The Emergency Department (ED) management presents a really high complexity due to the admissions of patients with a wide variety of diseases and different urgency, which require the execution of different activities involving human and medical resources. This have an impact on ED overcrowding that may affect the quality and access of health care. In this paper we apply Process Mining techniques to a real case study: from the ED database, discovery techniques identify the possible paths of a patient on the basis of the information available at the triage. Our purpose is to obtain precise process models for replicating and predicting the patient paths.

Mining the patient flow through an emergency department to deal with overcrowding

Duma D.
;
2017-01-01

Abstract

The Emergency Department (ED) management presents a really high complexity due to the admissions of patients with a wide variety of diseases and different urgency, which require the execution of different activities involving human and medical resources. This have an impact on ED overcrowding that may affect the quality and access of health care. In this paper we apply Process Mining techniques to a real case study: from the ED database, discovery techniques identify the possible paths of a patient on the basis of the information available at the triage. Our purpose is to obtain precise process models for replicating and predicting the patient paths.
2017
Springer Proceedings in Mathematics and Statistics
Inglese
3rd International Conference on Health Care Systems Engineering, HCSE 2017
2017
ita
210
49
59
11
978-3-319-66145-2
978-3-319-66146-9
Springer New York LLC
Emergency department; Overcrowding; Patient flow; Process mining
no
none
Duma, D.; Aringhieri, R.
273
info:eu-repo/semantics/conferenceObject
2
4 Contributo in Atti di Convegno (Proceeding)::4.1 Contributo in Atti di convegno
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11571/1440895
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