Resource-Based Patient Prioritization in Mass-Casualty Incidents

Alex F. Mills (), Nilay Tanık Argon () and Serhan Ziya ()
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Alex F. Mills: Operations and Decision Technologies, Kelley School of Business, Indiana University, Bloomington, Indiana 47405
Nilay Tanık Argon: Department of Statistics and Operations Research, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599
Serhan Ziya: Department of Statistics and Operations Research, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599

Manufacturing & Service Operations Management, 2013, vol. 15, issue 3, 361-377

Abstract: The most widely used standard for mass-casualty triage, START, relies on a fixed-priority ordering among different classes of patients, and does not explicitly consider resource limitations or the changes in survival probabilities with respect to time. We construct a fluid model of patient triage in a mass-casualty incident that incorporates these factors and characterize its optimal policy. We use this characterization to obtain useful insights about the type of simple policies that have a good chance to perform well in practice, and we demonstrate how one could develop such a policy. Using a realistic simulation model and data from emergency medicine literature, we show that the policy we developed based on our fluid formulation outperforms START in all scenarios considered, sometimes substantially.

Keywords: health operations; emergency response; triage (search for similar items in EconPapers)
Date: 2013
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Citations: View citations in EconPapers (19)

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Persistent link: https://EconPapers.repec.org/RePEc:inm:ormsom:v:15:y:2013:i:3:p:361-377

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