public release; distribution is unlimited. This research has been conducted in compliance with all applicable federal regulations governing the protection of human subjects in research.
Summary ProblemModeling and simulation applications require accurate estimations of the number and type of injuries and illnesses.These estimates, called patient streams, include projections of the patient condition (PC) code frequencies needed for estimating medical resources for various types of military operations. They are the diagnostic nomenclature that modeling and simulation applications use. Currently, no quantitative process has been developed to estimate these patient streams.
ObjectiveThe objective of this research was to develop a methodology that links hospitalization data to the PC code nomenclature. In addition, patient streams resulting from specific causative agents would be estimated by associating the traumas and anatomical locations that result from a specific weapon. Finally, a tool using this quantitative approach would be developed that allows the user to select one of these methods to easily calculate the patient distributions.
ApproachTwo approaches to estimate PC code patient streams were addressed. The first approach linked trauma and anatomical location percentages to PC codes for selected operations. Diagnostic data obtained from Operation Iraqi Freedom (OIF) were grouped and coded to illustrate the estimation of a patient stream in terms of PC codes using the first approach. In the second approach, using OIF and Vietnam data, patient streams were estimated from the traumas resulting from the causative agents expected to be used by enemy forces.
ResultsThe Patient Condition Occurrence Frequency (PCOF) tool was developed to allow the user to estimate various patient distributions based on operation type or causative agent.
DiscussionThis study provides medical planners the ability to easily generate patient streams using a quantitative and a mathematical approach. These approaches provide patient streams from the different phases of OIF, and illustrate the potential application of the tool for generating patient streams for future operations in support of the global war on terror.2