A mathematical model for efficient ambulance location based on DSM-MALP integration

Optimal location of medical facilities and vehicles is one of the most crucial aspects of emergency services such that even slight improvements in this regard can save the lives of many people. In the large cities suffering from fluctuating population distribution and traffic congestion, finding the optimal location of ambulance stations can significantly reduce patient mortality due to delay of medical service and thus increase the efficiency of the healthcare sector. This study investigated the current status of ambulance service provided in four districts of Isfahan city (Iran) and assessed the potential for improvement in availability by increasing the number of ambulances and relocating the stations. The main objective of this work is to integrate two ambulance location methods, ie, double standard model (DSM) and maximum availability location problem (MALP), to develop a static probabilistic model, which allows covering radius of stations to be increased according to ambulance availability factor. The efficiency of the developed method was assessed by sensitivity analysis through four different approaches, all indicating an increase in the efficiency compared to the default model.