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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
Descripción
Sumario: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.