Methods
Setting and Population
Fraser Health Authority is 1 of 5 regional health authorities in British Columbia that emerged in 2001.23,24 It operates a network of hospitalist programs in 10 of its 12 acute care hospitals. In addition to hospitalists, there are a variable number of “traditional” physician providers who continue to act as MRPs. These include community-based FPs who continue to see their own patients in the hospital, either as part of a solo-practice model or a clinic-based call group. There are also a number of general internists and other subspecialists who accept MRP roles for general medicine patients who may present with higher-acuity conditions. As a result, patients requiring hospitalization due to nonsurgical or noncritical care conditions at each Fraser Health hospital may be cared for by a physician belonging to 1 of 3 groups, depending on local circumstances: an FP, a hospitalist, or an internist.
Inclusion and Exclusion Criteria
In order to evaluate comparative outcomes associated with hospitalist care, we included all patients admitted to a physician in each of the 3 provider groups between April 1, 2012, and March 31, 2018. We chose this time period for 2 reasons: first, we wanted to ensure comparability over an extended period of time, given the methodological changes implemented in 2009 by the Canadian Institute for Health Information (CIHI), the federal organization in the country responsible for setting standards for health care measures.25 Second, previous internal reviews had suggested that data quality prior to this year was inconsistent. We only considered hospitalizations where patients were admitted to and discharged by the same service, and excluded 2 acute care facilities and 1 free-standing rehabilitation facility without a hospitalist service during this period. We also excluded patients who resided in a location beyond the geographic catchment area of Fraser Health. Further details about data collection are outlined in the Appendix.
Measures
We used the framework developed by White and Glazier26 to inform the selection of our outcome measures, as well as relevant variables that may impact them. This framework proposes that the design of the inpatient care model (structures and processes of care) directly affects care outcomes. The model also proposes that patient and provider attributes can modulate this relationship, and suggests that a comprehensive evaluation of hospitalist performance needs to take these factors into account. We identified average total LOS, 30-day readmission rate, in-hospital mortality, and hospital standardized mortality ratio (HSMR)27 as primary outcome measures. HSMR is defined as actual over expected mortality and is measured by CIHI through a formula that takes into account patient illness attributes (eg, the most responsible diagnosis, comorbidity levels) and baseline population mortality rates.27 We chose these measures because they are clinically relevant and easy to obtain and have been utilized in previous similar studies in Canada and the United States.18-21,26
Statistical Analysis
Baseline demographic and clinical differences in patient outcomes were examined using independent t-tests or chi-square tests. Furthermore, baseline differences based on provider groups were explored using analysis of variance or chi-square tests. Multiple logistic regression analyses were completed to determine the relationship between provider groups and readmission and mortality, while the relationship between provider groups and hospital LOS was determined with generalized linear regression (using gamma distribution and a log link). Gamma distribution with a log link analysis is appropriate with outcome measures that are positively skewed (eg, hospital LOS). It assumes that data are sampled from an exponential family of distributions, thus mimicking a log-normal distribution, and minimizes estimation bias and standard errors. These analyses were completed while controlling for the effects of age, gender, and other potential confounding factors.
We initially attempted to control for case mix by incorporating case-mix groups (CMGs) in our multivariate analysis. However, we identified 475 CMGs with at least 1 patient in our study population. We then explored the inclusion of major clinical categories (MCCs) that broadly group CMGs into various higher order/organ-system level categories (eg, diseases of the respiratory system); however, we could not aggregate them into sufficiently homogenous groups to be entered into regression models. Instead, we conducted subgroup analyses on patients in our study population who were hospitalized with 1 of the following 3 CMGs: chronic obstructive pulmonary disease (COPD, n = 11,404 patients), congestive heart failure without coronary angiography (CHF, n = 7680), and pneumonia (itself an aggregate of 3 separate CMGs: aspiration pneumonia, bacterial pneumonia, viral/unspecified pneumonia, n = 11,155). We chose these CMGs as they are among the top 8 presentations for all 3 provider groups.
For all outcome measures, we excluded atypical patients (defined by CIHI as those with atypically long stays) and patients who had been transferred between facilities. For the readmission analysis, we also excluded patients who died in the hospital (Appendix A). Data analyses were completed in IBM SPSS, version 21. For all analyses, significance was determined using 2-tailed test and alpha < 0.05.
Ethics
The Fraser Health Department of Research and Evaluation reviewed this project to determine need for formal Ethics Review Board review, and granted an exemption based on institutional guidelines for program evaluations.