Background: Geographic cohorting is a hospital admission structure in which every patient on a given physician team is admitted to a dedicated hospital unit. Little is known about the long-term impact of this admission structure on patient outcomes and resident satisfaction.

Objective: To evaluate the effect of geographic cohorting on patient outcomes and resident satisfaction among inpatient internal medicine teaching services within an academic hospital.

Design And Intervention: We conducted an interrupted time series analysis examining patient outcomes before and after the transition to geographic cohorting of our 3 inpatient teaching services within a 520-bed academic hospital in November 2017. The study observation period spanned from January 2017 to October 2018, allowing for a 2-month run-in period (November-December 2017).

Participants: We included patients discharged from the inpatient teaching teams during the study period. We excluded patients admitted to the ICU and observation admissions.

Main Measures: Primary outcome was 6-month mortality adjusted for patient age, sex, race, insurance status, and Charlson Comorbidity Index (CCI) analyzed using a linear mixed effects model. Secondary outcomes included hospital length of stay (LOS), 7-day and 30-day readmission rate, Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) scores, and resident evaluations of the rotation.

Key Results: During the observation period, 1720 patients (mean age 64, 53% female, 56% white, 62% Medicare-insured, mean CCI 1.57) were eligible for inclusion in the final adjusted model. We did not detect a significant change in 6-month mortality, LOS, and 7-day or 30-day readmission rates. HCAHPS scores remained unchanged (77 to 80% top box, P = 0.19), while resident evaluations of the rotation significantly improved (mean overall score 3.7 to 4.0, P = 0.03).

Conclusions: Geographic cohorting was associated with increased resident satisfaction while achieving comparable patient outcomes to those of traditional hospital admitting models.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9551005PMC
http://dx.doi.org/10.1007/s11606-021-07387-zDOI Listing

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