 Predicting and explaining absenteeism risk in hospital patients before and during COVID-19Ana Borges, Mariana Carvalho, Miguel Maia, Miguel Guimarães and Davide Carneiro Socio-Economic Planning Sciences, 2023, vol. 87, issue PB Abstract: 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. Keywords: Patients absenteeism; Risk factors; Logistic model; Explainable model; CART algorithm; COVID-19 (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:soceps:v:87:y:2023:i:pb:s0038012123000496 DOI: 10.1016/j.seps.2023.101549 Access Statistics for this article Socio-Economic Planning Sciences is currently edited by Barnett R. Parker More articles in Socio-Economic Planning Sciences from Elsevier |
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