Inpatient Capacity Management during COVID-19 Pandemic: The Yale New Haven Hospital Capacity Expansion Experience

Fogerty, Robert L.; Aniskiewicz, Michael; Hedges, Todd; Ryan, Sean; Brien, Piper; Beley, Peggy; Tangredi, Marc; Mitchell, Marci R.; d’Atri, Hillary; Jansen, Laura; Williams, Ena; LoRusso, Francine; Sevilla, Mark; Menillo, Jennifer; Doyle, D. John; Parrott, Heather; Sheehan, Susan; Martinello, Richard A.; Holmes, Michael W.

doi:10.1080/00185868.2021.1926383

Cited by 1 publication

(2 citation statements)

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Section: Discussionmentioning

confidence: 98%

“…This study adds to the emerging literature on tangible operational policies and interventions employed by hospitals during COVID surges to address major capacity and staffing strain. [12][13][14][15][16][17][18] Several prior studies examined the impact of procedural volume reduction on hospital capacity and patient outcomes. 5,13 Our findings complement these studies by demonstrating how redistribution of inpatients can help leverage the capacity generated by procedural reduction and reduce strain on GMS teams.…”

Section: Discussionmentioning

confidence: 99%

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Impact of a hospital policy to redistribute admission flow across clinical services for capacity relief during COVID‐19 surges

Safavi

Copenhaver

Moore

et al. 2023

Journal of Hospital Medicine

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Background: Increased hospital admissions due to COVID-19 place a disproportionate strain on inpatient general medicine service (GMS) capacity compared to other services.Objective: To study the impact on capacity and safety of a hospital-wide policy to redistribute admissions from GMS to non-GMS based on admitting diagnosis during surge periods. Design, Setting, and Participants: Retrospective case-controlled study at a large teaching hospital. The intervention included adult patients admitted to general care wards during two surge periods (January-February 2021 and 2022) whose admission diagnosis was impacted by the policy. The control cohort included admissions during a matched number of days preceding the intervention. Main Outcomes and Measures: Capacity measures included average daily admissions and hospital census occupied on GMS. Safety measures included length of stay (LOS) and adverse outcomes (death, rapid response, floor-to-intensive care unit transfer, and 30-day readmission).Results: In the control cohort, there were 365 encounters with 299 (81.9%) GMS admissions and 66 (18.1%) non-GMS versus the intervention with 384 encounters, including 94 (24.5%) GMS admissions and 290 (75.5%) non-GMS (p < .001). The average GMS census decreased from 17.9 and 21.5 during control periods to 5.5 and 8.5 during intervention periods. An interrupted time series analysis confirmed a decrease in GMS daily admissions (p < .001) and average daily hospital census (p = .014; p < .001). There were no significant differences in LOS (5.9 vs. 5.9 days, p = .059) or adverse outcomes (53, 14.5% vs. 63, 16.4%; p = .482). Conclusion:Admission redistribution based on diagnosis is a safe lever to reduce capacity strain on GMS during COVID-19 surges.

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Section: Discussionmentioning

confidence: 98%