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CPAS: the UK’s national machine learning-based hospital capacity planning system for COVID-19
The coronavirus disease 2019 (COVID-19) global pandemic poses the threat of overwhelming healthcare systems with unprecedented demands for intensive care resources. Managing these demands cannot be effectively conducted without a nationwide collective effort that relies on data to forecast hospital...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer US
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7685302/ https://www.ncbi.nlm.nih.gov/pubmed/33250568 http://dx.doi.org/10.1007/s10994-020-05921-4 |
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author | Qian, Zhaozhi Alaa, Ahmed M. van der Schaar, Mihaela |
author_facet | Qian, Zhaozhi Alaa, Ahmed M. van der Schaar, Mihaela |
author_sort | Qian, Zhaozhi |
collection | PubMed |
description | The coronavirus disease 2019 (COVID-19) global pandemic poses the threat of overwhelming healthcare systems with unprecedented demands for intensive care resources. Managing these demands cannot be effectively conducted without a nationwide collective effort that relies on data to forecast hospital demands on the national, regional, hospital and individual levels. To this end, we developed the COVID-19 Capacity Planning and Analysis System (CPAS)—a machine learning-based system for hospital resource planning that we have successfully deployed at individual hospitals and across regions in the UK in coordination with NHS Digital. In this paper, we discuss the main challenges of deploying a machine learning-based decision support system at national scale, and explain how CPAS addresses these challenges by (1) defining the appropriate learning problem, (2) combining bottom-up and top-down analytical approaches, (3) using state-of-the-art machine learning algorithms, (4) integrating heterogeneous data sources, and (5) presenting the result with an interactive and transparent interface. CPAS is one of the first machine learning-based systems to be deployed in hospitals on a national scale to address the COVID-19 pandemic—we conclude the paper with a summary of the lessons learned from this experience. |
format | Online Article Text |
id | pubmed-7685302 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Springer US |
record_format | MEDLINE/PubMed |
spelling | pubmed-76853022020-11-25 CPAS: the UK’s national machine learning-based hospital capacity planning system for COVID-19 Qian, Zhaozhi Alaa, Ahmed M. van der Schaar, Mihaela Mach Learn Article The coronavirus disease 2019 (COVID-19) global pandemic poses the threat of overwhelming healthcare systems with unprecedented demands for intensive care resources. Managing these demands cannot be effectively conducted without a nationwide collective effort that relies on data to forecast hospital demands on the national, regional, hospital and individual levels. To this end, we developed the COVID-19 Capacity Planning and Analysis System (CPAS)—a machine learning-based system for hospital resource planning that we have successfully deployed at individual hospitals and across regions in the UK in coordination with NHS Digital. In this paper, we discuss the main challenges of deploying a machine learning-based decision support system at national scale, and explain how CPAS addresses these challenges by (1) defining the appropriate learning problem, (2) combining bottom-up and top-down analytical approaches, (3) using state-of-the-art machine learning algorithms, (4) integrating heterogeneous data sources, and (5) presenting the result with an interactive and transparent interface. CPAS is one of the first machine learning-based systems to be deployed in hospitals on a national scale to address the COVID-19 pandemic—we conclude the paper with a summary of the lessons learned from this experience. Springer US 2020-11-24 2021 /pmc/articles/PMC7685302/ /pubmed/33250568 http://dx.doi.org/10.1007/s10994-020-05921-4 Text en © The Author(s) 2020 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 Qian, Zhaozhi Alaa, Ahmed M. van der Schaar, Mihaela CPAS: the UK’s national machine learning-based hospital capacity planning system for COVID-19 |
title | CPAS: the UK’s national machine learning-based hospital capacity planning system for COVID-19 |
title_full | CPAS: the UK’s national machine learning-based hospital capacity planning system for COVID-19 |
title_fullStr | CPAS: the UK’s national machine learning-based hospital capacity planning system for COVID-19 |
title_full_unstemmed | CPAS: the UK’s national machine learning-based hospital capacity planning system for COVID-19 |
title_short | CPAS: the UK’s national machine learning-based hospital capacity planning system for COVID-19 |
title_sort | cpas: the uk’s national machine learning-based hospital capacity planning system for covid-19 |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7685302/ https://www.ncbi.nlm.nih.gov/pubmed/33250568 http://dx.doi.org/10.1007/s10994-020-05921-4 |
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