SBIR-STTR Award

Non trauma surgeons mobilized to support military operations are often ill-prepared for the challenges of trauma surgery. Training to date has not bridged the gap between their experience and abilities and the rigor of their assignment. The objective of this research is to develop a training system that utilizes best known instructional practices and exploits advanced, distributed training technology to deliver comprehensive trauma surgery preparation. The components of this system are in place, and this research will focus on their integration. A comprehensive set of almost 200 trauma decision trees, developed for the Navy (Contract N66001-85-C-0297), will provide the foundation for the training content. An existing, robust online training delivery system that imbeds best teaching practices will provide the technology for delivery. The research will result in a case study based, online learning system that provides experiential learning to mobilized non trauma surgeons. Case studies will simulate combat trauma and disaster scenarios. Interactive and self paced instruction will provide challenges to surgeon trainees to make medical treatment decisions and to react to nuances in treatment response. Implementation would cost effectively prepare mobilized non trauma surgeons to face trauma scenarios, and to utilize proper treatment decision making.

Non trauma surgeons mobilized to support military operations are often ill prepared for the challenges of trauma surgery. Training to date has not bridged the gap between their experience and abilities and the rigor of their assignment. The objective of this research project is to develop a robust, modular, and deployable online training system proven to enhance the trauma training of non trauma surgeons. The work will be an extension and scaling up of the Phase I prototype, with the overlay of instructional research to maximize training effectiveness. The contingency-based and best practices trauma decision trees will be updated beyond airway management to include the other nine trauma modules, and a battery of case studies will be developed to provide experiential learning for simple and compound trauma. The resulting training system will be modular, self paced and interactive and will include electronic decision trees, tutorials, assessments and dozens of case studies. The system will be tested with military medical personnel in the United States, Afghanistan, and Iraq.

Keywords:
TRAUMA DECISION TREES ONLINE TRAINING WEB-BASED TRAINING ANALOGICAL ENCODING PATTERN RECOGNITION