The Program offers six core courses on Pharmacoepidemiology, Introduction to Pharmacoepidemiology, Advanced Pharmacoepidemiology, Seminars in Drug Safety and CER, Health Services Research, and Propensity Scores.
Pharmacoepidemiology (EPI221, Fall1). Instructor: Dr. Alexander Walker. Within the framework of formal epidemiologic analysis, this course covers inference about the effects of pharmaceuticals from case reports, case series, vital statistics and other registration schemes, cohort studies, and case-control studies. Decision-making with inadequate data is examined from the perspectives of manufacturers and of regulators. Students are graded on the basis of group projects. This course is intended primarily for students wishing to pursue a career in the pharmaceutical industry or in national regulatory bodies, but may have more general interest as an applied mid-level course with a heavy methodological emphasis.
Advanced Pharmacoepidemiology (EPI286, Fall2). Instructors: Dr. Sebastian Schneeweiss and guest lecturers. Using current examples and with the participation of active researchers in pharmacoepidemiology, this course addresses a range of study designs and analytic techniques for observational studies on the utilization, safety, and effectiveness of pharmaceuticals. Students will develop an understanding of how to plan, implement, analyze, and criticize pharmacoepidemiologic studies. Original research will be presented by principal investigators, followed by intensive discussions on design options, analytic strategies, and sensitivity analyses of confounding and misclassification bias. Lectures will provide methodological background and will cover applied issues typically encountered in pharmacoepidemiology. This course is intended primarily for graduate students considering a career in the pharmaceutical/biotech industry, pharmaceutical benefits management, or in national regulatory bodies.
Epi Methods in Health Services Research Epidemiology (EPI235, Spring1) Instructors: Dr. Sebastian Schneeweiss. The course is designed to introduce students to the application of standard epidemiologic methods to Health Services Research. Students will learn to recognize the principles of Epidemiology in Health Services Research and understand the terminology and methods specific to the field. Threats to validity including confounding, selection bias, information bias, and methods for their control will be discussed in a variety of settings, both in the U.S. and around the world, emphasizing practical considerations. Lectures will include recent newsworthy case studies and examples from the literature. Topics include strategic planning, quality control and management, risk adjustment, benchmarking, outcomes and comparative effectiveness research, geographic information systems, and health program evaluation. The clinical, economic, and polcy impact of health serves research will be discussed.
Effective Research with Longitudinal Healthcare Databases (EPI 253 Odd Years, Summer 2) Instructors: Drs. Sebastian Schneeweiss, Michael Fisher, Sonia Hernandez-Diaz.
Large longitudinal healthcare databases have become important tools for studying the utilization patterns and clinical effectiveness of medical products and interventions in a wide variety of care settings and for evaluating the impact of clinical programs or policy changes. This course will prepare students to identify and use longitudinal databases in their own research.
Strengths and limitations of large longitudinal healthcare databases that are commonly used for research will be considered. Special attention will be devoted to nationally representative databases that are critical for comparative effectiveness research and local electronic medical record data sources that are readily available to new investigators.
Practical issues in obtaining, linking, and analyzing large databases will be emphasized throughout the course, and key analytic issues will be addressed, including design considerations and multivariate risk-adjustment. Students will evaluate published database studies, complete programming exercises with statistical software and hands-on access to a large longitudinal database, and prepare a proposal for analyzing a specific research question using a large healthcare database.
The course focuses on analytic principles and their application to database research. It requires an understanding of epidemiologic study designs (cohort, case-control) and typical analysis strategies (logistic regression, Cox regression, propensity score analysis).
Propensity Score Analysis: Theoretical & Practical Considerations (EPI 271, Winter) Instructor:Drs Tobias Kurth and John Seeger. This course introduces basic and advanced theory underlying propensity score analyses and provides practical insights into the conduct of studies employing the method. Course readings will include propensity score theory as well as applications. Lectures are complemented by computer lab sessions devoted to the mechanics of estimating and using the propensity score as a tool to control for confounding in observational research. Students should have knowledge in multivariable modeling approaches. A course project will involve the application of propensity scores to a data set or the review of a related, published paper.