Real-time forecasting of COVID-19 bed occupancy in wards and Intensive Care Units

被引：32

作者：

Baas, Stef ^{[1
]}

Dijkstra, Sander ^{[1
]}

Braaksma, Aleida ^{[1
]}

van Rooij, Plom ^{[2
]}

Snijders, Fieke J. ^{[3
]}

Tiemessen, Lars ^{[4
]}

Boucherie, Richard J. ^{[1
]}

机构：

[1] Univ Twente, Ctr Healthcare Operat Improvement & Res CHOIR, Enschede, Netherlands

[2] Elisabeth TweeSteden Ziekenhuis, Tilburg, Netherlands

[3] Leiden Univ, Med Ctr, Leiden, Netherlands

[4] Rijnstate, Arnhem, Netherlands

来源：

HEALTH CARE MANAGEMENT SCIENCE | 2021年 / 24卷 / 02期

关键词：

COVID-19; Forecast; Bed occupancy; Network of infinite server queues; Richards’ curve; Kaplan-Meier estimator; HOSPITAL WARDS;

D O I：

10.1007/s10729-021-09553-5

中图分类号：

R19 [保健组织与事业（卫生事业管理）];

学科分类号：

摘要：

This paper presents a mathematical model that provides a real-time forecast of the number of COVID-19 patients admitted to the ward and the Intensive Care Unit (ICU) of a hospital based on the predicted inflow of patients, their Length of Stay (LoS) in both the ward and the ICU as well as transfer of patients between the ward and the ICU. The data required for this forecast is obtained directly from the hospital's data warehouse. The resulting algorithm is tested on data from the first COVID-19 peak in the Netherlands, showing that the forecast is very accurate. The forecast may be visualised in real-time in the hospital's control centre and is used in several Dutch hospitals during the second COVID-19 peak.

引用

页码：402 / 419

页数：18

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