Verifying Guideline Compliance in Clinical Treatment Using Multi-perspective Conformance Checking: A Case Study

Clinical guidelines support physicians in the evidence-based treatment of patients. The technical verification of guideline compliance is not trivial, since guideline knowledge is usually represented textually and none of the approaches to computer-interpretable guideline representation has yet been able to establish itself. Due to the procedural nature of treatment sequences, this case study examines the applicability of a guideline process model to real hospital data for verification of guideline compliance. For this purpose, the limitations and challenges in the transformation of clinical data into an event log and in the application of conformance checking to align the data with the guideline reference model are investigated. As a data set, we use treatment data of skin tumor patients from a cancer registry enriched by hospital information system data. The results show the difficulty of applying process mining to medically complex and heterogeneous data and the need for complex preprocessing. The variability of clinical processes makes the application of global conformance checking algorithms challenging. In addition, the work shows the semantic weakness of the alignments and the need for new semantically sensitive approaches.