Applying Process Mining and RTLS for Modeling, and Analyzing Patients’ Pathways

Sina Namaki Araghi 1 Franck Fontanili 1 Elyes Lamine 1 Ludovic Tancerel Frederick Benaben 1
1 CGI - Centre Génie Industriel
Abstract : This paper aims at introducing a generic approach for visualizing, analyzing and diagnosing patients’ pathways. This approach could be categorized as a business intelligence approach to extract knowledge for decision makers in healthcare organizations. The analyses provided by this approach are based on the location data which is being recorded in the information system (IS) by indoor-Real-Time Location Systems (RTLS). Findings: Healthcare organizations are getting more eager to learn from the execution of their processes. They seek different tools and approaches to analyze the processes and visualize the problems. This paper presents one of the possibilities to provide more understanding of process executions and it is based on the positions of the patients in the organization. Approach: Business intelligence approaches provide new technical and technological solutions for business analysts to improve the quality of products and services within organizations. The approach i n this work helps to visualize patients’ pathways and analyze them by associating real-time localization and process mining. This approach consists of four phases in which several functionalities have been defined. These phases are Data, Information, Awareness, and Governance (DIAG). Also, a case study has been designed to illustrate the DIAG approach.
Keywords : Business Process Management Process Mining Real Time Location Systems
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Conference papers
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https://hal-mines-albi.archives-ouvertes.fr/hal-01924032
Contributor : Sina Namaki Araghi <>
Submitted on : Thursday, November 15, 2018 - 4:02:01 PM
Last modification on : Wednesday, June 5, 2019 - 11:03:01 AM

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Sina Namaki Araghi, Franck Fontanili, Elyes Lamine, Ludovic Tancerel, Frederick Benaben. Applying Process Mining and RTLS for Modeling, and Analyzing Patients’ Pathways. HEALTHINF 2018 - 11th International Conference on Health Informatics, Jan 2018, Funchal, Madeira, Portugal. pp.540-547, ⟨10.5220/0006651605400547⟩. ⟨hal-01924032⟩

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