We report our work in progress to create an experimental decision support architecture for evidence-based health policy planning employing open data records. It combines a population-level disease control and prevention simulation with de-identified data for patients hospitalized with diabetes in Albany County, New York, USA over a period of years. The geo-coding associated with this combined dataset is visualized through dynamic plots of neighborhood hot-spots over multiple years. This multi-model approach provides a novel tool for reflecting on historical data, policy choices and possible long-term outcomes in numeric and geo-space.
['Eliot Rich', 'David F. Andersen', 'William F. Augustine', 'Felipe Mendes Cronemberger', 'Katrina Hull', 'Luis F. Luna-Reyes', 'Roderick MacDonald', 'Mahdi M. Najafabadi', 'Smita Sharma', 'Carson Tao', 'James Houghton', 'Jack Homer', 'Xu Jianping']
An experimental platform for interpreting open-source health data though integration with dynamic disease models and geoplots