Democratizing health system data to impact social and environmental health contexts: a novel collaborative community data-sharing model

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 o...

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Veröffentlicht in:Journal of public health (Oxford, England) England), 2020-11, Vol.42 (4), p.784-792
Hauptverfasser: Boulware, L E, Harris, G B, Harewood, P, Johnson, F F, Maxson, P, Bhavsar, N, Blackwelder, S S, Poley, S S, Arnold, K, Akindele, B, Ferranti, J, Lyn, M
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Sprache:eng
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Zusammenfassung: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.
ISSN:1741-3842
1741-3850
DOI:10.1093/pubmed/fdz171