Artificial Neural Networks and risk stratification models in Emergency Departments: The policy maker's perspective
Raffaello Furlan and
Roberto Ippoliti ()
Health Policy, 2016, vol. 120, issue 1, 111-119
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: I12 D81 (search for similar items in EconPapers)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:hepoli:v:120:y:2016:i:1:p:111-119
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