Population Health Informatics intersects with epidemiology and informatics to provide a framework for collecting, analyzing, reporting, and ultimately responding to emerging public health events. To fully realize an educational opportunity, the course is taught with freely available, anonymous surveillance data. Students learn the basics of data science programming for population health, concepts of clinical epidemiology and epidemiologic surveillance, and evaluation of informatics systems. Over the 10-week course, students submit and present 6 discussion board topics relating to stakeholder engagement and system design, case definition performance, baseline preparation, anomaly detection, public health response, and visualization. In addition, students prepare a final project either developing an informatics tool for population health professionals or employing advanced data science methods on population health data. Over the course of 5 quarters, Master's level students have submitted weekly evaluations of the course as it develops. Both quantitative and qualitative measures were analyzed to understand the overall rating of the course, knowledge gained, challenges faced, and ways to make the topic more engaging. Future plans to improve the course design will also be discussed.
Nicholas Soulakis (Presenter)
Northwestern University Feinberg School of Medicine