Process mining has proven itself as a promising analysis technique for processes in the health care domain. The goal of the EBMC 2 project is to analyze skin cancer treatment processes regarding their compliance with relevant guidelines. For this, first of all, the actual treatment processes have to be discovered from the available data sources. In general, the L * life cycle model has been suggested as structured methodology for process mining projects. In this experience paper, we describe the challenges and lessons learned when realizing the L * life cycle model in the EBMC 2 context. Specifically, we provide and discuss different approaches to empower data of low maturity levels, i.e., data that is not already available in temporally ordered event logs, including a prototype for structured data acquisition. Further, first results on how process mining techniques can be utilized for data screening are presented. © 2012 Springer-Verlag Berlin Heidelberg.
CITATION STYLE
Binder, M., Dorda, W., Duftschmid, G., Dunkl, R., Fröschl, K. A., Gall, W., … Weber, S. (2012). On analyzing process compliance in skin cancer treatment: An experience report from the evidence-based medical compliance cluster (EBMC 2). In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7328 LNCS, pp. 398–413). https://doi.org/10.1007/978-3-642-31095-9_26
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