Abstract
This paper deals with optimizing the location of ambulance stations in a two-tiered emergency medical system in an urban environment. Several variants of station distribution are calculated by different mathematical programming models and are evaluated by a detailed computer simulation model. A new modification of the modular capacitated location model is proposed. Two ways of demand modelling are applied; namely, the aggregation of the ambient population and the aggregation of permanent residents at the street level. A case study of the city of Prešov, Slovakia is used to assess the models. The performance of the current and proposed sets of locations is evaluated using real historical data on ambulance trips. Computer simulation demonstrates that the modular capacitated location model, with the ambient population demand, significantly reduces the average response time to high-priority patients (by 79 s in the city and 62 s in the district) and increases the percentage of high-priority calls responded to within 8 min (by almost 4% in the city and 5% in the district). Our findings show that a significant improvement in the availability of the service can be achieved when ambulances are not accumulated at a few stations but rather spread over the city territory.
Highlights
Emergency medical services (EMS) play the main role in pre-hospital medical care.Their goal is to provide timely and appropriate treatment to patients with emergency medical conditions and transport them to the nearest appropriate healthcare facility
The average expected response time is calculated by dividing the objective function of the expected response time model (ERTM) model by the total number of potential patients
We evaluate the performance of the location models based on the LandScan distribution of demand in the city of Prešov
Summary
Emergency medical services (EMS) play the main role in pre-hospital medical care. Their goal is to provide timely and appropriate treatment to patients with emergency medical conditions and transport them to the nearest appropriate healthcare facility. The ambulance location is an optimization problem that deals with the location of the base stations where the vehicles providing emergency medical services are housed. The importance of sitting emergency facilities has not diminished over the years because population ageing leads to a growing demand for healthcare, including urgent pre-hospital care [4,5]. The increasing availability of demographic, geographical, and transportation data allows for designing better optimization location models [6]. Mathematical programming solvers such as CPLEX and Gurobi are constantly being improved, and they are becoming more able to solve more complicated models, e.g., [7]
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