Intermediate Pharmacoepidemiology: Approaches to Unmeasured Confounders

1. Course Aim

This course will introduce students to multiple approaches to addressing unmeasured confounders through study design and analysis, and the requirements and assumptions of each.

2. Requisites Statement

This is an intermediate level course for researchers using healthcare data for pharmacoepidemiology. There are no precourse materials to be reviewed.

3. Course Objectives

· Identify common unmeasured covariates in pharmacoepidemiology and the types of bias that can result.
· Describe multiple approaches to addressing unmeasured covariates in pharmacoepidemiology through study design and analysis.
· Understand the assumptions of each approach, ways of evaluating these assumptions, and when they are likely to be violated.

4. Syllabus Outline

Introductions: Course faculty lead will provide an overview of the course objectives and introduce the presenting Faculty.

Section 1: Use of study design to control unmeasured confounding: During the first set of lectures, Drs Jonsson Funk, Raman, and Gokhale will introduce three ways in which study design can be used to limit bias due to unmeasured confounding: a) the active comparator new user (ACNU) design, b) self-controlled designs, and c) instrumental variable designs. Faculty will provide foundational knowledge about each approach illustrated through real-world examples.
· Module 1: Active comparator / new user study design with Dr. Michele Jonsson Funk
· Module 2: Self-controlled study designs with Dr. Sudha Raman
· Module 3: Instrumental variable study designs with Dr. Mugdha Gokhale

Section 2: Analytic approaches to unmeasured confounding: During the second set of modules, Drs Jonsson Funk, Stürmer, and Young will introduce three analytic approaches to reduce bias due to unmeasured confounding: a) proxy measures, b) external control for confounding, and c) quantitative bias analysis. Faculty will provide foundational knowledge about each approach illustrated through real-world examples.
· Module 4: Proxy measures with Dr. Michele Jonsson Funk
· Module 5: External control for confounding with Dr. Til Stürmer
· Module 6: Quantitative bias analysis with Dr. Jessica Young

Format: Live, in person lectures followed by Q&A with the course faculty.