Simulating emergency patient flow during the COVID-19 pandemic

IF 1.3 4区 工程技术 Q4 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Journal of Simulation Pub Date : 2021-12-30 DOI:10.1080/17477778.2021.2015259
Thomas Reiten Bovim, Anders N. Gullhav, H. Andersson, Jostien Dale, Kjetil Karlsen
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引用次数: 10

Abstract

ABSTRACT The work presented in this paper is based on two projects that were conducted at St. Olavs Hospital (Norway) when preparing for the COVID-19 pandemic. Three discrete event simulation models are provided to evaluate the resource requirements during the peak of the pandemic. First, we estimate the number of beds needed in the emergency department (ED). In the second model, we estimate the number of ambulances required to maintain prepandemic response times for emergency patients. The third model is a coupling of the two former models, and it is used to study the effects of ED boarding time for COVID-19 patients. The resource needs are analysed under different COVID-19 testing policies. A strict testing policy increases the bed requirements in the ED, while it has the opposite effect for ambulances. Two distinct mechanisms causing boarding time are found. The effects from boarding time are most prominent during night and weekends.
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模拟新冠肺炎大流行期间的紧急患者流动
本文介绍的工作基于圣奥拉夫斯医院(挪威)在准备应对COVID-19大流行时进行的两个项目。提供了三个离散事件模拟模型,以评估大流行高峰期间的资源需求。首先,我们估计急诊科(ED)所需的床位数量。在第二个模型中,我们估计维持大流行前对急诊病人的反应时间所需的救护车数量。第三个模型是前两个模型的耦合,用于研究ED登机时间对COVID-19患者的影响。分析了不同COVID-19检测策略下的资源需求。严格的测试政策增加了急诊科的床位需求,而对救护车却产生了相反的效果。发现了导致登机时间的两种不同机制。登机时间的影响在夜间和周末最为突出。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Journal of Simulation
Journal of Simulation COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS-OPERATIONS RESEARCH & MANAGEMENT SCIENCE
CiteScore
5.70
自引率
16.00%
发文量
42
期刊介绍: Journal of Simulation (JOS) aims to publish both articles and technical notes from researchers and practitioners active in the field of simulation. In JOS, the field of simulation includes the techniques, tools, methods and technologies of the application and the use of discrete-event simulation, agent-based modelling and system dynamics.
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