Event

Separate registration required.

This highly practical course will outline the computational and transparency advantages of using R, for those used in 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.

Senior Lecturer in Data Analytics

Queen’s University Belfast

and Director, Northern Ireland Centre for Health Analytics and Decision Science (NI-CHADS)

Belfast, Ireland

Professor of Statistics and Health Economics

Department of Statistical Science, University College London

London, England, UK

Lecturer, Health Economic Modelling

University of Bristol and

Senior Director

Clifton Insight, Bristol, UK

Senior Health Economist

Lumanity Inc.

Sheffield, England, UK