R for trial and model-based cost-effectiveness analysis

29-30 June 2020, University College London

Half day short course: “Introduction to R for Cost-Effectiveness Modelling”

29 June 2020, 9.00-13.00.
Room 113 — Public Cluster, 1-19 in Torrington Place, University College London, United Kingdom
Registration fee: £180 (there are 25 places available)

This is an introductory course aimed at Excel users familiar with decision trees and Markov models who would like to start transitioning to R. Attendees should have basic to intermediate level experience with R.

Registration via the UCL Store


9:00 - 9:15. Howard Thom. Welcome and introductions
9:15 - 9:45. Howard Thom. Building a decision tree in R
9:45 - 10:15. Gianluca Baio. Using BCEA to summarise outputs of an economic model
10:15 - 10:45. Practical 1: Decision trees
10:45 - 11:00. Coffee break
11:00 - 11:45. Howard Thom. R for building Markov models
11:45 - 12:15. Gianluca Baio. Further use of BCEA
12:15 - 13:00. Practical 2: Markov models

Half day short course “Being more productive in R: Lessons learnt the hard way”.

29 June 2020, 13.30-17.15.
Room 113 — Public Cluster, 1-19 in Torrington Place, University College London, United Kingdom
Registration fee: £180 (there are 25 places available)

This is an intermediate course on how to get the best out of R for HTA. This is aimed at those who have been using R for HTA for a few years but would like to improve their skills.

Registration via the UCL Store


13.30 – 13.45 Introduction and welcome.
13:45 - 14:15 Nathan Green. GitHub through Rstudio
14:15 - 14:45 Coffee
14.45 – 15:15 Anthony Hatswell. Doing less for the same output; set up, looping and using data structures to your advantage (including examples), functions and modular programming
15.15 – 16.00 Iryna Schlackow. An introduction to Tidyverse
16.00 - 16.15 Coffee 16.15 – 16.30 Iryna Schlackow. Profiling code and identifying bottlenecks
16.30 – 17.00 Nathan Green. Functional programming with purrr
17.00 – 17.15 Wrap up discussion

Main workshop “R for HTA”

30 June 2020, 13.30-17.15.
Room G12, 1-19 in Torrington Place, University College London, United Kingdom
Registration fee: £100 (there are 100 places available)

This is the third annual R for health technology assessment (HTA) showcase. Presentations will consist of dives into examples of R code for HTA where participants are welcome to download the code being discussed and test it out in real time. Topics to be presented include efficient implementation of cohort Markov models, incorporating expert opinion into survival analysis, use of RShiny for user interface design, and infectious disease modelling.

Registration via the UCL Store


9:30-9:40. Howard Thom, University of Bristol. Welcome
9:40-10:10. Anthony Hatswell, DeltaHat. Propensity scores in R. Managing multiple scenario analyses in a single clean script
10:10-10:40. Josephine Walker, University of Bristol. Using R for cost-effectiveness analysis of Hepatitis C screening and treatment interventions in low and middle-income countries
10:40-10:55. Coffee
10:55-11:10. Philip Cooney. Novartis Pharma. Incorporating clinical opinion into survival extrapolations with visualisations through RShiny
11:10-11:40. Claire Simons. Pharmerit. A novel approach to modelling treatment sequences: implementation and challenges
11:40-12:00. Open Presentation
12:00-12:30. Mi Jun Keng, University of Oxford. Optimizing a Markov model using apply, parallel computing, and Rcpp
12:30-13:30. Lunch.
13:30-13:45. Iryna Schlackow, University of Oxford. The Tidyverse style guide
13:45-14:15. Seamus Kent, University of Oxford. Generating evidence for HTA using the OMOP common data model and standardised analytical tools
14:15-14:45. Richard Fitzjohn, Imperial College London. An Excel-to-R translator to automatically convert Excel decision trees into R scripts
14:45-15:00 Coffee
15:00-15:30. Sam Abbott, London School of Hygiene and Tropical Medicine. The SpeedyMarkov package. A highly optimized package for cohort Markov models in R
15:30-16:30. Panel Discussion. (representatives from academia consultancy, NICE, and industry)
16:30-16:45. Gianluca Baio, UCL. Closing statements


Gianluca Baio
Gianluca Baio
Professor of Statistics and Health Economics