Metadata assisted Management of Diabetes in Rural Health Disparity Communities

Award Information
Agency: Department of Agriculture
Branch: N/A
Contract: 2012-00086
Agency Tracking Number: 2012-00086
Amount: $99,832.00
Phase: Phase I
Program: SBIR
Awards Year: 2012
Solitcitation Year: 2012
Solitcitation Topic Code: 8.6
Solitcitation Number: USDA-NIFA-SBIR-003497
Small Business Information
AUTOMATED MEDICAL DIAGNOSTICS, LLC
6415 RIVER TIDE DRIVE, Memphis, TN, 38120-2601
Duns: 809106342
Hubzone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: N
Principal Investigator
 Derek Austin
 Director
 (865) 566-3912
 daustin@hubbletelemedical.com
Business Contact
 Ed Chaum
Title: Chief Medical Officer
Phone: (901) 448-3638
Email: echaum@hubbletelemedical.com
Research Institution
 Stub
Abstract
Diabetes is an epidemic disease in the United States and accounts for 15% of all US healthcare costs. The rural Mississippi Delta region is statistically at the epicenter of the negative trends in the health and has the highest prevalence of diabetes and obesity in the nation. Low health literacy and limited access to healthcare resources are critical socioeconomic barriers to those patients at the greatest risk for complications of diabetes, and are not met by current healthcare delivery models. As an emerging technology, telemedicine is an efficient, cost-effective way to deliver healthcare services to rural, health disparity communities. Hubble Telemedical currently provides remote management of diabetic retinopathy in the Delta and elsewhere using images acquired in the primary care setting through its award winning TRIAD Network. This proposal leverages an ongoing partnership with the Delta Health Alliance (Stoneville, MS) to implement a translational, population-based diabetes management program in the Delta. The goal of this Phase I study is to leverage our expertise in medical data networking and analysis to employ a proprietary web-based software interface with DHA electronic health records and test the feasibility of using automated clinical metadata analysis to identify and more effectively manage those children and adults at highest risk for the complications of diabetes, hypertension, stroke, and obesity due to poor health care compliance, blood sugar control, and co-morbidity. Our ultimate goal is to target these high risk patients for medical and behavioral intervention in a cost-effective approach to improving health outcomes in rural America.

* information listed above is at the time of submission.

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