Abstract
Abstract Effective treatment of acute coronary syndrome (ACS) patients depends on the transportation time to a hospital. But selection of an optimal route and target hospital for an ambulance within a large city is a complex problem. It requires taking into account the dynamical nature of an urban environment. Such dynamic factors as traffic flow, changing road graph, population mobility, and hospital capabilities are sources of uncertainty in decision making on hospitalization, and eventually they influence the functioning quality of emergency medical services (EMS) in a city. This work is devoted to the analysis of this problem for the city of Saint-Petersburg (Russia) with the use of statistical data, public geographic information services (OpenStreetMap), and real-time data on traffic flow (Yandex.Maps). It is shown that dynamic traffic conditions influence selection of a hospital and have to be considered within the task of ambulance routing. The results may be applied in order to design a more efficient EMS decision support system for ambulance personnel and dispatchers.
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