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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...

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Detalles Bibliográficos
Autores principales: Borges, Ana, Carvalho, Mariana, Maia, Miguel, Guimarães, Miguel, Carneiro, Davide
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Author(s). Published by Elsevier Ltd. 2023
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.
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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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