Objectives:
By the end of this course, participants will
1) understand the key concepts and goals of medical decision analysis,
2) know the basic methods of decision tree analysis and Markov modeling and be able to choose the appropriate model type for a given research question
3) understand why and when decision-analytic modeling should be used in clinical evaluation, and
4) be able to critically judge the conclusions derived from a decision-analytic model and know the strengths and limitations of modeling
Course Description:
This half day course provides an introduction into medical decision analysis a tool for clinical evaluation, benefit-harm analysis and medical decision making. During the course, participants will develop a basic understanding of:
- Key concepts, definitions and goals of medical decision analysis
- Creating the structure of a decision-analytic model
- Measuring benefits, harms, and patient preferences
- Application of modeling techniques such as decision trees and Markov models
- Perform a medical decision analysis with uncertainty/sensitivity analyses
- Translate the results from decision analysis into medical decision making and clinical guidelines
Using practical examples, participants will be guided through the main modeling steps. Examples from the published literature will be discussed to understand the application of modeling techniques to specific decision problems and research questions. Modeling recommendations of the ISPOR-SMDM Joint Modeling Good Research Practices Task Force will be presented to allow participants assessing and judging the quality and validity of decision models. Strengths and limitations of medical decision analysis will be discussed at the end of the course.
For introductory reading the following literature is recommended:
Hunink MG, et al. Decision making in health and medicine. Integrating evidence and values. Cambridge: Cambridge University Press, 2014.
Caro, J.J., et al., Modeling good research practices--overview: a report of the ISPOR-SMDM Modeling Good Research Practices Task Force-1. Med Decis Making, 2012. 32(5): p. 667-77.