This highly practical course will outline the computational and transparency advantages of R over Microsoft Excel for use in health economic modelling. This short course explores the use of R for health economic modelling in the context of health economics and outcomes research (HEOR). The faculty will guide the participants through practical examples of health economics and outcomes research (HEOR). The faculty will also lead participants through practical examples of health economic modelling including, using R for decision trees and Markov models from deterministic analysis through to sensitivity analysis and EVPI. All sessions will interchange between descriptive lectures and hands-on exercises. Participants will be provided with materials following the course, including model examples and information on where to go for further learning. This course is designed for those familiar with the modelling techniques and concepts of decision tree models, probabilistic sensitivity analysis, and discrete time cohort Markov models. This course is designed for those with some familiarity with modelling techniques, but familiarity with R coding is not required. Attendees will require a laptop with RStudio (v1.1.0 or higher) and R (v3.5.0 or higher) downloaded and installed