Process mining techniques: an application to stroke care.
In a competitive health-care market, hospitals have to focus on ways to streamline their processes in order to deliver high quality care while at the same time reducing costs. To accomplish this goal, hospital managers need a thorough understanding of the actual processes. Diffusion of Information and Communication Technology tools within hospitals, such as electronic clinical charts, computerized guidelines and, more generally, decision support systems, make huge collections of data available, not only for data analysis, but also for process analysis. Process mining can be used to extract process related information (e.g., process models) from data, i.e., process mining describes a family of a-posteriori analysis techniques exploiting the information recorded in the event logs. This process information can be used to understand and redesign processes to become efficient high quality processes. In this paper, we apply process mining on two datasets for stroke patients and present the most interesting results. Above all, the paper demonstrates the applicability of process mining in the health-care domain.
Mans
Ronny
R
Eindhoven University of Technology, The Netherlands. r.s.mans@tue.nl
Schonenberg
Helen
H
Leonardi
Giorgio
G
Panzarasa
Silvia
S
Cavallini
Anna
A
Quaglini
Silvana
S
van der Aalst
Wil
W
D002985:Clinical Protocols; D003625:Data Collection; D003628:Database Management Systems; D020000:Decision Support Systems, Clinical; D017598:Efficiency, Organizational; D004632:Emergency Medical Services; D019983:Guideline Adherence; D006751:Hospital Information Systems; D006801:Humans; D016247:Information Storage and Retrieval; D007558:Italy; D008492:Medical Informatics Computing; D016347:Medical Records Systems, Computerized; D017064:Process Assessment, Health Care; D020521:Stroke / Q000175:diagnosis / Q000628:therapy*; D013647:Task Performance and Analysis