Decision support through risk cost estimation in 30-day hospital unplanned readmission

Laura Arnal, Pedro Pons-Suñer, J Ramón Navarro-Cerdán, Pablo Ruiz-Valls, Jose Caballero Mateos Mª, Bernardo Valdivieso Martínez and Juan-Carlos Perez-Cortes

PLOS ONE, 2022, vol. 17, issue 7, 1-16

Abstract: Unplanned hospital readmissions mean a significant burden for health systems. Accurately estimating the patient’s readmission risk could help to optimise the discharge decision-making process by smartly ordering patients based on a severity score, thus helping to improve the usage of clinical resources. A great number of heterogeneous factors can influence the readmission risk, which makes it highly difficult to be estimated by a human agent. However, this score could be achieved with the help of AI models, acting as aiding tools for decision support systems. In this paper, we propose a machine learning classification and risk stratification approach to assess the readmission problem and provide a decision support system based on estimated patient risk scores.

Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0271331

DOI: 10.1371/journal.pone.0271331

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