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Predicting and explaining absenteeism risk in hospital patients before and during COVID-19
In order to address one of the most challenging problems in hospital management – patients’ absenteeism without prior notice – this study analyses the risk factors associated with this event. To this end, through real data from a hospital located in the North of Portugal, a prediction model previous...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Author(s). Published by Elsevier Ltd.
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9972778/ https://www.ncbi.nlm.nih.gov/pubmed/37255583 http://dx.doi.org/10.1016/j.seps.2023.101549 |
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author | Borges, Ana Carvalho, Mariana Maia, Miguel Guimarães, Miguel Carneiro, Davide |
author_facet | Borges, Ana Carvalho, Mariana Maia, Miguel Guimarães, Miguel Carneiro, Davide |
author_sort | Borges, Ana |
collection | PubMed |
description | In order to address one of the most challenging problems in hospital management – patients’ absenteeism without prior notice – this study analyses the risk factors associated with this event. To this end, through real data from a hospital located in the North of Portugal, a prediction model previously validated in the literature is used to infer absenteeism risk factors, and an explainable model is proposed, based on a modified CART algorithm. The latter intends to generate a human-interpretable explanation for patient absenteeism, and its implementation is described in detail. Furthermore, given the significant impact, the COVID-19 pandemic had on hospital management, a comparison between patients’ profiles upon absenteeism before and during the COVID-19 pandemic situation is performed. Results obtained differ between hospital specialities and time periods meaning that patient profiles on absenteeism change during pandemic periods and within specialities. |
format | Online Article Text |
id | pubmed-9972778 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | The Author(s). Published by Elsevier Ltd. |
record_format | MEDLINE/PubMed |
spelling | pubmed-99727782023-02-28 Predicting and explaining absenteeism risk in hospital patients before and during COVID-19 Borges, Ana Carvalho, Mariana Maia, Miguel Guimarães, Miguel Carneiro, Davide Socioecon Plann Sci Article In order to address one of the most challenging problems in hospital management – patients’ absenteeism without prior notice – this study analyses the risk factors associated with this event. To this end, through real data from a hospital located in the North of Portugal, a prediction model previously validated in the literature is used to infer absenteeism risk factors, and an explainable model is proposed, based on a modified CART algorithm. The latter intends to generate a human-interpretable explanation for patient absenteeism, and its implementation is described in detail. Furthermore, given the significant impact, the COVID-19 pandemic had on hospital management, a comparison between patients’ profiles upon absenteeism before and during the COVID-19 pandemic situation is performed. Results obtained differ between hospital specialities and time periods meaning that patient profiles on absenteeism change during pandemic periods and within specialities. The Author(s). Published by Elsevier Ltd. 2023-06 2023-02-28 /pmc/articles/PMC9972778/ /pubmed/37255583 http://dx.doi.org/10.1016/j.seps.2023.101549 Text en © 2023 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 Borges, Ana Carvalho, Mariana Maia, Miguel Guimarães, Miguel Carneiro, Davide Predicting and explaining absenteeism risk in hospital patients before and during COVID-19 |
title | Predicting and explaining absenteeism risk in hospital patients before and during COVID-19 |
title_full | Predicting and explaining absenteeism risk in hospital patients before and during COVID-19 |
title_fullStr | Predicting and explaining absenteeism risk in hospital patients before and during COVID-19 |
title_full_unstemmed | Predicting and explaining absenteeism risk in hospital patients before and during COVID-19 |
title_short | Predicting and explaining absenteeism risk in hospital patients before and during COVID-19 |
title_sort | predicting and explaining absenteeism risk in hospital patients before and during covid-19 |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9972778/ https://www.ncbi.nlm.nih.gov/pubmed/37255583 http://dx.doi.org/10.1016/j.seps.2023.101549 |
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