Course Level: Beginner
Format Requirements: The class will be structured with theory bursts followed by interactive exercises. Participants should have some familiarity with the concepts of regression and have a basic knowledge of Excel since the examples will use Excel and regression analysis to illustrate the concepts and methods. Participants must bring a laptop computer (Windows or Mac) with Excel to the session. Individuals are invited to bring their own data for analysis to the session but are not required to do so (we will provide sample datasets).
Background: This introductory course provides insight about person-level cost-effectiveness analysis (CEA). A deeper understanding of person-level CEA is important for analyzing data from clinical trials or observational studies that collect information about costs and health outcomes at an individual level. In addition, a fundamental understanding of the concepts of estimation and uncertainty in a person-level setting can enrich one’s understanding of economic evaluation more broadly. This class introduces the principles and practices of estimation and uncertainty as applied to person-level cost-effectiveness analysis (e.g., a CEA using data from a clinical trial). Our approach is predominantly intuitive and focused on enhancing practical skills.
Description and Objectives: This class is for individuals interested in person-level cost-effectiveness analysis (CEA), such as those analyzing data from randomized controlled trials or observational studies. Our objective is that attendees will be able to perform and interpret a cost-effectiveness analysis using person-level data. The fundamental concepts of estimation and uncertainty will be taught in the first part of the class, focusing on how to estimate the incremental cost-effectiveness ratio (ICER) and the uncertainty around the estimate. The second part of the class will focus on limitations of the ICER, introduce the incremental net benefit (INB) approach, and review how to estimate this statistic and its associated uncertainty. At the course’s conclusion, participants will be able to use Excel to produce ICER and INB estimates as well as characterize their uncertainty with confidence bounds, graphical representations, and cost-effectiveness acceptability curves. Participants will also have a deeper understanding of the concepts of estimation and uncertainty and be able to address these with regression analysis methods.
The class will be structured with theory bursts followed by group work exercises. Participants should have some familiarity with how to do regression as well as how to use Excel since the examples will use Excel and regression to illustrate a concept or how to do a technique. Participants must bring a laptop loaded with Excel to the session.
The objectives of this course are for participants to learn the principles and practice of
- Estimating and interpreting the ICER and INB
- Characterizing uncertainty of ICER and INB estimates using statistical methods
- Displaying uncertainty of ICER and INB estimates graphically
Interpreting and analyzing summary measures of uncertainty, including cost-effectiveness acceptability curves