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Weissman GE, Crane-Droesch A, Chivers C, Luong T, Hanish A, Levy MZ, Lubken J, Becker M, Draugelis ME, Anesi GL, Brennan PJ, Christie JD, Hanson CW, Mikkelsen ME, Halpern SD. Locally Informed Simulation to Predict Hospital Capacity Needs During the COVID-19 Pandemic. Ann Intern Med 2020; 173:21-28. [PMID: 32259197 PMCID: PMC7153364 DOI: 10.7326/m20-1260] [Citation(s) in RCA: 157] [Impact Index Per Article: 39.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/08/2023] Open
Abstract
BACKGROUND The coronavirus disease 2019 (COVID-19) pandemic challenges hospital leaders to make time-sensitive, critical decisions about clinical operations and resource allocations. OBJECTIVE To estimate the timing of surges in clinical demand and the best- and worst-case scenarios of local COVID-19-induced strain on hospital capacity, and thus inform clinical operations and staffing demands and identify when hospital capacity would be saturated. DESIGN Monte Carlo simulation instantiation of a susceptible, infected, removed (SIR) model with a 1-day cycle. SETTING 3 hospitals in an academic health system. PATIENTS All people living in the greater Philadelphia region. MEASUREMENTS The COVID-19 Hospital Impact Model (CHIME) (http://penn-chime.phl.io) SIR model was used to estimate the time from 23 March 2020 until hospital capacity would probably be exceeded, and the intensity of the surge, including for intensive care unit (ICU) beds and ventilators. RESULTS Using patients with COVID-19 alone, CHIME estimated that it would be 31 to 53 days before demand exceeds existing hospital capacity. In best- and worst-case scenarios of surges in the number of patients with COVID-19, the needed total capacity for hospital beds would reach 3131 to 12 650 across the 3 hospitals, including 338 to 1608 ICU beds and 118 to 599 ventilators. LIMITATIONS Model parameters were taken directly or derived from published data across heterogeneous populations and practice environments and from the health system's historical data. CHIME does not incorporate more transition states to model infection severity, social networks to model transmission dynamics, or geographic information to account for spatial patterns of human interaction. CONCLUSION Publicly available and designed for hospital operations leaders, this modeling tool can inform preparations for capacity strain during the early days of a pandemic. PRIMARY FUNDING SOURCE University of Pennsylvania Health System and the Palliative and Advanced Illness Research Center.
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Affiliation(s)
- Gary E Weissman
- University of Pennsylvania, Philadelphia, Pennsylvania (G.E.W., M.Z.L., G.L.A., P.J.B., J.D.C., C.W.H., M.E.M., S.D.H.)
| | - Andrew Crane-Droesch
- University of Pennsylvania and Penn Medicine Predictive Healthcare, Philadelphia, Pennsylvania (A.C., M.E.D.)
| | - Corey Chivers
- Penn Medicine Predictive Healthcare, Philadelphia, Pennsylvania (C.C., T.L., A.H., J.L., M.B.)
| | - ThaiBinh Luong
- Penn Medicine Predictive Healthcare, Philadelphia, Pennsylvania (C.C., T.L., A.H., J.L., M.B.)
| | - Asaf Hanish
- Penn Medicine Predictive Healthcare, Philadelphia, Pennsylvania (C.C., T.L., A.H., J.L., M.B.)
| | - Michael Z Levy
- University of Pennsylvania, Philadelphia, Pennsylvania (G.E.W., M.Z.L., G.L.A., P.J.B., J.D.C., C.W.H., M.E.M., S.D.H.)
| | - Jason Lubken
- Penn Medicine Predictive Healthcare, Philadelphia, Pennsylvania (C.C., T.L., A.H., J.L., M.B.)
| | - Michael Becker
- Penn Medicine Predictive Healthcare, Philadelphia, Pennsylvania (C.C., T.L., A.H., J.L., M.B.)
| | - Michael E Draugelis
- University of Pennsylvania and Penn Medicine Predictive Healthcare, Philadelphia, Pennsylvania (A.C., M.E.D.)
| | - George L Anesi
- University of Pennsylvania, Philadelphia, Pennsylvania (G.E.W., M.Z.L., G.L.A., P.J.B., J.D.C., C.W.H., M.E.M., S.D.H.)
| | - Patrick J Brennan
- University of Pennsylvania, Philadelphia, Pennsylvania (G.E.W., M.Z.L., G.L.A., P.J.B., J.D.C., C.W.H., M.E.M., S.D.H.)
| | - Jason D Christie
- University of Pennsylvania, Philadelphia, Pennsylvania (G.E.W., M.Z.L., G.L.A., P.J.B., J.D.C., C.W.H., M.E.M., S.D.H.)
| | - C William Hanson
- University of Pennsylvania, Philadelphia, Pennsylvania (G.E.W., M.Z.L., G.L.A., P.J.B., J.D.C., C.W.H., M.E.M., S.D.H.)
| | - Mark E Mikkelsen
- University of Pennsylvania, Philadelphia, Pennsylvania (G.E.W., M.Z.L., G.L.A., P.J.B., J.D.C., C.W.H., M.E.M., S.D.H.)
| | - Scott D Halpern
- University of Pennsylvania, Philadelphia, Pennsylvania (G.E.W., M.Z.L., G.L.A., P.J.B., J.D.C., C.W.H., M.E.M., S.D.H.)
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