A modeling approach based on multi-perspective declarative process mining for clinical activity

Abstract

Modeling clinical activities plays an important role in process mining, which is essential for improving medical quality. Traditional process mining methods focus on control flow of events, ignoring the data perspective including time and resources properties. Besides, clinical experts often have difficulties to classify the event attributes from a computer's point of view for model representation. We present a constraint-based approach with multi-perspective declarative process mining, which supports modeling medical process by clinical staff themselves. The event attributes are classified according to openEHR and the created model could be shared among medical institutions.