Health Economic Modeling in R: A Hands-on Introduction

Author(s)

Faculty: Felicity Lamrock, PhD, Queens University Belfast, Belfast, ANT, UK Gianluca Baio, PhD, Department of Statistical Science, University College London, London, UK; Howard Thom, MSc, PhD, University of Bristol, Bristol, UK; Clifton Insight, Bristol, SOM, UK; Rose Hart, PhD, Lumanity Inc., Sheffield, UK

Presentation Documents

Separate registration required.

This highly practical course will outline the computational and transparency advantages of using R, for those used to health economic modelling using Microsoft Excel. This course explores the use of R for health economic modelling in the context of health economics and outcomes research (HEOR) and faculty will guide the participants through practical examples of HEOR. The faculty are expert speakers who have diverse experience in academia, national Health Technology Assessment agencies (NICE, NCPE), and industry. The faculty will lead participants through practical examples of health economic modelling including using R for Markov models from deterministic analysis through to probabilistic sensitivity analysis and EVPI. Additional useful packages for modelling using R will also be discussed. All sessions will interchange between descriptive lectures and hands-on exercises. Participants will be provided with materials, including model examples in R and information on where to go for further learning.

This course is designed for those with some familiarity with modelling techniques, such as the concepts of discrete time cohort Markov models and probabilistic sensitivity analysis, but familiarity with R coding is not required.

Attendees will require a laptop with RStudio (v1.1.0 or higher) and R (v4.2.1 or higher) downloaded and installed.

Conference/Value in Health Info

2023-11, ISPOR Europe 2023, Copenhagen, Denmark

Code

003

Topic

Economic Evaluation

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