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 can have an impact on ED overcrowding that may affect the quality and access of health care. In this paper we propose an ad hoc process mining approach to discover the paths of the patients served by an ED. Our aim is to obtain a process model capable (1) to replicate properly the possible patient paths, and (2) to predict the next activities in the view of a possible application to online optimisation. To prove its effectiveness, we apply our ad hoc approach to a real case study.

An ad hoc process mining approach to discover patient paths of an Emergency Department

Duma, Davide;Aringhieri, Roberto
2020-01-01

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 can have an impact on ED overcrowding that may affect the quality and access of health care. In this paper we propose an ad hoc process mining approach to discover the paths of the patients served by an ED. Our aim is to obtain a process model capable (1) to replicate properly the possible patient paths, and (2) to predict the next activities in the view of a possible application to online optimisation. To prove its effectiveness, we apply our ad hoc approach to a real case study.
2020
32
6
34
https://rdcu.be/bcXn4
Duma, Davide; Aringhieri, Roberto
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2318/1684425
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