3.0

credits

Average Course Rating

Introduces students to concepts, methods, and issues related to the application of data science to population health. Covers the uses of informatics to define and identify populations and sub-populations of interest, and describe the health status and needs of them. Describes the process of analyzing population health data from checking data quality to developing predictive models of utilization. Examines different data sources / methods to risk stratify a population of interest and compares the advantage and disadvantages of each data source / method. Describes various techniques to visualize data quality, depict the denominator selection process, and illustrate the risk adjustment results for large populations