Population Health Analytics

Course Description

The Population Health Analytics course provides students with the methodological and analytical skills required for competent evidence-based decision-making regarding population health improvement projects. Beginning with a review of current methods and an introduction to emerging methods for the generation and analysis of health data, such as precision medicine/”big data”, telemedicine/”digital health”, and spatial analysis/”hotspotting”, the course covers the major elements required for the evidence-based pursuit of population health goals. In particular, hands-on training is provided on how to synthesize evidence, via comprehensive systematic review methodologies, in the following 4 aspects of evidence-based decision-making: effectiveness, efficiency, feasibility, and appropriateness/meaningfulness. In addition, students will learn how to retrieve and summarize information about population health from major public health information systems in the U.S. Lectures and labs are aimed at developing hands-on skills for the management and analysis of health data using SPSS and other relevant statistical software programs, such as Open Meta Analyst (OMA) and the System for the Unified Management, Assessment and Review of Information (SUMARI). 3 credits Prerequisite: Admission to Graduate Public Health Program or Department Consent; HPH 501 and HPH 506 Grading Letter graded (A, A-, B+, etc.)

Code

HPH 562

Credits

3

Subject

HPH