Evaluating the dispatching policies for a regional network of emergency departments exploiting health care big data
Publication date
2018
Authors
Aringhieri, Roberto
Dell’Anna, Davide
Duma, Davide
Sonnessa, Michele
Editors
Advisors
Supervisors
Document Type
Part of book
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License
taverne
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.
Keywords
Big data, Emergency care pathway, Health systems, Taverne, Theoretical Computer Science, General Computer Science
Citation
Aringhieri, R, Dell’Anna, D, Duma, D & Sonnessa, M 2018, Evaluating the dispatching policies for a regional network of emergency departments exploiting health care big data. in Machine Learning, Optimization, and Big Data - Third International Conference, MOD 2017, Revised Selected Papers. vol. 10710 LNCS, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 10710 LNCS, Springer, pp. 549-561, 3rd International Conference on Machine Learning, Optimization, and Big Data, MOD 2017, Volterra, Italy, 14/09/17. https://doi.org/10.1007/978-3-319-72926-8_46, conference