Bull’s eye: Diabetes

Two universities take aim at diabetes in the Southeast

Officials at Duke University and the University of Michigan have their figurative arrows fletched – and the aim is to target diabetes in a serious way.

Leaders from Duke and the University of Michigan National Center for Geospatial Medicine will begin work on a $9.8 million innovation project on July 1 to reduce death and disability from Type 2 diabetes among 57,000 people in the Southeast.

The award is one of the 26 grants announced by the department of Health and Human Services on May 8. The project, titled “From Clinic to Community: Achieving Health Equity in the Southern United States,” is slated to span three years and save nearly $20.8 million.

The project hinges on a detailed IT program. Researchers will use predictive and geospatial medicine to regenerate four southeastern counties that are struggling with the expensive and debilitating spread of diabetes.

The project will incorporate four site partners spanning several states: Durham County Health Department (Durham County, N.C.), Cabarrus Health Alliance (Cabarrus County, N.C.), Mississippi Public Health Institute (Quitman County, N.C.), and Mingo County Health Department (Mingo County, W.V.).

“Geographically, diabetes is rooted most apparently in the southeastern U.S.,” said Marie Lynn Miranda, director of the University of Michigan National Center for Geospatial Medicine ¬– hence the project’s focus.

Population statistics of each site reflect this; approximately 27,000 citizens in Cabarrus County alone are at risk or have Type 2 diabetes, said Barbara Sheppard, senior director of Health and Community Initiatives at Cabarrus Health Alliance.

“We have an opportunity to create a healthier community and reduce burdensome costs associated with Type 2 diabetes morbidity and mortality,” she said.

To that end, the project will extract, transfer, and load patient record data from across site EHRs. Pairing patient information with publicly available socioeconomic information will generate risk algorithms on area neighborhoods, explained Ashley Dunham, project leader at the Duke Translational Medicine Institute.

“We can actually develop a risk algorithm which tells you, based on the healthcare that someone is receiving, how high or low risk they are, using a variety of indicators from their electronic health record,” she said.

The geospatial technology will allow for two kinds of interventions.

“We have a plan for a sophisticated information technology system that will feed into decision support,” said Miranda. This decision support will provide patient focus on high-risk individuals, as well as community-based interventions.

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