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

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 (i) to replicate properly the possible patient paths, and (ii) 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.

Identifying Frequent Health Care Users and Care Consumption Patterns: Process Mining of Emergency Medical Services Data

“…Process mining has been successfully used to map health care processes, clarifying how patients are served as a net effect of activities performed by health care providers. So far, most examples of its use in health care are related to an intrahospital context [17][18][19][20][21][22][23][24][25][26][27]. By automatically generating process maps using factual observations retrieved from data, process mining has important advantages over other modeling techniques that rely on manual observations of the actual system or inspection of documents [17,34].…”

“…Process mining has an advantage over other mapping techniques as it uses factual observations retrieved from data rather than man-made process models. Process mining has been successfully used to analyze health care processes, usually in an intrahospital context [17][18][19][20][21][22][23][24][25][26][27]. However, its application to regional health care networks is new.…”

Process Mining-Supported Emergency Room Process Performance Indicators

“…In addition, [ 16 ] proposed time-related indicators that focus on the elapsed time between two ER activities, such as triage and doctor seen. In addition to presenting indicators, there have been several applications with the ad-hoc approaches to understand ER processes [ 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 , 25 ]. For example, [ 18 ] introduced an approach to evaluate the capabilities of process mining to the ER process on the stroke case, and [ 19 ] explored the effects of interactive process mining using the value-based technologies.…”

“…In addition, [ 22 ] performed a comparative analysis of four different hospitals by focusing on control-flow and time perspectives, and [ 23 ] applied the trace clustering technique for deriving more explicit process maps. In addition, [ 24 ] proposed an ad-hoc process mining approach to discover the ER patient paths, and [ 25 ] suggested how to derive optimal layout of an emergency room by analyzing the care processes.…”

Editorial for the special issue on “Modelling, simulation, and optimization in health care”

“…After a thorough peer-review according to the standards of the FSM journal, the following eighth papers were accepted for publication. Duma and Aringhieri (2020) propose a framework to mine patterns in a sequence of activities, i.e., paths, occurring when patients, with different characteristics and urgency, access Emergency Departments (ED). The study presents an ad hoc process mining model capable to replicate a large variety of paths and to predict the use of the ED resources by each patient based on the information known upon patient access.…”