Process Mining for Demographic Insights: A Subpopulation Analysis in Healthcare Pathways

Priya Naguine, Faiza Bukhsh, Jeewanie Jayasinghe Arachchige, Rob Bemthuis

2025

Abstract

Demographic variations in healthcare pathways are key for delivering effective and equitable patient care. Examining pathway differences across age and gender groups can help uncover demographic-specific disparities in care delivery. In this paper, we demonstrate the use of the Process Mining Project Methodology in Health-care (PM2HC) for the subpopulation-based analysis of treatment pathways, using process mining techniques. We validate this methodology through a case study on frozen shoulder treatment using the MIMIC-IV data set. Key findings reveal distinct procedural sequences for male and female patients, as well as notable age-based variations in treatment choices and timelines. These insights underscore the influence of demographic factors on healthcare processes. Expert evaluations further highlight the practicality of the methodology and its potential to guide targeted interventions that address various patient needs, thus enhancing personalized care. This work contributes to clinical research and practice by identifying inefficiencies and informing tailored interventions. Future efforts will extend the methodology to other medical conditions and integrate multi-institutional data for broader applicability. By advancing process mining in healthcare, this research provides insight into improving patient care and addressing demographic diversity.

Paper Citation

in Harvard Style

Naguine P., Bukhsh F., Arachchige J. and Bemthuis R. (2025). Process Mining for Demographic Insights: A Subpopulation Analysis in Healthcare Pathways. In Proceedings of the 27th International Conference on Enterprise Information Systems - Volume 1: ICEIS; ISBN 978-989-758-749-8, SciTePress, pages 267-277. DOI: 10.5220/0013289800003929

in Bibtex Style

@conference{iceis25,
author={Priya Naguine and Faiza Bukhsh and Jeewanie Arachchige and Rob Bemthuis},
title={Process Mining for Demographic Insights: A Subpopulation Analysis in Healthcare Pathways},
booktitle={Proceedings of the 27th International Conference on Enterprise Information Systems - Volume 1: ICEIS},
year={2025},
pages={267-277},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013289800003929},
isbn={978-989-758-749-8},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 27th International Conference on Enterprise Information Systems - Volume 1: ICEIS
TI - Process Mining for Demographic Insights: A Subpopulation Analysis in Healthcare Pathways
SN - 978-989-758-749-8
AU - Naguine P.
AU - Bukhsh F.
AU - Arachchige J.
AU - Bemthuis R.
PY - 2025
SP - 267
EP - 277
DO - 10.5220/0013289800003929
PB - SciTePress