Implementation of a Voluntary Hospitalist Service at a Community Teaching Hospital: Improved Clinical Efficiency and Patient Outcomes

Context Many studies suggest that hospitalists reduce average length of stay and costs but have little or no effect on patient survival. Contribution This 2-year cohort study from a community-based urban teaching hospital found that patients cared for by faculty hospitalists rather than community physicians had shorter lengths of stay, lower costs, and better in-hospital and 1- and 2-month survival rates. Implications Length of stay and cost benefits were apparent only in year 2 of the study, which suggests that experience is an important aspect of successful care by hospitalists. Cautions The study was retrospective, was done in a single site, and involved only five hospitalists. The Editors The organization of inpatient services has been transformed with the development of the hospitalist (1). Traditionally, primary care physicians have cared for their own inpatients. In the hospitalist model, a hospitalist becomes the patient's attending physician during hospitalization and the outpatient physician resumes supervision of the patient after discharge (2). Several studies have demonstrated improved clinical efficiency in the hospitalist model, but these studies have focused largely on academic centers or health maintenance organizations, or have not used concurrent controls or reported longer periods of follow-up (3-7). One published study examining a hospitalist system at a community-based teaching hospital suggested improvement in clinical efficiency and a reduction in readmissions (8). However, analytic limitations open these findings to many interpretations. To examine the effects of implementation of a hospitalist service on resource utilization and patient outcomes over time, we studied 5308 consecutive patients admitted to an urban community teaching hospital in San Francisco, California. Methods Study Site Mount Zion Hospital (San Francisco, California) was a 280-bed community-based teaching hospital affiliated with University of California, San Francisco. Mount Zion's inpatient facilities were closed in November 1999 because of financial pressures. During the year before closure, all physicians were aware of the hospital's financial difficulties, but no individual or group was made a focus of efforts to improve clinical efficiency. Discussions about possible closure began 1 month after this study ended, and the hospital closed 5 months later. Medical patients at Mount Zion Hospital were admitted to one of four medical teams composed of a resident, one to two interns, and zero to three medical students. Mount Zion medical teams cared for common inpatient diagnoses, as well as specialty-associated diagnoses such as cancer, acute myocardial infarction, and cerebrovascular accidents. Housestaff wrote all orders and provided 24-hour coverage to inpatients. Each team had a ward attending physician who before 1 July 1997 was a full-time faculty member serving in this role for 1 month each year. Community-based physicians remained the physician of record for most patients and worked with house officers in the care of their hospitalized patients. On 1 July 1997, Mount Zion implemented a voluntary hospitalist service. Hospitalists, who were University of California, San Francisco, faculty based at Mount Zion, served as ward attendings 6 to 8 months per year and spent their remaining time in ambulatory practice or teaching. Hospitalists cared for patients without primary physicians, patients with faculty or house officer primary care physicians, and patients whose community-based physician chose to use the hospitalist service. Rotating nonhospitalist faculty continued to provide some inpatient care after implementation of the hospitalist service. Patients were admitted to rotating faculty according to the same criteria used for hospitalist services. There were no differences in other inpatient care systems available to community, rotating, or hospitalist physicians (for example, level of housestaff coverage, computer systems, case managers, social workers, or nursing staff). Patients Between 1 July 1997 and 30 June 1999, 5907 patients 18 years of age or older were admitted to the medical service at Mount Zion Hospital. We excluded patients who were admitted for chemotherapy or as part of a research protocol (n = 167) and those for whom some data on primary diagnosis were missing (n = 30). The resulting cohort was composed of 5710 patients, of whom 3693 (65%) were cared for by community-based physicians, 1615 (28%) were cared for by hospitalists, and 402 (7%) were cared for by rotating faculty. Data Management At Mount Zion Hospital, data were drawn from TSI (Transition Systems, Inc., Boston, Massachusetts) administrative databases, a cost-accounting system that collects data abstracted from patient charts at discharge. These databases contain information on sociodemographic characteristics, principal diagnosis (in the form of International Classification of Diseases, 9th revision, codes), diagnosis-related group, length of stay, costs, number of consultations, and whether the patient was in an intensive care unit during hospitalization. Data were manually screened for validity of physician designation as hospitalist or community physician by using previously published definitions of hospitalist physician characteristics (1, 2). Discharge summaries of patients who died during hospitalization were examined to validate deaths. An additional 200 discharge summaries of randomly selected patients discharged alive were also reviewed, revealing no errors. Information regarding physician characteristics and board certification was obtained from hospital credentialing databases. Patient survival to points in time after hospitalization was determined by using data from the California State Death Index (for patients admitted before 1 January 1999) and Social Security death indexes (for patients admitted on or after 1 January 1999 and for those who did not reside in California). Statistical Analysis To satisfy normality requirements and stabilize variance of residuals, we explored two methods of transforming skewed data on cost and length of stay: logarithmic conversion and truncation at the mean + 3 SDs. Since both techniques yielded similar results, we chose to present results by using truncation, as has been done in previous studies of inpatient costs and utilization (4, 9-11). All costs were adjusted to 1999 U.S. dollars by using an annual inflation rate of 3% (4). Primary analyses compared 5308 patients cared for by community or hospital-based physicians; we excluded the few patients cared for by rotating physicians from core analyses. This method was chosen to maximize our ability to discern differences in rare outcomes (such as death or readmission), to determine trends in frequent outcomes (such as length of stay), and to maintain focus on our primary question: hospitalist-directed versus community physiciandirected inpatient care. For bivariable comparisons, we used the Fisher exact test or the Wilcoxon rank-sum test. Unadjusted survival rates were estimated by using KaplanMeier product-limit methods. We then used multivariable models to determine the independent effect of hospitalist care on patient outcomes. Using automated forward and stepwise selection techniques along with manually entered variables, we fit multivariable linear regression models to determine the independent association of hospitalist care with length of stay and costs. Items were selected on the basis of the statistical significance of their association with the outcome or on observed confounding with other independent variables, or to maintain face validity of the model. Similar methods were used in fitting logistic models of readmission; use of consultations; and Cox proportional-hazards models of survival to discharge, 30 days, and 60 days. All analyses were performed by using SAS software, version 8.0 for Windows (SAS Institute, Inc., Cary, North Carolina). Multivariable models contained adjustment for patient age, sex, ethnicity, insurance type, source of admission (for example, emergency department), site of discharge, whether a cardiovascular procedure was performed during hospitalization, whether the patient received care in an intensive care unit during hospitalization, and case-mix measures. For case-mix measures, specific diagnoses were defined by using International Classification of Diseases, 9th revision, codes for pneumonia, asthma, congestive heart failure, acute myocardial infarction, angina, unstable angina, chest pain, cancer, gastrointestinal hemorrhage, HIV infection, and cerebrovascular accident. Models also contained a variable indexed to admission date to adjust for secular trends. Trends in adjusted outcomes were tested by using variables dummy-coded to indicate service and year of admission. Because patients were not randomly assigned to hospitalists or community physicians, we performed secondary analyses using a propensity score (12, 13). In our analyses, the propensity score represents the likelihood that any given patient would be admitted to a hospitalist attending physician. The propensity score was calculated in a logistic regression model with attending designation [that is, hospitalist vs. community physician] as the dependent variable. The model contained all covariates in core models, as well as variables found to contribute to nonrandom allocation of patients to specialty care at a P value less than or equal to 0.20. The propensity score was then used in analyses of cost, length of stay, and mortality in two ways: 1) multivariable analyses stratified within tertiles of propensity score and 2) multivariable analyses using the score as a continuous adjustment variable. Results Physician Characteristics One hundred thirteen community physicians, 20 rotating physicians, and 5 hospitalist physicians admitted patients to Mount Zion Hospital during the 2 years of this study. The mean age was 34 years for hospital