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Reducing ambulance response time using simulation: The case of Val-de-Marne department emergency medical service

Author

Listed:
  • Zied Jemai

    (LGI - Laboratoire Génie Industriel - EA 2606 - CentraleSupélec)

  • Lina Aboueljinane

    (LGI - Laboratoire Génie Industriel - EA 2606 - CentraleSupélec)

  • Evren Sahin

    (LGI - Laboratoire Génie Industriel - EA 2606 - CentraleSupélec)

Abstract

The French Emergency Medical service, known as SAMU, is responsible for providing permanent phone support and dispatching the proper response for emergency requests. The response time required for an ambulance's arrival at the scene following a call is an important performance indicator in determining the quality of the SAMU system since this may be directly related to patient's survival. In this paper, discrete simulation techniques are used to model the SAMU of the Val-de-Marne department (France) in order to investigate several alternative configurations for potential improvements. Scenarios consist of adding more resources, relocating existing teams and reducing processing times in order to improve response time. We found that repositioning part of the existing teams into potential stations increased average percentage of calls covered within the 20-minutes criterion up to 4.8%. This improvement in coverage reaches 5.2% when reducing the regulation processing time by 20%.

Suggested Citation

  • Zied Jemai & Lina Aboueljinane & Evren Sahin, 2012. "Reducing ambulance response time using simulation: The case of Val-de-Marne department emergency medical service," Post-Print hal-01672421, HAL.
    • Handle: RePEc:hal:journl:hal-01672421
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    Cited by:

    1. Colla, Marcos & Santos, Gilson Ditzel & Oliveira, Gilson Adamczuk & de Vasconcelos, Renata Braga Berenguer, 2023. "Ambulance response time in a Brazilian emergency medical service," Socio-Economic Planning Sciences, Elsevier, vol. 85(C).
    2. Karatas, Mumtaz & Yakıcı, Ertan, 2019. "An analysis of p-median location problem: Effects of backup service level and demand assignment policy," European Journal of Operational Research, Elsevier, vol. 272(1), pages 207-218.
    3. Rania Boujemaa & Aida Jebali & Sondes Hammami & Angel Ruiz & Hanen Bouchriha, 2018. "A stochastic approach for designing two-tiered emergency medical service systems," Flexible Services and Manufacturing Journal, Springer, vol. 30(1), pages 123-152, June.
    4. Mumtaz Karatas & Nasuh Razi & Murat M. Gunal, 2017. "An ILP and simulation model to optimize search and rescue helicopter operations," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 68(11), pages 1335-1351, November.

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