The Emergency Department (ED) is responsible to provide medical and surgical care to patients arriving at the hospital in need of immediate care. At the regional level, the EDs system can be seen as a network of EDs cooperating to maximise the outputs (number of patients served, average waiting time, ...) and outcomes in terms of the provided care quality. In this paper we discuss how quantitative analysis based on health care big data can provide a tool to evaluate the dispatching policies for the network of emergency departments operating in Piedmont, Italy: the basic idea is to exploit clusters of EDs in such a way to fairly distribute the workload. Further, we discuss how big data can enable a novel methodological approach to the health system analysis.

Evaluating the Dispatching Policies for a Regional Network of Emergency Departments Exploiting Health Care Big Data

Aringhieri, Roberto;Duma, Davide;
2018-01-01

Abstract

The Emergency Department (ED) is responsible to provide medical and surgical care to patients arriving at the hospital in need of immediate care. At the regional level, the EDs system can be seen as a network of EDs cooperating to maximise the outputs (number of patients served, average waiting time, ...) and outcomes in terms of the provided care quality. In this paper we discuss how quantitative analysis based on health care big data can provide a tool to evaluate the dispatching policies for the network of emergency departments operating in Piedmont, Italy: the basic idea is to exploit clusters of EDs in such a way to fairly distribute the workload. Further, we discuss how big data can enable a novel methodological approach to the health system analysis.
MOD 2017: Machine Learning, Optimization, and Big Data
Volterra
Settembre 2017
MOD 2017: Machine Learning, Optimization, and Big Data
Springer
10710
549
561
https://link.springer.com/chapter/10.1007%2F978-3-319-72926-8_46
Aringhieri, Roberto; Dell’Anna, Davide; Duma, Davide; Sonnessa, Michele
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2318/1655211
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