Medical Modeling and Simulation Based Training Return on Investment Decision Model

Modeling and simulation (M & S) technologies provide the capability for high-quality training in many areas of medicine while simultaneously reducing the costs and risks involved. However, M & S technologies require significant investment to realize their benefits, and it is crucial to have an appropriately designed system to best attain training objectives. The aim of this research is to develop an advanced software-based decision support tool to assess and compare the return on investment of different M & S-based training system designs that ultimately leads to the selection of the best possible tool. This tool will provide systematic guidance for clearly articulating training objectives, decomposing these objectives into quantifiable performance metrics, identifying potential system capabilities and components as well as costs, and finally tying each of these metrics together into a return on investment measure. This will enable critical system requirements to be identified and well-understood early in the lifecycle. Users will then be able to specify different training system designs and modify them interactively. This will provide the ability to objectively compare different designs and interactively see the effects of different design decisions on the performance metrics, cost, and ROI. In addition, the tool will provide automated design optimization capabilities to automatically generate a design that maximizes the ROI from user-identified candidate components, capabilities, and constraints. This may then be interactively modified by users as needed to arrive at a final design. Finally, the system will provide a generic application programming interface (API) for creating data integration modules. These modules may then be created as needed to facilitate integration with external systems and support automated data injection and formatting of information into the decision support tool as well as data exporting.