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Updated: Jul 5, 2026

Setting Up a Stroke Team Algorithm and Conducting Simulation-based Training in the Emergency Department - A Practical Guide

Setting Up a Stroke Team Algorithm and Conducting Simulation-based Training in the Emergency Department - A Practical Guide

Published on: January 15, 2017

Process mining techniques: an application to stroke care.

Ronny Mans¹, Helen Schonenberg, Giorgio Leonardi

¹Eindhoven University of Technology, The Netherlands. r.s.mans@tue.nl

Studies in Health Technology and Informatics

|May 20, 2008

Summary

This summary is machine-generated.

Process mining analyzes hospital data to reveal process insights, improving patient care and reducing costs. This study demonstrates process mining

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Area of Science:

Health Informatics
Data Science
Process Management

Background:

Hospitals face pressure to enhance care quality and reduce costs in a competitive market.
Effective process understanding is crucial for hospital managers to achieve efficiency.
Information and Communication Technology (ICT) tools generate vast data for process analysis.

Purpose of the Study:

To demonstrate the applicability of process mining in the healthcare domain.
To extract process information from electronic health records for analysis.
To identify opportunities for process improvement in patient care.

Main Methods:

Utilizing process mining techniques on event log data from hospital information systems.
Applying a-posteriori analysis to extract process models.
Analyzing datasets specifically for stroke patient care pathways.

Main Results:

Process mining successfully extracted valuable process models from healthcare data.
The analysis provided insights into the actual processes for stroke patient care.
Demonstrated the potential for process redesign to improve efficiency and quality.

Conclusions:

Process mining is a viable and powerful technique for healthcare process analysis.
Understanding and optimizing clinical pathways can lead to better patient outcomes and cost savings.
The study highlights the transformative potential of data-driven process improvement in hospitals.