Distributed Medical Training for Force Mobilization and Disaster Response

Award Information
Agency: Department of Defense
Branch: Navy
Contract: N00014-04-M-0068
Agency Tracking Number: O032-3072
Amount: $100,000.00
Phase: Phase I
Program: SBIR
Awards Year: 2004
Solicitation Year: 2003
Solicitation Topic Code: OSD03-DH07
Solicitation Number: 2003.2
Small Business Information
215 Parkway North, P.O. Box 280, Waterford, CT, 06385
DUNS: 077317766
HUBZone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: N
Principal Investigator
 Margaret Bailey
 Principal Investigator
 (860) 326-3621
Business Contact
 Denise Grudier
Title: Contracting Officer
Phone: (860) 326-3652
Email: dgrudier@sonalysts.com
Research Institution
Training is critically needed to prepare physicians of various specialties to perform trauma care when mobilized on military missions or operations. The goal of Sonalysts' and the University of Maryland's Medical Center is to design a scenario-driven, real-time, simulation-based training system to close the gap between prior experience and likely future demands on physicians' skills. Our research will focus specifically on training rapid evaluation of potential abdominal trauma by conducting a Focused Assessment with Sonography for Trauma (FAST) examination. We will examine the feasibility of integrating ultrasound simulations with existing medical, case-based, electronic tutoring software. We will conduct a task analysis of FAST medical diagnosis and design a training system that incorporates the latest in instructional methods. We will foster apprenticeship learning through a learn-by-doing approach, with training scenarios presented in a narrative format to provide engaging and authentic context. An online coach will provide analogical comparisons, automatically generated hints and immediate remedial feedback. Identifiable features on the ultrasound images will contain active links, and normal and abnormal patient ultrasounds will be viewable for comparison. Students may select virtual patient views from any of the predetermined FAST viewpoints. Self critiques may be compared with computer-generated intelligent critiques during opportunities for reflection.

* Information listed above is at the time of submission. *

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