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Modelling Hospital Strategies in City-Scale Ambulance Dispatching

2022/01/05 by Xinyu Fu, Fu, Xinyu, Valeria V. Krzhizhanovskaya +5
Business, Management and Accounting · Economics, Econometrics and Finance · Health Professions · #Computer Science and Game Theory (cs.GT) #Computers and Society (cs.CY) #FOS: Computer and information sciences #Facility Location and Emergency Management #Healthcare Operations and Scheduling Optimization #Insurance and Financial Risk Management

paper · pdf · doi:10.48550/arxiv.2201.01846

openalex publication_date 2022/01/05 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

The optimisation in the ambulance dispatching process is significant for patients who need early treatments. However, the problem of dynamic ambulance redeployment for destination hospital selection has rarely been investigated. The paper proposes an approach to model and simulate the ambulance dispatching process in multi-agents healthcare environments of large cities. The proposed approach is based on using the coupled game-theoretic (GT) approach to identify hospital strategies (considering hospitals as players within a non-cooperative game) and performing discrete-event simulation (DES) of patient delivery and provision of healthcare services to evaluate ambulance dispatching (selection of target hospital). Assuming the collective nature of decisions on patient delivery, the approach assesses the influence of the diverse behaviours of hospitals on system performance with possible further optimisation of this performance. The approach is studied through a series of cases starting with a simplified 1D model and proceeding with a coupled 2D model and real-world application. The study considers the problem of dispatching ambulances to patients with the ACS directed to the PCI in the target hospital. A real-world case study of data from Saint Petersburg (Russia) is analysed showing the better conformity of the global characteristics (mortality rate) of the healthcare system with the proposed approach being applied to discovering the agents' diverse behaviour.

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