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Multi-Organizational Knowledge Based Approach Research

Award Information
Agency: Department of Health and Human Services
Branch: National Institutes of Health
Contract: 1R41RR018698-01A1
Agency Tracking Number: RR018698
Amount: $657,898.00
Phase: Phase I
Program: STTR
Solicitation Topic Code: N/A
Solicitation Number: N/A
Solicitation Year: N/A
Award Year: 2004
Award Start Date (Proposal Award Date): N/A
Award End Date (Contract End Date): N/A
Small Business Information
WESTON, MA 02493
United States
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 (617) 584-7323
Business Contact
Phone: (617) 584-7323
Research Institution
Tuscon, AZ 85722
United States

 Nonprofit College or University

DESCRIPTION (provided by applicant):
This Phase 1 STTR project will determine the feasibility of using web services, based on standard SOAP/XML (HL-7) protocols, to exchange Emergency Medical Services (EMS) field data with disparate hospital information systems. It will build upon a pre-hospital software package called iRevive, which consists of a network of wireless, handheld computers linked to a central database. The specific aims of the study address: 1) the business model, 2) the technical feasibility, and 3) the operational aspects of this information service.

The business model will delineate the patient care, economic, and societal benefits of a standardized approach to exchanging healthcare information. It will analyze the use of the Trusted Agent paradigm, in an effort to determine the optimal way for knowledge rovers to negotiate, access, process, and securely store healthcare information. The technical feasibility will center on the incorporation of a SOAP/XML messaging format into our system. Lastly we will deploy and field test a web services version of iRevive. This will include the application of emerging data mining and knowledge discovery techniques to demonstrate the feasibility of analyzing raw field data.

This project will foster the development of a coherent and continuous knowledge base of patient information that is capable of describing individual and population-based illness events, from the point of initial patient contact in the field to hospital discharge. It will serve as a platform for the development of a highly scalable, multi-organizational knowledge-based decision support system. This system will allow individual EMS systems to function locally, but act regionally, in response to a large scale event such as a multiple casualty incident (MCI) or mass casualty event (MCE). It will also aid in the development of new knowledge-based paradigms to enhance treatment algorithms and improve patient care.

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

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