A method for assessing the health status of communities has been under development for a decade at the University of South Florida. Known as CATCH (Comprehensive Assessment for Tracking Community Health), the method utilizes health status indicators from multiple data sources. With federal grant support, a unique data warehouse has been created to automate CATCH assessments and to enhance online analytical processing for efficient data browsing, knowledge discovery, and model testing. A comparison of two peer grouping methods (population size versus predicted age-adjusted mortality) is reviewed to demonstrate the warehouse capabilities.
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