Designing and evaluation of a location optimization model of emergency ambulance vehicles and stations based on Geographical Information Systems

Abstract

Background: Timeliness of emergency medical services (EMS) is critical for patient survival. In order to improve the efficiency of EMS systems we used Geographical Information Systems (GIS) approaches in three stages: (1) exploring epidemiology and spatio-temporal pattern of EMS enquires, (2) measuring spatial accessibility to EMS resources, and (3) developing a location-allocation model of existing and new ambulance vehicles.

Methods: This study was conducted in the county of Mashhad, the northeast of Iran, including 94 ambulance vehicles distributed across 74 EMS stations. Locations of demands were extracted using analysis of one-year EMS call data. Network analysis was employed to estimate the travel times. Various extensions of scan statistic approach were used to explore the spatio-temporal pattern of EMS enquiries. An enhanced age-integrated version of Two Step Floating Catchment Area (2SFCA) was developed to measure the potential accessibility of EMS resources. A maximal covering location problem (MCLP) model with a capacity threshold for vehicles was implemented to develop the location-allocation model. To make the proposed model more practical in the context of EMS, we added a constraint to the model formulation to maintain an acceptable service level for all EMS calls.

Results: The spatio-temporal clusters of EMS enquiries were indented during 11 a.m. to 11 p.m. in central parts of the city. The accessibility models showed a huge variation in terms of accessibility of EMS resources. Using the relocation model, the proportion of calls for service within the 5-minute coverage standard increased from 69% to 75%, ensuring all urban and rural service demands to be reached within 16 and 48 minutes, respectively. Our allocation model revealed that the coverage proportion could rise to 84% of the total call for service by adding ten vehicles and eight new stations.

Conclusions: Incorporating GIS approaches with optimization modeling has the potential to improve population health outcomes in real-world decision making regarding the accessibility and equity of health resource allocation including EMS services.

Keywords: Location-allocation, Geographical information system, Resource management, Emergency medical service, Maximal coverage location problem