Authors:
Sina Namaki Araghi
1
;
Franck Fontanili
1
;
Elyes Lamine
1
;
Ludovic Tancerel
2
and
Frédérick Benaben
1
Affiliations:
1
Ecole de Mines Albi-Carmaux, France
;
2
Maple High Tech, France
Keyword(s):
Business Process Management, Process Mining, Real Time Location Systems.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Biomedical Engineering
;
Data Engineering
;
Data Management and Quality
;
Data Manipulation
;
Data Mining
;
Data Visualization
;
Databases and Information Systems Integration
;
Enterprise Information Systems
;
Evaluation and Use of Healthcare IT
;
Health Information Systems
;
Healthcare Management Systems
;
Sensor Networks
;
Signal Processing
;
Soft Computing
Abstract:
Purpose: 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
in 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.
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