Analyzing Sepsis Treatment Variations in Subpopulations with Process Mining

F. Rademaker, R. H. Bemthuis, J. Arachchige, F. A. Bukhsh

2024

Abstract

Healthcare processes frequently deviate from established treatment protocols due to unforeseen events and the complexities of illnesses. Many healthcare procedures do not account for variations in treatment paths across different diseases and patient subpopulations. Understanding the similarities and differences in treatment paths for different patient groups can provide valuable insights and potential process enhancements for various subgroups of concern. For hospitals, understanding various patient populations, such as severe or non-severe cases, is key for enhancing care paths. In this paper, we aim to compare treatment procedures for different subpopulations of patients using process mining techniques and identify indicators to improve the care path. We utilize the process mining for healthcare (PM2 HC) methodology to identify variations in treatment paths among different patient subgroups. We conducted a case study on sepsis, a complex illness with a wealth of available data, for in-depth analysis. Our findings indicate that various subpopulations exhibit different outcomes, offering promising directions for further research.

Paper Citation

in Harvard Style

Rademaker F., H. Bemthuis R., Arachchige J. and A. Bukhsh F. (2024). Analyzing Sepsis Treatment Variations in Subpopulations with Process Mining. In Proceedings of the 26th International Conference on Enterprise Information Systems - Volume 1: ICEIS; ISBN 978-989-758-692-7, SciTePress, pages 85-94. DOI: 10.5220/0012600700003690

in Bibtex Style

@conference{iceis24,
author={F. Rademaker and R. H. Bemthuis and J. Arachchige and F. A. Bukhsh},
title={Analyzing Sepsis Treatment Variations in Subpopulations with Process Mining},
booktitle={Proceedings of the 26th International Conference on Enterprise Information Systems - Volume 1: ICEIS},
year={2024},
pages={85-94},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012600700003690},
isbn={978-989-758-692-7},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 26th International Conference on Enterprise Information Systems - Volume 1: ICEIS
TI - Analyzing Sepsis Treatment Variations in Subpopulations with Process Mining
SN - 978-989-758-692-7
AU - Rademaker F.
AU - H. Bemthuis R.
AU - Arachchige J.
AU - A. Bukhsh F.
PY - 2024
SP - 85
EP - 94
DO - 10.5220/0012600700003690
PB - SciTePress