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Cost-effective analyses for emergency medical services deployment: A case study in Shanghai

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  • Su, Qiang
  • Luo, Qinyi
  • Huang, Samuel H.

Abstract

The response speed of emergency medical services (EMS) is extremely critical for pre-hospital lifesaving. Each second plays a vital role in emergent cases. Therefore, the EMS network should be carefully designed to provide timely and reliable services. This paper focuses on improving the classical ambulance deployment method to optimize the distribution of first-aid resources. We refine the double coverage model with a new objective function that minimizes the expected cost for delayed emergencies plus the operational cost for EMS. EMS operators can use this refined model to analyze the cost-effectiveness of the emergency network, as demonstrated in a real-world EMS deployment case study. To solve this large-scale integer-programming problem, we compared several heuristic algorithms and finally chose ant colony optimization algorithm. Several modifications are made to adapt the traditional ant colony algorithm to solve our problem. The paper concludes with an optimized and cost-effective plan for ambulance deployment in the downtown area of Shanghai. After optimization, the objective cost is lowered by about 11% each year and 10% less emergency calls are missed or delayed. In addition, we use our modified model to test scenarios with relaxed limit of resources. Potential improvement of future EMS network is discovered. It turns out that increasing the number of first-aid stations from 35 (current number of stations) to 50 and adding 10 vehicles will achieve a surprising 49% cost saving while maintaining a satisfactory service level.

Suggested Citation

  • Su, Qiang & Luo, Qinyi & Huang, Samuel H., 2015. "Cost-effective analyses for emergency medical services deployment: A case study in Shanghai," International Journal of Production Economics, Elsevier, vol. 163(C), pages 112-123.
    • Handle: RePEc:eee:proeco:v:163:y:2015:i:c:p:112-123
    DOI: 10.1016/j.ijpe.2015.02.015
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    3. ShuJie Liao & Haiting Tu & Cheng Hu & Wulin Pan & Jianwu Xiong & Dongyang Yu & Lei Jing & Wei Pan, 2019. "Fuzzy multi-objective medical service organization selection model considering limited resources and stochastic demand in emergency management," PLOS ONE, Public Library of Science, vol. 14(3), pages 1-15, March.
    4. Junhu Ruan & Felix T. S. Chan & Xiaofeng Zhao, 2018. "Re-Planning the Intermodal Transportation of Emergency Medical Supplies with Updated Transfer Centers," Sustainability, MDPI, vol. 10(8), pages 1-20, August.
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    6. Shayesta Wajid & N. Nezamuddin, 2023. "Optimizing emergency services for road safety using a decomposition method: a case study of Delhi," OPSEARCH, Springer;Operational Research Society of India, vol. 60(1), pages 155-173, March.

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