A model based slicing technique for process mining healthcare information

Abstract

Process mining is a powerful technique which uses an organization’s event data to extract and analyse process flow information and develop useful process models. However, it is difficult to apply process mining techniques to healthcare information due to factors relating to the complexity inherent in the healthcare domain and associated information systems. There are also challenges in understanding and meaningfully presenting results of process mining and problems relating to technical issues among the users. We propose a model based slicing approach based on dimensional modeling and ontological hierarchies that can be used to raise the level of abstraction during process mining, thereby more effectively dealing with the complexity and other issues. We also present a structural property of the proposed slicing technique for process mining.