Publicación: Vehicle location models for Emergency Medical Services. An application for a Colombian company
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Resumen en español
Ambulance location, in a certain area of coverage, is a key element in reducing the waiting time of a potential patient and the initiation a healthcare service in Emergency Medical Services (EMS). The Operations Research area, developing and solving adequate mathematical models, helps to make good decisions in EMS. We propose two variants of a Mixed Integer Linear Programming model for locating heterogeneous fleet vehicles to support different types of services in emergency medical care, taking into account the operational requirements of a health care service company in Colombia. The proposed models do not exactly match any of those found in the literature. The models are solved with Gurobi solver and the modeling language AMPL and they are successfully validated with historical data of the company under study and some estimates based on external sources. These obtained results are compared using an adaptation of the concept of Preparedness taken from the literature for ambulance positioning, as regard to measure the readiness of the system to the expected demand. The new results show that the relevance of each model depends of the prioritization of services and/or areas that the company considers.
Resumen en inglés
Ambulance location, in a certain area of coverage, is a key element in reducing the waiting time of a potential patient and the initiation a healthcare service in Emergency Medical Services (EMS). The Operations Research area, developing and solving adequate mathematical models, helps to make good decisions in EMS. We propose two variants of a Mixed Integer Linear Programming model for locating heterogeneous fleet vehicles to support different types of services in emergency medical care, taking into account the operational requirements of a health care service company in Colombia. The proposed models do not exactly match any of those found in the literature. The models are solved with Gurobi solver and the modeling language AMPL and they are successfully validated with historical data of the company under study and some estimates based on external sources. These obtained results are compared using an adaptation of the concept of Preparedness taken from the literature for ambulance positioning, as regard to measure the readiness of the system to the expected demand. The new results show that the relevance of each model depends of the prioritization of services and/or areas that the company considers.