November 12: Applied Cost-Effectiveness Modeling with R - In Person at ISPOR Europe 2023
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November 12, 2023
Applied Cost-Effectiveness Modeling with R (in person)
LEVEL: Intermediate
TRACK: Methodological & Statistical Research
LENGTH: 4 Hours
| Course runs 1 day
This short course is offered in-person at the ISPOR Europe 2023 conference. Separate registration is required. Visit the ISPOR Europe 2023 Program page to register and learn more.
Sunday, 12 November 2023 | Course runs 1 Day
13:00-17:00 Central European Time (CET)
DESCRIPTION
Historically, economic models for cost-effectiveness analyses have been developed with specialized commercial software (such as TreeAge) or more commonly with spreadsheet software (almost always Microsoft Excel). But more recently there has been increasing
interest in using R and other programming languages for cost-effectiveness analysis which can offer advantages regarding the integration of input parameter estimation and model simulation, the evaluation of structural uncertainty, and the quantification
of decision uncertainty, among others. Programming languages such as R also facilitate reproducibility of model-based cost-effectiveness analysis which is more relevant than ever given recent calls for increased transparency. While these tools are
still relatively new, there is an increased interest in learning opportunities as evidenced by recent tutorials, workshops, and development of open-source software.
In this short course, 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. Participants will be asked to modify the models
in R (eg, adding health states, use of alternative time-to-event distributions) and run analyses (eg, cost-effectiveness analysis, probabilistic sensitivity analysis, evaluating structural uncertainty, and value of information analysis). To make this
interactive aspect of the course as efficient as possible, all participants will have access to the GitHub repository prior to the course. It will contain R code to run the economic models and R Markdown files to explain and reproduce the analyses
covered in the course.
Participants who wish to gain hands-on experience are required to bring their laptops with R packages and scripts available. To get the most out of the course, it is important that registrants are able to do some R programming. Special instructions will be provided before the course.
Registrants receive a digital course book. Copyright, Trademark and Confidentiality Policies apply.
FACULTY MEMBERS
Jeroen P. Jansen, PhD
Chief Scientist
PRECISIONheor
Oakland, CA, USA
and
Associate Professor
Clinical Pharmacy, University of California
San Francisco, CA
Devin Incerti, PhD
Head of Data Science
EntityRisk, Inc.
San Francisco, CA, USA
Basic Schedule:
4 Hours | Course runs 1 Day