Locally Informed Simulation to Predict Hospital Capacity Needs During the COVID-19 Pandemic
Locally Informed Simulation to Predict Hospital Capacity Needs During the COVID-19 Pandemic
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DOI：
10.7326/m20-1260
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发表时间：
2020-07-07
影响因子：
39.2
通讯作者：
Halpern, Scott D.
中科院分区：
文献类型：
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作者：
Weissman, Gary E.;Crane-Droesch, Andrew;Halpern, Scott D.
背景：2019冠状病毒病（COVID-19）大流行挑战了医院领导在临床操作和资源分配方面做出具有时间敏感性的关键决策。目的：估计临床需求激增的时间以及当地covid -19引起的医院容量紧张的最佳和最坏情况，从而为临床操作和人员需求提供信息，并确定医院容量何时饱和。设计：具有1天周期的易感、感染、移除（SIR）模型的蒙特卡罗模拟实例化。背景：一个学术卫生系统中的3家医院。病人：所有居住在大费城地区的人。测量方法：COVID-19医院影响模型（CHIME） （http://penn-chime.phl）。使用SIR模型来估计从2020年3月23日到可能超过医院容量的时间，以及激增的强度，包括重症监护病房（ICU）床位和呼吸机。结果：仅以COVID-19患者为例，CHIME估计需求将在31至53天后超过现有医院容量。在COVID-19患者数量激增的最佳和最坏情况下，三家医院所需的病床总容量将达到3131至12650张，其中包括338至1608张ICU床位和118至599台呼吸机。局限性：模型参数是直接获取的，或者来自不同人群和实践环境的公开数据以及卫生系统的历史数据。CHIME没有纳入更多的过渡状态来模拟感染严重程度，没有纳入更多的社会网络来模拟传播动态，也没有纳入更多的地理信息来解释人类互动的空间模式。结论：该建模工具公开可用，专为医院业务负责人设计，可以在大流行的早期为能力紧张的准备工作提供信息。
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-19induced 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.