Abstract
Process mining has proven itself as a promising analysis technique for processes in the health care domain. The goal of the EBMC2 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 EBMC2 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.
The work presented in this paper was conducted in the context of EBMC2 that is co-funded by the University of Vienna and the Medical University of Vienna.
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Binder, M. et al. (2012). On Analyzing Process Compliance in Skin Cancer Treatment: An Experience Report from the Evidence-Based Medical Compliance Cluster (EBMC2). In: Ralyté, J., Franch, X., Brinkkemper, S., Wrycza, S. (eds) Advanced Information Systems Engineering. CAiSE 2012. Lecture Notes in Computer Science, vol 7328. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31095-9_26
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DOI: https://doi.org/10.1007/978-3-642-31095-9_26
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