine, American College of Physicians, the American College of Emergency Physicians, and the Accreditation Council for Graduate Medical Education have recommended that patients know and understand who is guiding their care at all times during their hospitalization.[2, 3] Unfortunately, previous studies have shown that hospitalized patients often lack the ability to identify[4, 5] and understand their course of care.[6, 7] This may be due to numerous clinical factors including lack of a prior relationship, rapid pace of clinical care, and the frequent transitions of care found in both hospitalists and general medicine teaching services.[5, 8, 9] Regardless of the cause, one could hypothesize that patients who are unable to identify or understand the role of their physician may be less informed about their hospitalization, which may lead to further confusion, dissatisfaction, and ultimately a poor experience.

Given the proliferation of nonteaching hospitalist services in teaching hospitals, it is important to understand if patient experiences differ between general medicine teaching and hospitalist services. Several reasons could explain why patient experiences may vary on these services. For example, patients on a hospitalist service will likely interact with a single physician caretaker, which may give a feeling of more personalized care. In contrast, patients on general medicine teaching services are cared for by larger teams of residents under the supervision of an attending physician. Residents are also subjected to duty‐hour restrictions, clinic responsibilities, and other educational requirements that may impede the continuity of care for hospitalized patients.[10, 11, 12] Although 1 study has shown that hospitalist‐intensive hospitals perform better on patient satisfaction measures,[13] no study to date has compared patient‐reported experiences on general medicine teaching and nonteaching hospitalist services. This study aimed to evaluate the hospitalized patient experience on both teaching and nonteaching hospitalist services by assessing several patient‐reported measures of their experience, namely their confidence in their ability to identify their physician(s), understand their roles, and their rating of both the coordination and overall care.

METHODS

RESULTS

In total, 14,855 patients were enrolled during their hospitalization with 57% and 61% completing the 30‐day follow‐up survey on the hospitalist and general medicine teaching service, respectively. In total, 4131 (69%) and 4322 (48%) of the hospitalist and general medicine services, respectively, either did not answer all survey questions, or were missing basic demographic data, and thus were excluded. Data from 4591 patients on the general medicine teaching (52% of those enrolled at hospitalization) and 1811 on the hospitalist service (31% of those enrolled at hospitalization) were used for final analysis (Figure 1). Respondents were predominantly female (61% and 56%), African American (75% and 63%), with a mean age of 56.2 (19.4) and 57.1 (16.1) years, for the general medicine teaching and hospitalist services, respectively. A majority of patients (71% and 66%) had a CCI of 0 to 3 on both services. There were differences in self‐reported comorbidities between the 2 groups, with hospitalist services having a higher prevalence of cancer (20% vs 7%), renal disease (25% vs 18%), and liver disease (23% vs 7%). Patients on the hospitalist service had a longer mean LOS (5.5 vs 4.8 days), a greater percentage of a hospitalization within 1 year (58% vs 52%), and a larger proportion who were admitted in 2011 to 2013 compared to 2007 to 2010 (75% vs 39%), when compared to the general medicine teaching services. Median LOS and interquartile ranges were similar between both groups. Although most baseline demographics were statistically different between the 2 groups (Table 1), these differences were likely clinically insignificant. Compared to those who responded to the follow‐up survey, nonresponders were more likely to be African American (73% and 64%, P < 0.001) and female (60% and 56%, P < 0.01). The nonresponders were more likely to be hospitalized in the past 1 year (62% and 53%, P < 0.001) and have a lower CCI (CCI 03 [75% and 80%, P < 0.001]) compared to responders. Demographics between responders and nonresponders were also statistically different from one another.

Figure 1

Unadjusted results revealed that patients on the hospitalist service were more confident in their abilities to identify their physician(s) (50% vs 45%, P < 0.001), perceived greater ability in understanding the role of their physician(s) (54% vs 50%, P < 0.001), and reported greater satisfaction with coordination and teamwork (68% vs 64%, P = 0.006) and with overall care (73% vs 67%, P < 0.001) (Figure 2).

Figure 2

From the mixed‐effects regression models it was discovered that admission to the hospitalist service was associated with a higher odds ratio (OR) of reporting overall care as excellent or very good (OR: 1.33; 95% confidence interval [CI]: 1.15‐1.47). There was no difference between services in patients' ability to identify their physician(s) (OR: 0.89; 95% CI: 0.61‐1.11), in patients reporting a better understanding of the role of their physician(s) (OR: 1.09; 95% CI: 0.94‐1.23), or in their rating of overall coordination and teamwork (OR: 0.71; 95% CI: 0.42‐1.89).

A subgroup analysis was performed on the 25% of hospitalist attendings in the general medicine teaching service comparing this cohort to the hospitalist services, and it was found that patients perceived better overall care on the hospitalist service (OR: 1.17; 95% CI: 1.01‐ 1.31) than on the general medicine service (Table 2). All other domains in the subgroup analysis were not statistically significant. Finally, an ordinal logistic regression was performed for each of these outcomes, but it did not show any major differences compared to the logistic regression of dichotomous outcomes.

DISCUSSION

This study is the first to directly compare measures of patient experience on hospitalist and general medicine teaching services in a large, multiyear comparison across multiple domains. In adjusted analysis, we found that patients on nonteaching hospitalist services rated their overall care better than those on general medicine teaching services, whereas no differences in patients' ability to identify their physician(s), understand their role in their care, or rating of coordination of care were found. Although the magnitude of the differences in rating of overall care may appear small, it remains noteworthy because of the recent focus on patient experience at the reimbursement level, where small differences in performance can lead to large changes in payment. Because of the observational design of this study, it is important to consider mechanisms that could account for our findings.

The first are the structural differences between the 2 services. Our subgroup analysis comparing patients rating of overall care on a general medicine service with a hospitalist attending to a pure hospitalist cohort found a significant difference between the groups, indicating that the structural differences between the 2 groups may be a significant contributor to patient satisfaction ratings. Under the care of a hospitalist service, a patient would only interact with a single physician on a daily basis, possibly leading to a more meaningful relationship and improved communication between patient and provider. Alternatively, while on a general medicine teaching service, patients would likely interact with multiple physicians, as a result making their confidence in their ability to identify and perception at understanding physicians' roles more challenging.[18] This dilemma is further compounded by duty hour restrictions, which have subsequently led to increased fragmentation in housestaff scheduling. The patient experience on the general medicine teaching service may be further complicated by recent data that show residents spend a minority of time in direct patient care,[19, 20] which could additionally contribute to patients' inability to understand who their physicians are and to the decreased satisfaction with their care. This combination of structural complexity, duty hour reform, and reduced direct patient interaction would likely decrease the chance a patient will interact with the same resident on a consistent basis,[5, 21] thus making the ability to truly understand who their caretakers are, and the role they play, more difficult.

Another contributing factor could be the use of NPAs on our hospitalist service. Given that these providers often see the patient on a more continual basis, hospitalized patients' exposure to a single, continuous caretaker may be a factor in our findings.[22] Furthermore, with studies showing that hospitalists also spend a small fraction of their day in direct patient care,[23, 24, 25] the use of NPAs may allow our hospitalists to spend greater amounts of time with their patients, thus improving patients' rating of their overall care and influencing their perceived ability to understand their physician's role.

Although there was no difference between general medicine teaching and hospitalist services with respect to patient understanding of their roles, our data suggest that both groups would benefit from interventions to target this area. Focused attempts at improving patient's ability to identify and explain the roles of their inpatient physician(s) have been performed. For example, previous studies have attempted to improve a patient's ability to identify their physician through physician facecards[8, 9] or the use of other simple interventions (ie, bedside whiteboards).[4, 26] Results from such interventions are mixed, as they have demonstrated the capacity to improve patients' ability to identify who their physician is, whereas few have shown any appreciable improvement in patient satisfaction.[26]

Although our findings suggest that structural differences in team composition may be a possible explanation, it is also important to consider how the quality of care a patient receives affects their experience. For instance, hospitalists have been shown to produce moderate improvements in patient‐centered outcomes such as 30‐day readmission[27] and hospital length of stay[14, 28, 29, 30, 31] when compared to other care providers, which in turn could be reflected in the patient's perception of their overall care. In a large national study of acute care hospitals using the Hospital Consumer Assessment of Healthcare Providers and Systems survey, Chen and colleagues found that for most measures of patient satisfaction, hospitals with greater use of hospitalist care were associated with better patient‐centered care.[13] These outcomes were in part driven by patient‐centered domains such as discharge planning, pain control, and medication management. It is possible that patients are sensitive to the improved outcomes that are associated with hospitalist services, and reflect this in their measures of patient satisfaction.

Last, because this is an observational study and not a randomized trial, it is possible that the clinical differences in the patients cared for by these services could have led to our findings. Although the clinical significance of the differences in patient demographics were small, patients seen on the hospitalist service were more likely to be older white males, with a slightly longer LOS, greater comorbidities, and more hospitalizations in the previous year than those seen on the general medicine teaching service. Additionally, our hospitalist service frequently cares for highly specific subpopulations (ie, liver and renal transplant patients, and oncology patients), which could have influenced our results. For example, transplant patients who may be very grateful for their second chance, are preferentially admitted to the hospitalist service, which could have biased our results in favor of hospitalists.[32] Unfortunately, we were unable to control for all such factors.

Although we hope that multivariable analysis can adjust for many of these differences, we are not able to account for possible unmeasured confounders such as time of day of admission, health literacy, personality differences, physician turnover, or nursing and other ancillary care that could contribute to these findings. In addition to its observational study design, our study has several other limitations. First, our study was performed at a single institution, thus limiting its generalizability. Second, as a retrospective study based on observational data, no definitive conclusions regarding causality can be made. Third, although our response rate was low, it is comparable to other studies that have examined underserved populations.[33, 34] Fourth, because our survey was performed 30 days after hospitalization, this may impart imprecision on our outcomes measures. Finally, we were not able to mitigate selection bias through imputation for missing data .

All together, given the small absolute differences between the groups in patients' ratings of their overall care compared to large differences in possible confounders, these findings call for further exploration into the significance and possible mechanisms of these outcomes. Our study raises the potential possibility that the structural component of a care team may play a role in overall patient satisfaction. If this is the case, future studies of team structure could help inform how best to optimize this component for the patient experience. On the other hand, if process differences are to explain our findings, it is important to distill the types of processes hospitalists are using to improve the patient experience and potentially export this to resident services.

Finally, if similar results were found in other institutions, these findings could have implications on how hospitals respond to new payment models that are linked to patient‐experience measures. For example, the Hospital Value‐Based Purchasing Program currently links the Centers for Medicare and Medicaid Services payments to a set of quality measures that consist of (1) clinical processes of care (70%) and (2) the patient experience (30%).[1] Given this linkage, any small changes in the domain of patient satisfaction could have large payment implications on a national level.

CONCLUSION

In summary, in this large‐scale multiyear study, patients cared for by a nonteaching hospitalist service reported greater satisfaction with their overall care than patients cared for by a general medicine teaching service. This difference could be mediated by the structural differences between these 2 services. As hospitals seek to optimize patient experiences in an era where reimbursement models are now being linked to patient‐experience measures, future work should focus on further understanding the mechanisms for these findings.

The hospitalized patient experience has become an area of increased focus for hospitals given the recent coupling of patient satisfaction to reimbursement rates for Medicare patients.[1] Although patient experiences are multifactorial, 1 component is the relationship that hospitalized patients develop with their inpatient physicians. In recognition of the importance of this relationship, several organizations including the Society of Hospital Medicine, Society of General Internal Medicine, American College of Physicians, the American College of Emergency Physicians, and the Accreditation Council for Graduate Medical Education have recommended that patients know and understand who is guiding their care at all times during their hospitalization.[2, 3] Unfortunately, previous studies have shown that hospitalized patients often lack the ability to identify[4, 5] and understand their course of care.[6, 7] This may be due to numerous clinical factors including lack of a prior relationship, rapid pace of clinical care, and the frequent transitions of care found in both hospitalists and general medicine teaching services.[5, 8, 9] Regardless of the cause, one could hypothesize that patients who are unable to identify or understand the role of their physician may be less informed about their hospitalization, which may lead to further confusion, dissatisfaction, and ultimately a poor experience.

Given the proliferation of nonteaching hospitalist services in teaching hospitals, it is important to understand if patient experiences differ between general medicine teaching and hospitalist services. Several reasons could explain why patient experiences may vary on these services. For example, patients on a hospitalist service will likely interact with a single physician caretaker, which may give a feeling of more personalized care. In contrast, patients on general medicine teaching services are cared for by larger teams of residents under the supervision of an attending physician. Residents are also subjected to duty‐hour restrictions, clinic responsibilities, and other educational requirements that may impede the continuity of care for hospitalized patients.[10, 11, 12] Although 1 study has shown that hospitalist‐intensive hospitals perform better on patient satisfaction measures,[13] no study to date has compared patient‐reported experiences on general medicine teaching and nonteaching hospitalist services. This study aimed to evaluate the hospitalized patient experience on both teaching and nonteaching hospitalist services by assessing several patient‐reported measures of their experience, namely their confidence in their ability to identify their physician(s), understand their roles, and their rating of both the coordination and overall care.

METHODS

RESULTS

In total, 14,855 patients were enrolled during their hospitalization with 57% and 61% completing the 30‐day follow‐up survey on the hospitalist and general medicine teaching service, respectively. In total, 4131 (69%) and 4322 (48%) of the hospitalist and general medicine services, respectively, either did not answer all survey questions, or were missing basic demographic data, and thus were excluded. Data from 4591 patients on the general medicine teaching (52% of those enrolled at hospitalization) and 1811 on the hospitalist service (31% of those enrolled at hospitalization) were used for final analysis (Figure 1). Respondents were predominantly female (61% and 56%), African American (75% and 63%), with a mean age of 56.2 (19.4) and 57.1 (16.1) years, for the general medicine teaching and hospitalist services, respectively. A majority of patients (71% and 66%) had a CCI of 0 to 3 on both services. There were differences in self‐reported comorbidities between the 2 groups, with hospitalist services having a higher prevalence of cancer (20% vs 7%), renal disease (25% vs 18%), and liver disease (23% vs 7%). Patients on the hospitalist service had a longer mean LOS (5.5 vs 4.8 days), a greater percentage of a hospitalization within 1 year (58% vs 52%), and a larger proportion who were admitted in 2011 to 2013 compared to 2007 to 2010 (75% vs 39%), when compared to the general medicine teaching services. Median LOS and interquartile ranges were similar between both groups. Although most baseline demographics were statistically different between the 2 groups (Table 1), these differences were likely clinically insignificant. Compared to those who responded to the follow‐up survey, nonresponders were more likely to be African American (73% and 64%, P < 0.001) and female (60% and 56%, P < 0.01). The nonresponders were more likely to be hospitalized in the past 1 year (62% and 53%, P < 0.001) and have a lower CCI (CCI 03 [75% and 80%, P < 0.001]) compared to responders. Demographics between responders and nonresponders were also statistically different from one another.

Figure 1

Unadjusted results revealed that patients on the hospitalist service were more confident in their abilities to identify their physician(s) (50% vs 45%, P < 0.001), perceived greater ability in understanding the role of their physician(s) (54% vs 50%, P < 0.001), and reported greater satisfaction with coordination and teamwork (68% vs 64%, P = 0.006) and with overall care (73% vs 67%, P < 0.001) (Figure 2).

Figure 2

From the mixed‐effects regression models it was discovered that admission to the hospitalist service was associated with a higher odds ratio (OR) of reporting overall care as excellent or very good (OR: 1.33; 95% confidence interval [CI]: 1.15‐1.47). There was no difference between services in patients' ability to identify their physician(s) (OR: 0.89; 95% CI: 0.61‐1.11), in patients reporting a better understanding of the role of their physician(s) (OR: 1.09; 95% CI: 0.94‐1.23), or in their rating of overall coordination and teamwork (OR: 0.71; 95% CI: 0.42‐1.89).

A subgroup analysis was performed on the 25% of hospitalist attendings in the general medicine teaching service comparing this cohort to the hospitalist services, and it was found that patients perceived better overall care on the hospitalist service (OR: 1.17; 95% CI: 1.01‐ 1.31) than on the general medicine service (Table 2). All other domains in the subgroup analysis were not statistically significant. Finally, an ordinal logistic regression was performed for each of these outcomes, but it did not show any major differences compared to the logistic regression of dichotomous outcomes.

DISCUSSION

This study is the first to directly compare measures of patient experience on hospitalist and general medicine teaching services in a large, multiyear comparison across multiple domains. In adjusted analysis, we found that patients on nonteaching hospitalist services rated their overall care better than those on general medicine teaching services, whereas no differences in patients' ability to identify their physician(s), understand their role in their care, or rating of coordination of care were found. Although the magnitude of the differences in rating of overall care may appear small, it remains noteworthy because of the recent focus on patient experience at the reimbursement level, where small differences in performance can lead to large changes in payment. Because of the observational design of this study, it is important to consider mechanisms that could account for our findings.

The first are the structural differences between the 2 services. Our subgroup analysis comparing patients rating of overall care on a general medicine service with a hospitalist attending to a pure hospitalist cohort found a significant difference between the groups, indicating that the structural differences between the 2 groups may be a significant contributor to patient satisfaction ratings. Under the care of a hospitalist service, a patient would only interact with a single physician on a daily basis, possibly leading to a more meaningful relationship and improved communication between patient and provider. Alternatively, while on a general medicine teaching service, patients would likely interact with multiple physicians, as a result making their confidence in their ability to identify and perception at understanding physicians' roles more challenging.[18] This dilemma is further compounded by duty hour restrictions, which have subsequently led to increased fragmentation in housestaff scheduling. The patient experience on the general medicine teaching service may be further complicated by recent data that show residents spend a minority of time in direct patient care,[19, 20] which could additionally contribute to patients' inability to understand who their physicians are and to the decreased satisfaction with their care. This combination of structural complexity, duty hour reform, and reduced direct patient interaction would likely decrease the chance a patient will interact with the same resident on a consistent basis,[5, 21] thus making the ability to truly understand who their caretakers are, and the role they play, more difficult.

Another contributing factor could be the use of NPAs on our hospitalist service. Given that these providers often see the patient on a more continual basis, hospitalized patients' exposure to a single, continuous caretaker may be a factor in our findings.[22] Furthermore, with studies showing that hospitalists also spend a small fraction of their day in direct patient care,[23, 24, 25] the use of NPAs may allow our hospitalists to spend greater amounts of time with their patients, thus improving patients' rating of their overall care and influencing their perceived ability to understand their physician's role.

Although there was no difference between general medicine teaching and hospitalist services with respect to patient understanding of their roles, our data suggest that both groups would benefit from interventions to target this area. Focused attempts at improving patient's ability to identify and explain the roles of their inpatient physician(s) have been performed. For example, previous studies have attempted to improve a patient's ability to identify their physician through physician facecards[8, 9] or the use of other simple interventions (ie, bedside whiteboards).[4, 26] Results from such interventions are mixed, as they have demonstrated the capacity to improve patients' ability to identify who their physician is, whereas few have shown any appreciable improvement in patient satisfaction.[26]

Although our findings suggest that structural differences in team composition may be a possible explanation, it is also important to consider how the quality of care a patient receives affects their experience. For instance, hospitalists have been shown to produce moderate improvements in patient‐centered outcomes such as 30‐day readmission[27] and hospital length of stay[14, 28, 29, 30, 31] when compared to other care providers, which in turn could be reflected in the patient's perception of their overall care. In a large national study of acute care hospitals using the Hospital Consumer Assessment of Healthcare Providers and Systems survey, Chen and colleagues found that for most measures of patient satisfaction, hospitals with greater use of hospitalist care were associated with better patient‐centered care.[13] These outcomes were in part driven by patient‐centered domains such as discharge planning, pain control, and medication management. It is possible that patients are sensitive to the improved outcomes that are associated with hospitalist services, and reflect this in their measures of patient satisfaction.

Last, because this is an observational study and not a randomized trial, it is possible that the clinical differences in the patients cared for by these services could have led to our findings. Although the clinical significance of the differences in patient demographics were small, patients seen on the hospitalist service were more likely to be older white males, with a slightly longer LOS, greater comorbidities, and more hospitalizations in the previous year than those seen on the general medicine teaching service. Additionally, our hospitalist service frequently cares for highly specific subpopulations (ie, liver and renal transplant patients, and oncology patients), which could have influenced our results. For example, transplant patients who may be very grateful for their second chance, are preferentially admitted to the hospitalist service, which could have biased our results in favor of hospitalists.[32] Unfortunately, we were unable to control for all such factors.

Although we hope that multivariable analysis can adjust for many of these differences, we are not able to account for possible unmeasured confounders such as time of day of admission, health literacy, personality differences, physician turnover, or nursing and other ancillary care that could contribute to these findings. In addition to its observational study design, our study has several other limitations. First, our study was performed at a single institution, thus limiting its generalizability. Second, as a retrospective study based on observational data, no definitive conclusions regarding causality can be made. Third, although our response rate was low, it is comparable to other studies that have examined underserved populations.[33, 34] Fourth, because our survey was performed 30 days after hospitalization, this may impart imprecision on our outcomes measures. Finally, we were not able to mitigate selection bias through imputation for missing data .

All together, given the small absolute differences between the groups in patients' ratings of their overall care compared to large differences in possible confounders, these findings call for further exploration into the significance and possible mechanisms of these outcomes. Our study raises the potential possibility that the structural component of a care team may play a role in overall patient satisfaction. If this is the case, future studies of team structure could help inform how best to optimize this component for the patient experience. On the other hand, if process differences are to explain our findings, it is important to distill the types of processes hospitalists are using to improve the patient experience and potentially export this to resident services.

Finally, if similar results were found in other institutions, these findings could have implications on how hospitals respond to new payment models that are linked to patient‐experience measures. For example, the Hospital Value‐Based Purchasing Program currently links the Centers for Medicare and Medicaid Services payments to a set of quality measures that consist of (1) clinical processes of care (70%) and (2) the patient experience (30%).[1] Given this linkage, any small changes in the domain of patient satisfaction could have large payment implications on a national level.

CONCLUSION

In summary, in this large‐scale multiyear study, patients cared for by a nonteaching hospitalist service reported greater satisfaction with their overall care than patients cared for by a general medicine teaching service. This difference could be mediated by the structural differences between these 2 services. As hospitals seek to optimize patient experiences in an era where reimbursement models are now being linked to patient‐experience measures, future work should focus on further understanding the mechanisms for these findings.