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Demand for surgical care is rising worldwide, making the organization of the operating room (OR) a topic of strong interest. During the last two decades, the number of papers on methods for OR planning and scheduling under uncertainty has increased significantly. However, most hospitals neglect this aspect, and use deterministic approaches to schedule their surgical interventions. This leads us to the following research question: "How can discrete-event simulation help assess the impact of uncertainty on patient waiting time in the OR?" To answer this question, we suggest a 3-step methodology: (1) building the deterministic model of the studied OR, (2) implementing uncertainties on activity durations, patient arrival times and patient care requirements, and (3) experimenting with different uncertainty-related scenarios and analyzing the results. We have applied this methodology to a use-case inspired from our partner's OR: Hôpital Privé de La Baie, from the Vivalto Santé French health group.

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His research activities focus on the use of discrete event simulation-based digital twin in healthcare operational process. He has achieved several industrial studies and research projects based on discrete event simulation and associated tools such as BPM, RTLS, Process and Data Mining. He is a laureate of the AP-HP Paris & CHU Nantes call for Expression of Interest on Digital Hospital of the Future in 2017, with a proposal on a Digital Twin of Patients Pathways.

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