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The role of preparedness in ambulance dispatching

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  • S Lee

    (School of Industrial Engineering, Purdue University, Indiana, USA)

Abstract

Response time in the emergency medical service is an important performance measure and ambulance dispatching is one of the most important factors affecting the response time. The most commonly used dispatching rule is to send the closest available unit to the call site. However, though dispatching the closest unit enables the service to achieve the minimal response time for the current call, the response times for the next incoming calls may increase if the area where the closest ambulance is currently located has a high call rate, that is the area becomes ill-prepared. A dispatching algorithm based on the preparedness concept was recently proposed. Rather than greedily minimizing each current response time, the dispatching algorithm takes account of future calls by a quantitative definition of preparedness. This study investigates the role of preparedness by examining the performance of the preparedness-based dispatching algorithm as well as by evolving the algorithm in several ways in order to magnify the effectiveness of preparedness consideration. As a result of these efforts, it is found that the consideration of preparedness in ambulance dispatching can provide significant benefits in reducing response time but only when appropriately used.

Suggested Citation

  • S Lee, 2011. "The role of preparedness in ambulance dispatching," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(10), pages 1888-1897, October.
    • Handle: RePEc:pal:jorsoc:v:62:y:2011:i:10:p:1888-1897
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    Citations

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    Cited by:

    1. Wang, Wei & Wang, Shuaian & Zhen, Lu & Qu, Xiaobo, 2022. "EMS location-allocation problem under uncertainties," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 168(C).
    2. Akbari, Leilanaz & Kazemi, Ahmad & Salari, Majid, 2023. "Operational planning of vehicles for rescue and relief operations considering the unavailability of the relocated vehicles," Socio-Economic Planning Sciences, Elsevier, vol. 88(C).
    3. Sardar Ansari & Laura Albert McLay & Maria E. Mayorga, 2017. "A Maximum Expected Covering Problem for District Design," Transportation Science, INFORMS, vol. 51(1), pages 376-390, February.
    4. 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.
    5. Robbins, Matthew J. & Jenkins, Phillip R. & Bastian, Nathaniel D. & Lunday, Brian J., 2020. "Approximate dynamic programming for the aeromedical evacuation dispatching problem: Value function approximation utilizing multiple level aggregation," Omega, Elsevier, vol. 91(C).
    6. Seokcheon Lee, 2017. "A new preparedness policy for EMS logistics," Health Care Management Science, Springer, vol. 20(1), pages 105-114, March.
    7. van Barneveld, T.C. & Bhulai, S. & van der Mei, R.D., 2016. "The effect of ambulance relocations on the performance of ambulance service providers," European Journal of Operational Research, Elsevier, vol. 252(1), pages 257-269.
    8. 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.

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