R for Health Technology Assessment

1. Introduction to Health Technology Assessment
Anna Heath, Petros Pechlivanoglou, and Gianluca Baio  

2. Introduction to R
Howard Thom and David Phillippo

3. Why R? A Low- and Middle-Income Countries Perspective
Joshua Soboil, Federico Rodriguez Cairoli, and Antoinette Buhle Ndweni

4. Introduction to statistical modelling
Gianluca Baio

5. Individual level data
Mi Jun Keng, Iryna Schlackow, and Eleanor Pullenayegum

6. Missing data
Andrea Gabrio, Alexina Mason, Baptiste Leurent, and Manuel Gomes

7. Introduction to survival analysis in HTA
Christopher Jackson, Nick Latimer, Jeroen Jansen, Petros Pechlivanoglou, and Gianluca Baio

8. Decision tree models
Nathan Green, Eline Krijkamp, Howard Thom, and Padraig Dixon

9. Cohort Markov Models in Discrete Time
Howard Thom, Pedro Saramago, Marta Soares, Eline Krijkamp, and Felicity Lamrock

10. Network Meta-Analysis
Howard Thom, Nicky Welton, David Philippo, and Mathias Harrer

11. Continuous time multistate models
Howard Thom, David Incerti, Christopher Jackson, Felicity Lamrock, and Claire Williams

12. Discrete Event Simulation in R
Koen Degeling, Mark Clements, Erik Koffijberg, James O’Mahony, Mohsen Sadatsafavi, and Petros Pechlivanoglou

13. Population-adjusted indirect comparisons
David Phillippo, Jeroen Jansen, Antonio Remiro-Azocar, and Howard Thom

14. R and shiny in HTA
Rose Hart, Darren Burns, Mark Strong, Andrea Berardi, and Dawn Lee

Biography

Gianluca Baio is Professor of Statistics and Health Economics in the Department of Statistical Science at University College London (UK). Gianluca’s main interests are in Bayesian statistical modelling for cost effectiveness analysis and decision-making problems in the health systems, hierarchical/multilevel models and causal inference using the decision-theoretic approach. Gianluca leads the Statistics for Health Economic Evaluation research group within the department of Statistical Science and was the co-director of UCL MSc Programme in Health Economics and Decision Science. He is a founding member and former Scientific co-Director of the R-HTA consortium (https://r-hta.org/) and a founding member of the ConVOI (https://www.convoi-group.org/) network. He also served as Secretary (2014-2016) and then Programme Chair (2016-2018) in the Section on Biostatistics and Pharmaceutical Statistics of the International Society for Bayesian Analysis. He collaborates with the UK National Institute for Health and Care Excellence (NICE) as a Scientific Advisor on Health Technology Appraisal projects and has been the 18th Armitage Lecturer in November 2021. His research activity is now (almost) officially dead, since he has become the head of the department of Statistical Science at UCL, in 2021.

Howard Thom is Associate Professor in Health Economics at the University of Bristol, a health economics lead at the Bristol NICE Technology Assessment Group (TAG), and managing director of the consultancy Clifton Insight. At the University of Bristol he created the world’s first annual short course on Economic Evaluation Modelling in R in 2019 and teaches on R for Health Technology Assessment for the International Society for Pharmacoeconomics and Outcomes Research. With Professor Gianluca Baio he founded the R for HTA organisation in 2018. He has published more than 70 peer reviewer papers, including new methods for network meta-analysis, structural uncertainty in cost-effectiveness models, and value of information analysis. He has built and contributed to dozens of academic and commercial cost-effectiveness models across a wide range of indications, including oncology (e.g. NSCLC, prostate cancer, breast cancer, hepatocellular carcinoma, and melanoma), neurology, rheumatology, and cardiology. Many of these models have been in R, including decision trees, Markov models, multistate microsimulations and discrete event simulations. He is a founding member and current Co-Director of the R-HTA consortium (https://r-hta.org/), as well as a member of the ConVOI (https://www.convoi-group.org/) network.

Petros Pechlivanoglou PhD, is a Senior Scientist at the Hospital for Sick Children, an Associate Professor at the Institute of Health Policy, Management and Evaluation (IHPME) at the University of Toronto and an adjunct ICES Scientist. He completed an MSc in econometrics and a PhD in health econometrics at the University of Groningen, the Netherlands. His current research focuses on the integration of large real-world data, decision analysis and statistical modelling in estimating the long-term health economic consequences of disease or treatment exposure, with a focus in early childhood. He has been an R user for over 20 years and has taught decision modeling using R for the last 15 years. Together with an international group of researchers has formed the Decision Analysis in R for Technologies in Health (DARTH) workgroup.