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

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 o...

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Autores principales: Baas, Stef, Dijkstra, Sander, Braaksma, Aleida, van Rooij, Plom, Snijders, Fieke J., Tiemessen, Lars, Boucherie, Richard J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer US 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7993447/
https://www.ncbi.nlm.nih.gov/pubmed/33768389
http://dx.doi.org/10.1007/s10729-021-09553-5
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author Baas, Stef
Dijkstra, Sander
Braaksma, Aleida
van Rooij, Plom
Snijders, Fieke J.
Tiemessen, Lars
Boucherie, Richard J.
author_facet Baas, Stef
Dijkstra, Sander
Braaksma, Aleida
van Rooij, Plom
Snijders, Fieke J.
Tiemessen, Lars
Boucherie, Richard J.
author_sort Baas, Stef
collection PubMed
description 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.
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spelling pubmed-79934472021-03-26 Real-time forecasting of COVID-19 bed occupancy in wards and Intensive Care Units Baas, Stef Dijkstra, Sander Braaksma, Aleida van Rooij, Plom Snijders, Fieke J. Tiemessen, Lars Boucherie, Richard J. Health Care Manag Sci Article 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. Springer US 2021-03-25 2021 /pmc/articles/PMC7993447/ /pubmed/33768389 http://dx.doi.org/10.1007/s10729-021-09553-5 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Baas, Stef
Dijkstra, Sander
Braaksma, Aleida
van Rooij, Plom
Snijders, Fieke J.
Tiemessen, Lars
Boucherie, Richard J.
Real-time forecasting of COVID-19 bed occupancy in wards and Intensive Care Units
title Real-time forecasting of COVID-19 bed occupancy in wards and Intensive Care Units
title_full Real-time forecasting of COVID-19 bed occupancy in wards and Intensive Care Units
title_fullStr Real-time forecasting of COVID-19 bed occupancy in wards and Intensive Care Units
title_full_unstemmed Real-time forecasting of COVID-19 bed occupancy in wards and Intensive Care Units
title_short Real-time forecasting of COVID-19 bed occupancy in wards and Intensive Care Units
title_sort real-time forecasting of covid-19 bed occupancy in wards and intensive care units
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7993447/
https://www.ncbi.nlm.nih.gov/pubmed/33768389
http://dx.doi.org/10.1007/s10729-021-09553-5
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