A Pipeline for the Usage of the Core Data Set of the Medical Informatics Initiative for Process Mining – A Technical Case Report
Challenges encountered include handling the variability and quality of data, and overcoming network and computational constraints. Our pipeline demonstrates how PM can be applied even in complex systems like healthcare, by allowing for a standardized yet flexible analysis pipeline which is widely applicable.The successful application emphasize the critical role of tailored event log generation and data querying capabilities in enabling effective PM applications, thus enabling evidence-based improvements in healthcare processes.
Authors
- Harry H. Beyel (ORCID: https://orcid.org/0000-0002-6541-3848)
- Raphael W. Majeed (ORCID: https://orcid.org/0000-0002-8260-8815)
- Rainer Röhrig (ORCID: https://orcid.org/0000-0002-0032-5118)
- Jonas Bienzeisler (ORCID: https://orcid.org/0000-0003-3633-147X)
- Viki Peeva (ORCID: https://orcid.org/0000-0001-7144-5136)
- Behrus Puladi (ORCID: https://orcid.org/0000-0001-5909-6105)
- Wil M. P. van der Aalst (ORCID: https://orcid.org/0000-0002-0955-6940)
- Marco Pegoraro (ORCID: https://orcid.org/0000-0002-8997-7517)
- Hauke Heidemeyer (ORCID: https://orcid.org/0000-0002-7401-6860)
- Leo Auhagen
Institutions
- German Center for Lung Research (DE)
- Universities of Giessen and Marburg Lung Center (DE)
- RWTH Aachen University (DE)
Publication Details
- Journal
- Studies in health technology and informatics
- Published
- 2024-08-30
- DOI
- https://doi.org/10.3233/shti240835
- Citations
- 4
- Primary Topic
- Business Process Modeling and Analysis
- Type
- article
- Field-Weighted Citation Impact
- 4.13