Process mining techniques: An application to stroke care

Ronny Mans, Helen Schonenberg, Giorgio Leonardi, Silvia Panzarasa, Anna Cavallini, Silvana Quaglini, Wil Van Der Aalst

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

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.

Original languageEnglish
Title of host publicationStudies in Health Technology and Informatics
Pages573-578
Number of pages6
Volume136
Publication statusPublished - 2008

Keywords

  • Data analysis-extraction tools
  • Event-based systems
  • Process

ASJC Scopus subject areas

  • Biomedical Engineering
  • Health Informatics
  • Health Information Management

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