L E Boulware1,2, G B Harris3, P Harewood4, F F Johnson1,5, P Maxson1, N Bhavsar1,2, S S Blackwelder6, S S Poley6, K Arnold6, B Akindele6, J Ferranti6, M Lyn1,5. 1. Center for Community and Population Health Improvement, Duke University Clinical and Translational Science Institute, Durham, NC 27701, USA. 2. Division of General Internal Medicine, Department of Medicine Duke University School of Medicine, Durham, NC 27701, USA. 3. Durham County Department of Public Health, Durham, NC 27701, USA. 4. Lincoln Community Health Center, Durham, NC 27707, USA. 5. Division of Community Health, Department of Community and Family Medicine, Duke University School of Medicine, Durham, NC 27701, USA. 6. Duke Health Technology Solutions, Duke Health, Durham, NC 27707, USA.
Abstract
BACKGROUND: Community health data are infrequently viewed in the context of social and environmental health determinants. We developed a novel data-sharing model to democratize health system data and to facilitate community and population health improvement. METHODS: Durham County, the City of Durham in North Carolina, Durham health systems and other stakeholders have developed a data-sharing model to inform local community health efforts. Aggregated health system data obtained through clinical encounters are shared publicly, providing data on the prevalence of health conditions of interest to the community. RESULTS: A community-owned web platform called the Durham Neighborhood Compass provides aggregate health data (e.g. on diabetes, heart disease, stroke and other conditions of interest) in the context of neighborhood social (e.g. income distribution, education level, demographics) and environmental (e.g. housing prices, crime rates, travel routes, school quality, grocery store proximity) contexts. Health data are aggregated annually to help community stakeholders track changes in health and health contexts over time. CONCLUSIONS: The Durham Neighborhood Compass is among the first collaborative public efforts to democratize health system data in the context of social and environmental health determinants. This model could be adapted elsewhere to support local community and population health improvement initiatives.
BACKGROUND: Community health data are infrequently viewed in the context of social and environmental health determinants. We developed a novel data-sharing model to democratize health system data and to facilitate community and population health improvement. METHODS: Durham County, the City of Durham in North Carolina, Durham health systems and other stakeholders have developed a data-sharing model to inform local community health efforts. Aggregated health system data obtained through clinical encounters are shared publicly, providing data on the prevalence of health conditions of interest to the community. RESULTS: A community-owned web platform called the Durham Neighborhood Compass provides aggregate health data (e.g. on diabetes, heart disease, stroke and other conditions of interest) in the context of neighborhood social (e.g. income distribution, education level, demographics) and environmental (e.g. housing prices, crime rates, travel routes, school quality, grocery store proximity) contexts. Health data are aggregated annually to help community stakeholders track changes in health and health contexts over time. CONCLUSIONS: The Durham Neighborhood Compass is among the first collaborative public efforts to democratize health system data in the context of social and environmental health determinants. This model could be adapted elsewhere to support local community and population health improvement initiatives.
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Authors: Susan E Spratt; Katherine Pereira; Bradi B Granger; Bryan C Batch; Matthew Phelan; Michael Pencina; Marie Lynn Miranda; Ebony Boulware; Joseph E Lucas; Charlotte L Nelson; Benjamin Neely; Benjamin A Goldstein; Pamela Barth; Rachel L Richesson; Isaretta L Riley; Leonor Corsino; Eugenia R McPeek Hinz; Shelley Rusincovitch; Jennifer Green; Anna Beth Barton; Carly Kelley; Kristen Hyland; Monica Tang; Amanda Elliott; Ewa Ruel; Alexander Clark; Melanie Mabrey; Kay Lyn Morrissey; Jyothi Rao; Beatrice Hong; Marjorie Pierre-Louis; Katherine Kelly; Nicole Jelesoff Journal: J Am Med Inform Assoc Date: 2017-04-01 Impact factor: 4.497
Authors: 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 Journal: J Clin Transl Endocrinol Date: 2015-01-14