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Resource planning strategies for healthcare systems during a pandemic
We study resource planning strategies, including the integrated healthcare resources’ allocation and sharing as well as patients’ transfer, to improve the response of health systems to massive increases in demand during epidemics and pandemics. Our study considers various types of patients and resou...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Author(s). Published by Elsevier B.V.
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8759806/ https://www.ncbi.nlm.nih.gov/pubmed/35068665 http://dx.doi.org/10.1016/j.ejor.2022.01.023 |
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author | Fattahi, Mohammad Keyvanshokooh, Esmaeil Kannan, Devika Govindan, Kannan |
author_facet | Fattahi, Mohammad Keyvanshokooh, Esmaeil Kannan, Devika Govindan, Kannan |
author_sort | Fattahi, Mohammad |
collection | PubMed |
description | We study resource planning strategies, including the integrated healthcare resources’ allocation and sharing as well as patients’ transfer, to improve the response of health systems to massive increases in demand during epidemics and pandemics. Our study considers various types of patients and resources to provide access to patient care with minimum capacity extension. Adding new resources takes time that most patients don't have during pandemics. The number of patients requiring scarce healthcare resources is uncertain and dependent on the speed of the pandemic's transmission through a region. We develop a multi-stage stochastic program to optimize various strategies for planning limited and necessary healthcare resources. We simulate uncertain parameters by deploying an agent-based continuous-time stochastic model, and then capture the uncertainty by a forward scenario tree construction approach. Finally, we propose a data-driven rolling horizon procedure to facilitate decision-making in real-time, which mitigates some critical limitations of stochastic programming approaches and makes the resulting strategies implementable in practice. We use two different case studies related to COVID-19 to examine our optimization and simulation tools by extensive computational results. The results highlight these strategies can significantly improve patient access to care during pandemics; their significance will vary under different situations. Our methodology is not limited to the presented setting and can be employed in other service industries where urgent access matters. |
format | Online Article Text |
id | pubmed-8759806 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | The Author(s). Published by Elsevier B.V. |
record_format | MEDLINE/PubMed |
spelling | pubmed-87598062022-01-18 Resource planning strategies for healthcare systems during a pandemic Fattahi, Mohammad Keyvanshokooh, Esmaeil Kannan, Devika Govindan, Kannan Eur J Oper Res Article We study resource planning strategies, including the integrated healthcare resources’ allocation and sharing as well as patients’ transfer, to improve the response of health systems to massive increases in demand during epidemics and pandemics. Our study considers various types of patients and resources to provide access to patient care with minimum capacity extension. Adding new resources takes time that most patients don't have during pandemics. The number of patients requiring scarce healthcare resources is uncertain and dependent on the speed of the pandemic's transmission through a region. We develop a multi-stage stochastic program to optimize various strategies for planning limited and necessary healthcare resources. We simulate uncertain parameters by deploying an agent-based continuous-time stochastic model, and then capture the uncertainty by a forward scenario tree construction approach. Finally, we propose a data-driven rolling horizon procedure to facilitate decision-making in real-time, which mitigates some critical limitations of stochastic programming approaches and makes the resulting strategies implementable in practice. We use two different case studies related to COVID-19 to examine our optimization and simulation tools by extensive computational results. The results highlight these strategies can significantly improve patient access to care during pandemics; their significance will vary under different situations. Our methodology is not limited to the presented setting and can be employed in other service industries where urgent access matters. The Author(s). Published by Elsevier B.V. 2023-01-01 2022-01-15 /pmc/articles/PMC8759806/ /pubmed/35068665 http://dx.doi.org/10.1016/j.ejor.2022.01.023 Text en © 2022 The Author(s) Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. |
spellingShingle | Article Fattahi, Mohammad Keyvanshokooh, Esmaeil Kannan, Devika Govindan, Kannan Resource planning strategies for healthcare systems during a pandemic |
title | Resource planning strategies for healthcare systems during a pandemic |
title_full | Resource planning strategies for healthcare systems during a pandemic |
title_fullStr | Resource planning strategies for healthcare systems during a pandemic |
title_full_unstemmed | Resource planning strategies for healthcare systems during a pandemic |
title_short | Resource planning strategies for healthcare systems during a pandemic |
title_sort | resource planning strategies for healthcare systems during a pandemic |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8759806/ https://www.ncbi.nlm.nih.gov/pubmed/35068665 http://dx.doi.org/10.1016/j.ejor.2022.01.023 |
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