Social network analysis and GIS, mapping community health using secondary data: An exploratory analysis

People live in complex, interconnected, and dynamic settings.  System models suggest that among the important determinants of community health are the physical or built environments and dynamic, complex, adaptive social systems in which they are situated.  Novel research methodologies such as social network analysis have the potential to inform environmental, economic, policy and social determinants.  There are few reported attempts to use network methods to actually construct a network profile of communities using secondary data.  Healthcare is experiencing an explosion of data due to the adoption of electronic health records and information systems.  Network modeling research has generally constrained observational units to agents or individuals.  By shifting the observational unit of analysis to patient health outcomes from administrative claims data, network analysis may provide useful insights into underlying determinants of community health.  Little research to date has examined the validity of this methodology in community health planning.  The objective of this presentation is to define a graph theoretic data structure, describe the network properties, evaluate how the network characteristics vary across space and time, then compare and contrast corresponding health outcomes across communities.  This exploratory analysis incorporates a network based approach with spatial analysis and GIS mapping tools. Findings demonstrate how health outcomes and co-morbidity relationships vary across space and time, revealing a profile of community health not readily apparent from studying individuals; and visualization and statistical metrics that provide useful insights into environmental, economic, policy and social determinants of community health.