Predicting and explaining absenteeism risk in hospital patients before and during COVID-19

Ana Borges; Mariana Carvalho; Miguel Maia; Miguel Guimarães; Davide Carneiro

doi:10.1016/j.seps.2023.101549

Predicting and explaining absenteeism risk in hospital patients before and during COVID-19

Socioecon Plann Sci. 2023 Jun:87:101549. doi: 10.1016/j.seps.2023.101549. Epub 2023 Feb 28.

Authors

Ana Borges¹, Mariana Carvalho¹, Miguel Maia¹, Miguel Guimarães¹, Davide Carneiro¹

Affiliation

¹ CIICESI, ESTG, Politecnico do Porto, Rua do Curral, Casa do Curral, Margaride, Felgueiras, 4610-156, Portugal.

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: 62J05; 62P10; 62P25; 68T10; CART algorithm; COVID-19; Explainable model; Logistic model; Patients absenteeism; Risk factors.