Methods and initial findings from the Durham Diabetes Coalition: Integrating geospatial health technology and community interventions to reduce death and disability

Susan E Spratt; Bryan C Batch; Lisa P Davis; Ashley A Dunham; Michele Easterling; Mark N Feinglos; Bradi B Granger; Gayle Harris; Michelle J Lyn; Pamela J Maxson; Bimal R Shah; Benjamin Strauss; Tainayah Thomas; Robert M Califf; Marie Lynn Miranda

doi:10.1016/j.jcte.2014.10.006

Methods and initial findings from the Durham Diabetes Coalition: Integrating geospatial health technology and community interventions to reduce death and disability

J Clin Transl Endocrinol. 2015 Jan 14;2(1):26-36. doi: 10.1016/j.jcte.2014.10.006. eCollection 2015 Mar.

Authors

Susan E Spratt¹, Bryan C Batch¹, Lisa P Davis^{2

3}, Ashley A Dunham^{2

3}, Michele Easterling⁴, Mark N Feinglos¹, Bradi B Granger⁵, Gayle Harris⁴, Michelle J Lyn⁶, Pamela J Maxson⁷, Bimal R Shah³, Benjamin Strauss⁷, Tainayah Thomas⁴, Robert M Califf^{2

3}, Marie Lynn Miranda^{7

8

9}

Affiliations

¹ Duke University Medical Center, Division of Endocrinology, Durham, NC, USA.
² Duke Translational Medicine Institute, Duke University, Durham, NC, USA.
³ Duke Clinical Research Institute, Duke University, Durham, NC, USA.
⁴ Durham County Department of Public Health, Durham, NC, USA.
⁵ Duke University School of Nursing, Duke University Health System, Durham, NC, USA.
⁶ Department of Community and Family Medicine, Duke University Medical Center, Durham, NC, USA.
⁷ School of Natural Resources and Environment, University of Michigan, Ann Arbor, MI, USA.
⁸ Department of Pediatrics, University of Michigan, Ann Arbor, MI, USA.
⁹ Department of Obstetrics & Gynecology, University of Michigan, Ann Arbor, MI, USA.

Abstract

Objective: The Durham Diabetes Coalition (DDC) was established in response to escalating rates of disability and death related to type 2 diabetes mellitus, particularly among racial/ethnic minorities and persons of low socioeconomic status in Durham County, North Carolina. We describe a community-based demonstration project, informed by a geographic health information system (GHIS), that aims to improve health and healthcare delivery for Durham County residents with diabetes.

Materials and methods: A prospective, population-based study is assessing a community intervention that leverages a GHIS to inform community-based diabetes care programs. The GHIS integrates clinical, social, and environmental data to identify, stratify by risk, and assist selection of interventions at the individual, neighborhood, and population levels.

Results: The DDC is using a multifaceted approach facilitated by GHIS to identify the specific risk profiles of patients and neighborhoods across Durham County. A total of 22,982 patients with diabetes in Durham County were identified using a computable phenotype. These patients tended to be older, female, African American, and not covered by private health insurance, compared with the 166,041 persons without diabetes. Predictive models inform decision-making to facilitate care and track outcomes. Interventions include: 1) neighborhood interventions to improve the context of care; 2) intensive team-based care for persons in the top decile of risk for death or hospitalization within the coming year; 3) low-intensity telephone coaching to improve adherence to evidence-based treatments; 4) county-wide communication strategies; and 5) systematic quality improvement in clinical care.

Conclusions: To improve health outcomes and reduce costs associated with type 2 diabetes, the DDC is matching resources with the specific needs of individuals and communities based on their risk characteristics.

Keywords: Barriers to diabetes care; CAARE, Case management of AIDS and Addiction through Resources and Education; CAB, community advisory board; Cardiovascular risk and diabetes; Community health; DDC, Durham Diabetes Coalition; DIO, diabetes information and communication officer; DSR, Decision Support Repository; Diabetes complications; Diabetes mellitus type 2; GHIS, geographic health information system; ICD-9, International Classification of Diseases, Ninth Revision; NHB, non-Hispanic black; NHW, non-Hispanic white; Population diabetes; SUPREME-DM, Surveillance, Prevention, and Management of Diabetes Mellitus; eMERGE, Electronic Medical Records and Genomics.