Artificial Neural Networks and risk stratification models in Emergency Departments: The policy maker's perspective

Ivo Casagranda, Giorgio Costantino, Greta Falavigna, Raffaello Furlan and Roberto Ippoliti

Health Policy, 2016, vol. 120, issue 1, 111-119

Abstract: The primary goal of Emergency Department (ED) physicians is to discriminate between individuals at low risk, who can be safely discharged, and patients at high risk, who require prompt hospitalization. The problem of correctly classifying patients is an issue involving not only clinical but also managerial aspects, since reducing the rate of admission of patients to EDs could dramatically cut costs. Nevertheless, a trade-off might arise due to the need to find a balance between economic interests and the health conditions of patients.

Keywords: Emergency Departments (ED); Risk stratification; Artificial Neural Networks (ANNs); Syncope; Hospital admission (search for similar items in EconPapers)
JEL-codes: D81 I12 (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (5)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:hepoli:v:120:y:2016:i:1:p:111-119

DOI: 10.1016/j.healthpol.2015.12.003

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