Mixing It Up: Operational Impact of Hospitalist Caseload and Case-Mix

Abstract

Hospitalists are medical doctors that specialize in the care of hospitalized patients, a role that until recently belonged to primary care physicians. We develop an operational model of hospitalist-patient interactions with rounding and responding service modes, optimizing hospitalist caseload and case-mix to achieve the maximal reduction in patient length of stay (LOS). We show that hospitalists are effective at reducing LOS for patients with complex conditions, corroborating intuitive reasoning. However, the optimal hospitalist case-mix also includes “simple” patients with few interventions and short LOS, as they can effectively reduce discharge delays. This actionable insight is particularly salient for small community hospitals with simple, short-stay patients, where hospitalists may be undervalued due to the prevailing belief that they are primarily effective for complex patients. We conduct a comparative case study of a small community hospital and a large academic hospital, drawing a stark contrast between the two in terms of ideal caseload and patient coverage. Despite the fact that the academic hospital treats higher complexity patients, hospitalists at the community hospital should actually have a lower caseload than hospitalists at the academic hospital due to shorter stays in the community hospital. We find that both hospitals are understaffed but for different reasons: the academic hospital needs to staff more hospitalists to reduce the current caseload of its hospitalists, whereas the community hospital needs to staff more hospitalists to expand its hospitalist coverage to more patients. We estimate that these hospitals can save on average $1.5 million annually by implementing the optimal staffing policies. This paper was accepted by Stefan Scholtes, healthcare management. Funding: This work was supported by a PSC-CUNY Award, jointly funded by The Professional Staff Congress and The City University of New York. Supplemental Material: The e-companion and data files are available at https://doi.org/10.1287/mnsc.2022.4342 .