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Optimal service order for mass-casualty incident response

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  • Kamali, Behrooz
  • Bish, Douglas
  • Glick, Roger

Abstract

In the aftermath of a mass-casualty incident, one of the first steps in the response is to triage the casualties. Triage systems categorize the casualties based on criticality, and then prioritize casualties for transfer to hospitals for further treatment. The prioritization is usually based on simply ordering the casualty types without considering the available resources to transport them and the scale of the disaster. These factors can significantly affect the outcome of the rescue efforts. In this research we study a mathematical model to incorporate the above mentioned factors in the triage process. We assume a disaster location with a set of casualties, categorized by criticality and care requirements, that must be transported to hospitals in the region using a fleet of available ambulances. The goal is to maximize the expected number of survivors. We analyze the structure of the optimal solution to this problem, and compare the performance of the model with the current practice and other related models in the literature.

Suggested Citation

  • Kamali, Behrooz & Bish, Douglas & Glick, Roger, 2017. "Optimal service order for mass-casualty incident response," European Journal of Operational Research, Elsevier, vol. 261(1), pages 355-367.
    • Handle: RePEc:eee:ejores:v:261:y:2017:i:1:p:355-367
    DOI: 10.1016/j.ejor.2017.01.047
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    References listed on IDEAS

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    1. Evin Uzun Jacobson & Nilay Tanık Argon & Serhan Ziya, 2012. "Priority Assignment in Emergency Response," Operations Research, INFORMS, vol. 60(4), pages 813-832, August.
    2. Alex F. Mills & Nilay Tanık Argon & Serhan Ziya, 2013. "Resource-Based Patient Prioritization in Mass-Casualty Incidents," Manufacturing & Service Operations Management, INFORMS, vol. 15(3), pages 361-377, July.
    3. Li, Dong & Glazebrook, Kevin D., 2011. "A Bayesian approach to the triage problem with imperfect classification," European Journal of Operational Research, Elsevier, vol. 215(1), pages 169-180, November.
    4. Dean, Matthew D. & Nair, Suresh K., 2014. "Mass-casualty triage: Distribution of victims to multiple hospitals using the SAVE model," European Journal of Operational Research, Elsevier, vol. 238(1), pages 363-373.
    5. Armann Ingolfsson & Susan Budge & Erhan Erkut, 2008. "Optimal ambulance location with random delays and travel times," Health Care Management Science, Springer, vol. 11(3), pages 262-274, September.
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    Cited by:

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    2. Shuwan Zhu & Wenjuan Fan & Shanlin Yang & Panos M. Pardalos, 2023. "Scheduling operating rooms of multiple hospitals considering transportation and deterioration in mass-casualty incidents," Annals of Operations Research, Springer, vol. 321(1), pages 717-753, February.
    3. Elmira Farrokhizadeh & Seyed Amin Seyfi-Shishavan & Sule Itir Satoglu, 2022. "Blood supply planning during natural disasters under uncertainty: a novel bi-objective model and an application for red crescent," Annals of Operations Research, Springer, vol. 319(1), pages 73-113, December.
    4. Atefe Baghaian & M. M. Lotfi & Shabnam Rezapour, 2022. "Integrated deployment of local urban relief teams in the first hours after mass casualty incidents," Operational Research, Springer, vol. 22(4), pages 4517-4555, September.
    5. Shuwan Zhu & Wenjuan Fan & Xueping Li & Shanlin Yang, 2023. "Ambulance dispatching and operating room scheduling considering reusable resources in mass-casualty incidents," Operational Research, Springer, vol. 23(2), pages 1-37, June.
    6. Liu, Yang & Cui, Na & Zhang, Jianghua, 2019. "Integrated temporary facility location and casualty allocation planning for post-disaster humanitarian medical service," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 128(C), pages 1-16.
    7. Rezapour, Shabnam & Naderi, Nazanin & Morshedlou, Nazanin & Rezapourbehnagh, Shaghayegh, 2018. "Optimal deployment of emergency resources in sudden onset disasters," International Journal of Production Economics, Elsevier, vol. 204(C), pages 365-382.

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