Optimizing Privacy-Utility Trade-Off in Healthcare Processes: Simulation, Anonymization, and Evaluation (Using Process Mining) of Event Logs

Omar Kamal, Syeda Sohail, Faiza Bukhsh

2024

Abstract

In healthcare, big data analytics involve balancing patients’ privacy and data utility. Optimizing healthcare data utility often includes limited access to sensitive data by trusted onsite entities. This potentially hinders broader-scale data utilization by third-party data analysts. As a solution, this research simulates a health-care process-based event log, inspired by a local hospital’s radiology department. The simulated event log is anonymized using k-anonymity. The anonymized and un-anonymized event logs are evaluated, through process discovery techniques, using the process mining tool, ProM 6.11, for Privacy-utility trade-off assessment. Results indicate successful privacy preservation with a distinct loss in utility in the anonymized healthcare process model, which was not visible otherwise. Therefore, to ensure the efficacy of healthcare process analysis on anonymized sensitive event logs, the utilization of process mining techniques is beneficial for process utility and privacy protection evaluation.

Paper Citation

in Harvard Style

Kamal O., Sohail S. and Bukhsh F. (2024). Optimizing Privacy-Utility Trade-Off in Healthcare Processes: Simulation, Anonymization, and Evaluation (Using Process Mining) of Event Logs. In Proceedings of the 14th International Conference on Simulation and Modeling Methodologies, Technologies and Applications - Volume 1: SIMULTECH; ISBN 978-989-758-708-5, SciTePress, pages 289-296. DOI: 10.5220/0012766800003758

in Bibtex Style

@conference{simultech24,
author={Omar Kamal and Syeda Sohail and Faiza Bukhsh},
title={Optimizing Privacy-Utility Trade-Off in Healthcare Processes: Simulation, Anonymization, and Evaluation (Using Process Mining) of Event Logs},
booktitle={Proceedings of the 14th International Conference on Simulation and Modeling Methodologies, Technologies and Applications - Volume 1: SIMULTECH},
year={2024},
pages={289-296},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012766800003758},
isbn={978-989-758-708-5},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 14th International Conference on Simulation and Modeling Methodologies, Technologies and Applications - Volume 1: SIMULTECH
TI - Optimizing Privacy-Utility Trade-Off in Healthcare Processes: Simulation, Anonymization, and Evaluation (Using Process Mining) of Event Logs
SN - 978-989-758-708-5
AU - Kamal O.
AU - Sohail S.
AU - Bukhsh F.
PY - 2024
SP - 289
EP - 296
DO - 10.5220/0012766800003758
PB - SciTePress