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A review on simulation models applied to emergency medical service operations

Author

Listed:
  • Zied Jemai

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

  • L. Aboueljinane

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

  • E. Sahin

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

Abstract

Emergency medical services (EMS) are public safety systems responsible for the pre-hospital stabilization and transport of seriously injured patients. The goal of such systems is to respond adequately to population calls by providing first aid services and transferring patients, when needed, to the emergency department of the appropriate hospital. In order to achieve this goal, a variety of tools (e.g. simulation, mathematical programming and queuing theory models) have been used to improve the performance of EMS. This paper focuses specifically on computer simulation models used for the analysis and improvement of EMS. In particular, we give a critical overview of the existing international literature on simulation models for EMS by pinpointing the issues considered, the associated modeling assumptions as well as the results obtained. Such a contribution is lacking in the current literature.

Suggested Citation

  • Zied Jemai & L. Aboueljinane & E. Sahin, 2013. "A review on simulation models applied to emergency medical service operations," Post-Print hal-01672393, HAL.
    • Handle: RePEc:hal:journl:hal-01672393
    DOI: 10.1016/j.cie.2013.09.017
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    Citations

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    Cited by:

    1. F. Javier Otamendi & David García-Heredia, 2015. "Isochrones as Indicators of the Influence of Traffic in Public Health: A Visual Simulation Application in Ávila, Spain," IJERPH, MDPI, vol. 12(10), pages 1-21, October.
    2. Fabbri, Cristiano & Lombardi, Michele & Malaguti, Enrico & Monaci, Michele, 2024. "On-line strategy selection for reducing overcrowding in an Emergency Department," Omega, Elsevier, vol. 127(C).
    3. Chang, Kuo-Hao & Chen, Tzu-Li & Yang, Fu-Hao & Chang, Tzu-Yin, 2023. "Simulation optimization for stochastic casualty collection point location and resource allocation problem in a mass casualty incident," European Journal of Operational Research, Elsevier, vol. 309(3), pages 1237-1262.
    4. Kaushal, Arjun & Zhao, Yuancheng & Peng, Qingjin & Strome, Trevor & Weldon, Erin & Zhang, Michael & Chochinov, Alecs, 2015. "Evaluation of fast track strategies using agent-based simulation modeling to reduce waiting time in a hospital emergency department," Socio-Economic Planning Sciences, Elsevier, vol. 50(C), pages 18-31.
    5. Ľudmila Jánošíková & Marek Kvet & Peter Jankovič & Lýdia Gábrišová, 2019. "An optimization and simulation approach to emergency stations relocation," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 27(3), pages 737-758, September.
    6. Ridler, Samuel & Mason, Andrew J. & Raith, Andrea, 2022. "A simulation and optimisation package for emergency medical services," European Journal of Operational Research, Elsevier, vol. 298(3), pages 1101-1113.
    7. Bélanger, V. & Lanzarone, E. & Nicoletta, V. & Ruiz, A. & Soriano, P., 2020. "A recursive simulation-optimization framework for the ambulance location and dispatching problem," European Journal of Operational Research, Elsevier, vol. 286(2), pages 713-725.
    8. Hamed Kazemipoor & Mohammad Ebrahim Sadeghi & Agnieszka Szmelter-Jarosz & Mohadese Aghabozorgi, 2022. "Providing a model for the issue of multi-period ambulance location," Papers 2206.11811, arXiv.org.
    9. Davide Duma & Roberto Aringhieri, 2020. "An ad hoc process mining approach to discover patient paths of an Emergency Department," Flexible Services and Manufacturing Journal, Springer, vol. 32(1), pages 6-34, March.
    10. Hainan Guo & David Goldsman & Kwok-Leung Tsui & Yu Zhou & Shui-Yee Wong, 2016. "Using simulation and optimisation to characterise durations of emergency department service times with incomplete data," International Journal of Production Research, Taylor & Francis Journals, vol. 54(21), pages 6494-6511, November.
    11. Bélanger, V. & Ruiz, A. & Soriano, P., 2019. "Recent optimization models and trends in location, relocation, and dispatching of emergency medical vehicles," European Journal of Operational Research, Elsevier, vol. 272(1), pages 1-23.
    12. Duma, Davide & Aringhieri, Roberto, 2023. "Real-time resource allocation in the emergency department: A case study," Omega, Elsevier, vol. 117(C).
    13. 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).
    14. Cildoz, Marta & Ibarra, Amaia & Mallor, Fermin, 2020. "Coping with stress in emergency department physicians through improved patient-flow management," Socio-Economic Planning Sciences, Elsevier, vol. 71(C).
    15. Nelas, José & Dias, Joana, 2020. "Optimal Emergency Vehicles Location: An approach considering the hierarchy and substitutability of resources," European Journal of Operational Research, Elsevier, vol. 287(2), pages 583-599.
    16. Alberto De Santis & Tommaso Giovannelli & Stefano Lucidi & Mauro Messedaglia & Massimo Roma, 2020. "An optimal non-uniform piecewise constant approximation for the patient arrival rate for a more efficient representation of the Emergency Departments arrival process," DIAG Technical Reports 2020-01, Department of Computer, Control and Management Engineering, Universita' degli Studi di Roma "La Sapienza".
    17. Suriyaphong Nilsang & Chumpol Yuangyai & Chen-Yang Cheng & Udom Janjarassuk, 2019. "Locating an ambulance base by using social media: a case study in Bangkok," Annals of Operations Research, Springer, vol. 283(1), pages 497-516, December.
    18. Carvalho, A.S. & Captivo, M.E. & Marques, I., 2020. "Integrating the ambulance dispatching and relocation problems to maximize system’s preparedness," European Journal of Operational Research, Elsevier, vol. 283(3), pages 1064-1080.
    19. 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.
    20. 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.
    21. Inkyung Sung & Taesik Lee, 2018. "Scenario-based approach for the ambulance location problem with stochastic call arrivals under a dispatching policy," Flexible Services and Manufacturing Journal, Springer, vol. 30(1), pages 153-170, June.
    22. Mohammad Reza Davahli & Waldemar Karwowski & Redha Taiar, 2020. "A System Dynamics Simulation Applied to Healthcare: A Systematic Review," IJERPH, MDPI, vol. 17(16), pages 1-27, August.
    23. Li, Mengyu & Carter, Alix & Goldstein, Judah & Hawco, Terence & Jensen, Jan & Vanberkel, Peter, 2021. "Determining ambulance destinations when facing offload delays using a Markov decision process," Omega, Elsevier, vol. 101(C).
    24. Mengyu Li & Peter Vanberkel & Alix J. E. Carter, 2019. "A review on ambulance offload delay literature," Health Care Management Science, Springer, vol. 22(4), pages 658-675, December.

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