Effecteurs mobiles de la permanence des soins ambulatoires missionnés par le SAMU-Centre 15 : intérêt d'un modèle numérique des trajets. Application dans le Val-de-Marne

Abstract : During out-of-hours times, mobile general practitioners (GPs), appointed by the SAMU - Centre 15 (French public emergency call center), can provide out-of-hours home visits (OOH-HV).The order in which these visits are carried out is based on an intuitive model, i.e. the shortest path problem, and determined according to the degree of urgency established at the time of the call to the SAMU - Centre 15 and the knowledge of the sector by the mobile GP. Maintaining timelines consistent with the medical need thus depends on the flow of visits and the GP’s response times. However, this transit time depends in particular on the number of available GPs and traffic conditions. Existing models for routing optimization are inapplicable to OOH-HV, due to the continuous updating of the list of visits to be carried out, as well as the weighting of the target time by the degree of urgency.We therefore propose to create a specific model for the optimization of the mobile GPs’ sent by the SAMU-Centre 15. We develop an evolutionary meta-heuristic of the genetic algorithm type, whose computational performances we first compare with those of an exact method of integer linear optimization (non evolutionary combinatorial optimization method), on theoretical data, integrating the clinical data (3 degrees of priority of visit), operational constraints data (mobile GPs’ fleet size) and response times objectives (3 target effection times). The objectives of this work are to show that the genetic algorithm, compared to the integer linear method, leads to a reduction in mobile GPs visit completion times, to a greater respect of the deadlines of target outcomes, as well as an increase in the number of patients seen per time unit (GPs time slot).Our results suggest that the genetic algorithm is more efficient than the integer linear method on all established criteria, and that its performances improve with the complexity of the problem to be solved (number of patients to visit, size of mobile GPs’ fleet).The use of the optimization method developed in this work could enable the SAMU-Centres 15 to improve the service provided to the population, in terms of efficiency, safety and quality of access to care.
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Matthieu Heidet. Effecteurs mobiles de la permanence des soins ambulatoires missionnés par le SAMU-Centre 15 : intérêt d'un modèle numérique des trajets. Application dans le Val-de-Marne. Médecine humaine et pathologie. Université Paris-Est, 2019. Français. ⟨NNT : 2019PESC0021⟩. ⟨tel-02178943⟩

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