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Prioritizing Burn-Injured Patients During a Disaster

Author

Listed:
  • Carri W. Chan

    (Decision, Risk, and Operations, Columbia Business School, Columbia University, New York, New York 10027)

  • Linda V. Green

    (Decision, Risk, and Operations, Columbia Business School, Columbia University, New York, New York 10027)

  • Yina Lu

    (Decision, Risk, and Operations, Columbia Business School, Columbia University, New York, New York 10027)

  • Nicole Leahy

    (New York-Presbyterian Hospital/Weill Cornell Medical Center, New York, New York 10065)

  • Roger Yurt

    (New York-Presbyterian Hospital/Weill Cornell Medical Center, New York, New York 10065)

Abstract

The U.S. government has mandated that, in a catastrophic event, metropolitan areas need to be capable of caring for 50 burn-injured patients per million population. In New York City, this corresponds to 400 patients. There are currently 140 burn beds in the region, which can be surged up to 210. To care for additional patients, hospitals without burn centers will be used to stabilize patients until burn beds become available. In this work, we develop a new system for prioritizing patients for transfer to burn beds as they become available and demonstrate its superiority over several other triage methods. Based on data from previous burn catastrophes, we study the feasibility of being able to admit 400 patients to burn beds within the critical three- to five-day time frame. We find that this is unlikely and that the ability to do so is highly dependent on the type of event and the demographics of the patient population. This work has implications for how disaster plans in other metropolitan areas should be developed.

Suggested Citation

  • Carri W. Chan & Linda V. Green & Yina Lu & Nicole Leahy & Roger Yurt, 2013. "Prioritizing Burn-Injured Patients During a Disaster," Manufacturing & Service Operations Management, INFORMS, vol. 15(2), pages 170-190, May.
    • Handle: RePEc:inm:ormsom:v:15:y:2013:i:2:p:170-190
    DOI: 10.1287/msom.1120.0412
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    References listed on IDEAS

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    1. Lawrence M. Wein & Youngsoo Choi & Sylvie Denuit, 2010. "Analyzing Evacuation Versus Shelter‐in‐Place Strategies After a Terrorist Nuclear Detonation," Risk Analysis, John Wiley & Sons, vol. 30(9), pages 1315-1327, September.
    2. Eva K. Lee & Chien-Hung Chen & Ferdinand Pietz & Bernard Benecke, 2009. "Modeling and Optimizing the Public-Health Infrastructure for Emergency Response," Interfaces, INFORMS, vol. 39(5), pages 476-490, October.
    3. Nilay Tan{i}k Argon & Serhan Ziya, 2009. "Priority Assignment Under Imperfect Information on Customer Type Identities," Manufacturing & Service Operations Management, INFORMS, vol. 11(4), pages 674-693, June.
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    Citations

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    Cited by:

    1. Carri W. Chan & Linda V. Green & Suparerk Lekwijit & Lijian Lu & Gabriel Escobar, 2019. "Assessing the Impact of Service Level When Customer Needs Are Uncertain: An Empirical Investigation of Hospital Step-Down Units," Management Science, INFORMS, vol. 65(2), pages 751-775, February.
    2. Qiuping Yu & Gad Allon & Achal Bassamboo & Seyed Iravani, 2018. "Managing Customer Expectations and Priorities in Service Systems," Management Science, INFORMS, vol. 64(8), pages 3942-3970, August.
    3. Saghafian, Soroush & Trichakis, Nikolaos & Zhu, Ruihao & Shih, Helen A., 2019. "Joint Patient Selection and Scheduling under No-Shows: Theory and Application in Proton Therapy," Working Paper Series rwp19-019, Harvard University, John F. Kennedy School of Government.
    4. Michael Freeman & Susan Robinson & Stefan Scholtes, 2021. "Gatekeeping, Fast and Slow: An Empirical Study of Referral Errors in the Emergency Department," Management Science, INFORMS, vol. 67(7), pages 4209-4232, July.
    5. Tinglong Dai & Sridhar Tayur, 2020. "OM Forum—Healthcare Operations Management: A Snapshot of Emerging Research," Manufacturing & Service Operations Management, INFORMS, vol. 22(5), pages 869-887, September.
    6. 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.
    7. Farahani, Reza Zanjirani & Lotfi, M.M. & Baghaian, Atefe & Ruiz, Rubén & Rezapour, Shabnam, 2020. "Mass casualty management in disaster scene: A systematic review of OR&MS research in humanitarian operations," European Journal of Operational Research, Elsevier, vol. 287(3), pages 787-819.
    8. Adam N. Elmachtoub & Paul Grigas, 2022. "Smart “Predict, then Optimize”," Management Science, INFORMS, vol. 68(1), pages 9-26, January.
    9. R. K. Jha & B. S. Sahay & P. Charan, 2016. "Healthcare operations management: a structured literature review," DECISION: Official Journal of the Indian Institute of Management Calcutta, Springer;Indian Institute of Management Calcutta, vol. 43(3), pages 259-279, September.
    10. Pinar Keskinocak & Nicos Savva, 2020. "A Review of the Healthcare-Management (Modeling) Literature Published in Manufacturing & Service Operations Management," Manufacturing & Service Operations Management, INFORMS, vol. 22(1), pages 59-72, January.

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