Evaluating the Process Capability Ratio of Patients’ Pathways by the Application of Process Mining, SPC and RTLS

Sina Namaki Araghi (1) , Franck Fontanili (1) , Elyes Lamine (1) , Nicolas Salatge (1) , Julien Lesbegueries (1) , Sebastien Rebiere Pouyade (1) , Frederick Benaben (1)

1 CGI - Centre Génie Industriel

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.

Mots clés: Patient’s Pathways; Statistical Process Control; Process Mining; Real-Time Location Systems

Domaines: Sciences de l'ingénieur [physics]

Sina Namaki Araghi, Franck Fontanili, Elyes Lamine, Nicolas Salatge, Julien Lesbegueries, et al.. Evaluating the Process Capability Ratio of Patients’ Pathways by the Application of Process Mining, SPC and RTLS. HEALTHINF 2019 - 12th International Conference on Health Informatics, Feb 2019, Prague, Czech Republic. pp.302-309, ⟨10.5220/0007380803020309⟩. ⟨hal-02125316⟩