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, Davide;Aringhieri, Roberto
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
3rd International Conference on Health Care Systems Engineering, HCSE 2017
ita
2017
Springer Proceedings in Mathematics and Statistics
Springer New York LLC
210
49
59
9783319661452
http://www.springer.com/series/10533
https://link.springer.com/chapter/10.1007%2F978-3-319-66146-9_5
Emergency department; Overcrowding; Patient flow; Process mining; Mathematics (all)
Duma, Davide*; Aringhieri, Roberto
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2318/1662826
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