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Predicting and explaining absenteeism risk in hospital patients before and during COVID-19.
Borges, Ana; Carvalho, Mariana; Maia, Miguel; Guimarães, Miguel; Carneiro, Davide.
Afiliação
  • Borges A; CIICESI, ESTG, Politecnico do Porto, Rua do Curral, Casa do Curral, Margaride, Felgueiras, 4610-156, Portugal.
  • Carvalho M; CIICESI, ESTG, Politecnico do Porto, Rua do Curral, Casa do Curral, Margaride, Felgueiras, 4610-156, Portugal.
  • Maia M; CIICESI, ESTG, Politecnico do Porto, Rua do Curral, Casa do Curral, Margaride, Felgueiras, 4610-156, Portugal.
  • Guimarães M; CIICESI, ESTG, Politecnico do Porto, Rua do Curral, Casa do Curral, Margaride, Felgueiras, 4610-156, Portugal.
  • Carneiro D; CIICESI, ESTG, Politecnico do Porto, Rua do Curral, Casa do Curral, Margaride, Felgueiras, 4610-156, Portugal.
Socioecon Plann Sci ; 87: 101549, 2023 Jun.
Article em En | MEDLINE | ID: mdl-37255583
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.
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Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Etiology_studies / Prognostic_studies / Risk_factors_studies Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Etiology_studies / Prognostic_studies / Risk_factors_studies Idioma: En Ano de publicação: 2023 Tipo de documento: Article