Inhomogeneous Poisson Process for Ambulance Relocation - Hêche, F.; Barakat, O.; Desmettre, T.; Marx, T.; Robert-Nicoud, S.
This paper proposes a statistical approach for real-time ambulance relocation in an Emergency Medical Service (EMS) system. First, based on the idea of measuring the probability that there is no ambulance available for a life-threatening call at the closest ambulance station, the risk of the environment is introduced. Then, a method for ambulance relocation to minimize this risk is developed. To assess the proposed approach, historical data spanning six years provided by the Centre Hospitalier Universitaire Vaudois (CHUV) are used. Data from 2015 to 2020 is utilized to build our method and the data from 2021 is used for the evaluation. The use of real-world data and an API to estimate travel times makes our experiments representative of real-world situations. In all experiments, our approach enables us to significantly decrease the risk of the environment. Furthermore, the proposed method reduces the mean response time by up to 30 seconds. Finally, the computation time is negligible and through the adjustment of specific hyperparameters, it becomes feasible to control the frequency of resource relocations throughout the day. This adjustment offers the flexibility to tailor the strategy according to the specific requirements of each EMS system. Moreover, our method demonstrates particular utility in situations with limited resources, which makes it especially valuable in crisis situations. These observations collectively suggest that our method has the potential to enhance the quality of EMS and, consequently, save lives. © 2023 Owner/Author(s).
Keywords: conferencePaper