Analysis of patient pathways with contextual process mining

Abstract

The volume and diversity of healthcare information available through the use of modern technology offers great potential for improving health services delivery. Giving healthcare practitioners and health system administrators the ability to investigate and analyse data from various perspectives can promote evidence-based decision making. Current analysis approaches often result in models where essential relations are difficult to depict and/or discern. Further it is not easy to dynamically change the level of detail in order to accommodate user requirements and allow users to analyse data from various perspectives. We outline an approach involving filtering and abstraction of event logs using ontologies, dimensional modeling and cluster analysis so healthcare professionals may access the information they need. Our approach enhances existing process mining techniques by incorporating data mining techniques for dividing patient records into closely related groups, and results in contextual process mining.