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Tuesday, 17 October 2006


Eric B. Hollingsworth, BS, Wei Xiong, PhD, and Nathaniel Hupert, MD, MPH. Weill Medical College, Cornell University, New York, NY, NY

Purpose:  There are no general models describing the outcomes of mass casualty care at different levels of regional surge capacity.  We created a simulation model to assist decision making by quantifying the marginal benefit of additional treatment capacity under different casualty load and time-dependent mortality assumptions.

Methods:  We developed a discrete event simulation queueing model of mass casualty care by applying a standard triage protocol to a hypothetical population of variably injured patients and then evaluating outcomes based on three different time-dependent mortality rates derived from the medical literature.  Evidence-based casualty treatment times varied from 11 minutes for non-critical casualties triaged inappropriately to the ED, to 2 hours 55 minutes for critical casualty stabilization and operative management.  We defined a unit of treatment capacity as an emergency department trauma bay/operating room tandem (EDOR).

Results:  We found few reports of time-dependent mortality for casualties, and chose three representative curves: late (post-6 hours), linear (steady decline of ~12% per hour), and exponential (rapid decline after "golden hour").  We found a complex relationship between critical mortality and EDOR capacity depending on choice of mortality curve.  However, for a given mortality curve, outcomes are directly related to the ratio of event size to EDOR capacity.  The marginal benefit of additional surge capacity for mass casualty victims varies with event size and rate of time-dependent mortality.

Conclusions:  Our model highlights the importance of obtaining accurate time-dependent mortality rates for critically injured mass casualty patients to support evidence-based regional surge capacity planning.  Provided this information can be obtained, the model produces quantitative estimates of the surge capacity required to minimize mortality after a mass casualty event of a known size.


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See more of The 28th Annual Meeting of the Society for Medical Decision Making (October 15-18, 2006)