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Optimal Spatial Design for Environmental Health Research

Initially funded by the Robert Wood Johnson Foundation, this project seeks to develop methods to support health care delivery and ultimately improve health outcomes by integrating GIS into health systems operations. Using GIS for spatial data management and analysis at an enterprise level can enable different types of health care providers to better understand their patient populations and tailor health care delivery to improve outcomes and efficiency. This entails the establishment of spatially enabled data architectures for health care organizations. Spatial data architecture facilitates the performance of small area analyses using GIS. Small area analysis can enable providers to better understand factors that affect the health status of their patient populations.

CEHI is collaborating with the Duke University Health System to develop methods to create a system-wide spatial data architecture. After establishing the initial data architecture, CEHI will work with physician-scientists to develop clinical applications. We have already begun work on heart failure and childhood overweight and obesity. CEHI will generate a standard methodology for building spatially based predictive risk models to guide prevention efforts and health care delivery. The models will highlight critical areas for targeted interventions, outreach and education. CEHI will craft models tailored to the different populations and approaches of county health departments, private care providers, and community organizations. The project focuses on low-income and minority populations, placing advanced technologies in service to those most vulnerable in our communities. The project continues with funding from the Duke Translational Medicine Institute through the National Institutes of Health's Clinical and Translational Science Awards (Robert Califf, PI).


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