Curation and Analysis of MIMICEL -- An Event Log for MIMIC-IV Emergency Department

TL;DR

This paper introduces MIMICEL, a curated event log derived from MIMIC-IV-ED data, enabling process mining analysis of patient flow in emergency departments to improve efficiency and address overcrowding issues.

Contribution

The paper presents the creation and validation of MIMICEL, a novel event log dataset for ED process analysis, facilitating research and practical improvements in healthcare workflows.

Findings

MIMICEL effectively captures patient journey data in ED.

Analyses using MIMICEL demonstrate its utility for process mining.

The dataset supports future research in ED process optimization.

Abstract

The global issue of overcrowding in emergency departments (ED) necessitates the analysis of patient flow through ED to enhance efficiency and alleviate overcrowding. However, traditional analytical methods are time-consuming and costly. The healthcare industry is embracing process mining tools to analyse healthcare processes and patient flows. Process mining aims to discover, monitor, and enhance processes by obtaining knowledge from event log data. However, the availability of event logs is a prerequisite for applying process mining techniques. Hence, this paper aims to generate an event log for analysing processes in ED. In this study, we extract an event log from the MIMIC-IV-ED dataset and name it MIMICEL. MIMICEL captures the process of patient journey in ED, allowing for analysis of patient flows and improving ED efficiency. We present analyses conducted using MIMICEL to demonstrate the utility of the dataset. The curation of MIMICEL facilitates extensive use of MIMIC-IV-ED data for ED analysis using process mining techniques, while also providing the process mining research communities with a valuable dataset for study.