Authors:
Sina Namaki Araghi
;
Franck Fontanili
;
Elyes Lamine
;
Nicolas Salatge
;
Julien Lesbegueries
;
Sebastien Rebiere Pouyade
and
Frederick Benaben
Affiliation:
Industrial Engineering Center of IMT Mines Albi, University of Toulouse, Albi 81000 and France
Keyword(s):
Real-Time Location Systems, Process Mining, Statistical Process Control, Patient’s Pathways.
Related
Ontology
Subjects/Areas/Topics:
Biomedical Engineering
;
Biomedical Signal Processing
;
Cloud Computing
;
Data Engineering
;
Data Management and Quality
;
Data Manipulation
;
Data Visualization
;
Devices
;
Distributed and Mobile Software Systems
;
e-Health
;
Health Engineering and Technology Applications
;
Health Information Systems
;
Healthcare Management Systems
;
Human-Computer Interaction
;
Mobile Technologies
;
Mobile Technologies for Healthcare Applications
;
Neural Rehabilitation
;
Neurotechnology, Electronics and Informatics
;
Physiological Computing Systems
;
Platforms and Applications
;
Sensor Networks
;
Software Engineering
;
Wearable Sensors and Systems
Abstract:
Learning how patients receive their health treatments is a critical mission for hospitals. To fulfill this task, this paper defines patients’ pathways as business process models and tries to apply process mining, real-time location systems(RTLS), and statistical process control (SPC) as a set of techniques to monitor patients’ pathways. This approach has been evaluated by a case study in a hospital living lab. These techniques analyze patients’ pathways from two different perspectives: (1)control-flow and (2)performance perspectives. In order to do so, we gathered the location data from movements of patients and used a proof of concept framework known as R.IO-DIAG to discover the processes. To elevate the performance analyses, this paper introduces the process capability ratio of the patients’ pathways by measuring the walking distance. The results lead to the evaluation of the quality of business processes.