Investigating clinical care pathways correlated with outcomes

Abstract

Clinical care pathway analysis is the process of discovering how clinical activities impact patients in their care journeys, and uses the discovered knowledge for various applications including the redesign and optimization of clinical pathways. We present an approach for mining clinical care pathways correlated with patient outcomes that involves a combination of clustering, process mining and frequent pattern mining. Our approach is implemented as a set of interactive tools in the business process insight (BPI) platform, a a collaborative software as a service platform, that provides an event-driven process-aware analytics toolset. After interactively utilizing the individual clustering, process mining, and frequent pattern mining capabilities in BPI, users can overlay frequent patterns, ranked according to their correlation with a particular patient outcome, on a mined model of the patient population with that outcome. We have tested our approach for mining care pathways correlated with outcomes on electronic medical record data obtained from a US based healthcare provider on congestive heart failure (CHF) patients. Experimental results show that the tools we have developed and implemented can provide new insights to facilitate the improvement of existing clinical care pathways. © 2013 Springer-Verlag.