Improving the Management of an Emergency Call Service by Combining Process Mining and Discrete Event Simulation Approaches - Risks and Resilience of Collaborative Networks
Conference Papers Year : 2015

Improving the Management of an Emergency Call Service by Combining Process Mining and Discrete Event Simulation Approaches

Abstract

Each Emergency Medical Assistance Centre in France (SAMU), includes an emergency call service. It provides an adequate and immediate response to medical problems. The processing of the incoming calls can be seen as a collaborative process involving several stakeholders. The control of such a process is crucial. Indeed, the effectiveness of the response to these incoming calls strongly impacts the quality of service of these centres, which is the main information which the government relies for their funding. The aim of this paper is to analyse such a collaborative process, regarding the performance targets requested by the French government. To this end, we suggest applying a new approach, based on the combination of two well-known engineering techniques, in consecutive manner. We will first use process mining techniques to obtain meaningful knowledge about the studied collaborative processes, relying on real data from a French Emergency Medical Assistance Centre. Secondly, we will use a Discrete Event Simulation approach as an effective tool to assess the efficiency of the current management of this emergency call centre and to ask (and answer) some ‘what if?’ questions to identify possible ways of improving their effectiveness.
Fichier principal
Vignette du fichier
370605_1_En_50_Chapter.pdf (11.23 Mo) Télécharger le fichier
Origin Files produced by the author(s)
Loading...

Dates and versions

hal-01437942 , version 1 (17-01-2017)

Licence

Identifiers

Cite

Elyes Lamine, Franck Fontanili, Maria Di Mascolo, Hervé Pingaud. Improving the Management of an Emergency Call Service by Combining Process Mining and Discrete Event Simulation Approaches. 16th Working Conference on Virtual Enterprises (PROVE), Oct 2015, Albi, France. pp.535-546, ⟨10.1007/978-3-319-24141-8_50⟩. ⟨hal-01437942⟩
627 View
281 Download

Altmetric

Share

More