48. Process Mining in Clinical Pathways: Bridging Challenges and Opportunities
Invited abstract in session HF-4: Innovation 3, stream Sessions.
Thursday, 15:30-17:00Room: St Olavs, Kunnskapssenteret KA12
Authors (first author is the speaker)
| 1. | Luca Murazzano
|
| Département d'Opérations et systèmes de décision, Université Laval | |
| 2. | Paolo Landa
|
| Département d’opérations et systèmes de décision, Université Laval | |
| 3. | Jean-Baptiste Gartner
|
| Management, Université Laval | |
| 4. | Andre Cote
|
| Management, Universite Laval |
Abstract
This study presents a systematic literature review examining the application of process mining (PM) in clinical pathways. The research aims to explore the potential of PM to analyze, discover, monitor, and optimize healthcare processes through event logs derived from hospital information systems. With the increasing complexity of patient care, clinical pathways serve as crucial instruments to harmonize practices and enhance patient outcomes. Despite PM's promising opportunities—such as improving workflow efficiency, ensuring protocol conformity, and enabling predictive analytics—several challenges persist. These include inadequate regulatory frameworks governing PM usage in clinical contexts and uneven exploration of PM applications, particularly predictive process mining. By synthesizing findings from over 50 peer-reviewed studies spanning diverse specialties and healthcare settings, this review uncovers key methodologies, trends, and frameworks deployed in PM. Preliminary results emphasize the need for robust longitudinal data integration and regulatory alignment while highlighting gaps in specific applications like predictive process mining. This study paves the way for more targeted investigations to advance the quality, efficiency, and compliance of clinical pathways through PM methodologies.
Keywords
- Care Pathways
- Healthcare management
- Analytics
Status: accepted
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