Getting a grasp on clinical pathway data: An approach based on process mining

Abstract

Since healthcare processes are pre-eminently heterogeneous and multi-disciplinary, information systems supporting these processes face important challenges in terms of design, implementation and diagnosis. Nonetheless, streamlining clinical pathways with the purpose of delivering high quality care while at the same time reducing costs is a promising goal. In this paper, we propose a methodology founded on process mining for intelligent analysis of clinical pathway data. Process mining can be considered a valuable approach to obtain a better understanding about the actual way of working in human-centric processes such as clinical pathways by investigating the event data as recorded in healthcare information systems. However, capturing tangible knowledge from clinical processes with their ad hoc and complex nature proves difficult. Accordingly, this paper proposes a data analysis methodology focussing on the extraction of tangible insights from clinical pathway data by adopting both a drill up and a drill down perspective. © 2013 Springer-Verlag.