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In 12 Navy-Marine Corps medical logistics studies and analyses conducted by the Naval Health Research Center (NHRC) and Teledyne Brown Engineering (TBE) over the past 5 years, estimates of battlefield mortality have been a major metric of interest to medical planners. An ongoing concern is how mortality is related to delays in treatment for medical logistics reasons. In this paper, we describe how NHRC and TBE have been developing a statistically based model for mortality since 2003, first starting with panel results from a group of military medical doctors and continuing here with an analysis of empirical injury data from Operation Iraqi Freedom (OIF). The panel results and statistical analysis of life-threatening injury data in OIF from early 2004 to mid-2006 indicate that the Weibull distribution describes the timing of high risk of mortality events in a reasonable manner within surgical medical treatment facilities. The quest for a best-fitting probability distribution with parameters dependent on the casualty flow chain of treatment and evacuation in the theater is ongoing. In reality, combining analytical and subject matter expert (SME) results to model mortality is necessary given the breadth of theater medical delivery systems and general paucity of adequate empirical data in many of the segments of patient flow.

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Advances in autonomous aircraft technology are spurring research into the different roles these aircraft could fill. The Office of Naval Research (ONR) is pursuing an Innovative Naval Prototype of an autonomous cargo aircraft in response to a United States Marine Corps Universal Needs Statement. Since the use of such a vehicle to evacuate casualties after delivering supplies is an obvious extension, ONR initiated research into how the functional characteristics of an aircraft such as speed, range, capacity, and number available affect how the aircraft performs as a patient movement platform. To evaluate aircraft functional characteristics we executed experiments with a patient movement simulation that explicitly models treatment, evacuation, and mortality as patients flow from the point of injury through definitive care. The experiments provide data, which was used to develop a response surface model of estimated patient mortality as a function of the casualty evacuation system characteristics. This response surface will be useful for comparing competing systems when currently unknown constraints such as total cost of ownership, volume, area, and weight are applied.

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