Applied Cost-Effectiveness Modeling with R

Description and Objectives:

The course will begin with a background on why and how R can be used for cost-effectiveness modeling. A model taxonomy will be provided and participants will learn how to use R to develop a number of different types of economic models to perform cost-effectiveness analysis. Economic models will include time-homogeneous and time-inhomogeneous Markov cohort models,partitioned survival models, and semi-Markov individual patient simulations. The underlying assumptions of each model type will be summarized and the implementation in R will be presented in an accessible manner. Furthermore, the course will cover how to use simulated costs and QALYs from a probabilistic sensitivity analysis for decision-analysis within a cost-effectiveness framework, and how to produce representations of decision uncertainty (e.g. cost-effectiveness planes, cost-effectiveness acceptability curves, and cost-effectiveness acceptability frontiers), and conduct value of information analysis. The course will conclude with an illustrative R Shiny web application for one of the economic models to demonstrate how R code can be used to create an interactive user interface to facilitate transparency for a non-technical audience.

After completion of the course, participants will be able to:

  1. Understand how R can be used to perform model-based cost-effectiveness analysis with existing packages;

  2. Develop their own models in R by modifying existing code for commonly used model types;

  3. Understand how using R can improve reproducibility and transparency of model-based costeffectiveness analysis

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