The Autumn 2026 class will be offered in person.

– 2026 Teaching team: Nigam Shah, Maya Drusinsky, Bridget Lin, Alan Mao, Vivian Utti

This course is designed to prepare you to pose and answer meaningful clinical questions using routinely collected healthcare data. The practical skills you will learn in this class will be applicable to any task involving data manipulation and analysis. The course will use real, de-identified, large size patient datasets for home work projects associated with the course. To have the best learning experience, you will need to be proficient in R or Python.

Schedule: TUE, THU 3:00 PM - 4:20 PM in CoDa B60.
See the Canvas site (log in with your SUNet id), for office hours, contact information, Syllabus, Prerequisites etc.

Upon completing this course, you should be able to:

1. recognize categories of research questions and the study designs used to address them.
2. describe common healthcare data sources and their relative advantages and limitations.
3. extract and transform various kinds of clinical data to create analysis-ready datasets.
4. design and execute an analysis of a clinical dataset to answer a research question.
5. apply your knowledge to evaluate and criticize published clinical informatics research.