A three-day course focusing on advanced modelling methods for economic evaluation.
The course is aimed at health economists and those health professionals with experience of health economics who wish to learn about recent methodological developments in cost-effectiveness analysis.
It is designed for participants who are familiar with basic decision modelling who wish to learn how to use more advanced modelling methods. It is particularly suitable for those who have attended our Introduction to Modelling Methods for Health Economic Evaluation.
It is envisaged that participants will currently be undertaking modelling for health economic evaluation within the pharmaceutical and medical device industries, consultancy, academia or the health service.
This is a two-day course providing an introduction to the principles and practice of decision modelling for economic evaluation in health.
The course is aimed at health economists and those health professionals with experience of health economics who wish to develop skills and knowledge in decision analysis for purposes of cost effectiveness analysis. It is designed for participants who are familiar with the basic principles of economic evaluation who wish to build, interpret and appraise decision models.
It is envisaged that participants will currently be undertaking economic evaluation within the pharmaceutical and medical device industries, consultancy, academia or the health service.
A mixture of presentations from members of the Faculty, together with computer-based exercises using MS Excel. All exercises will be supported by Faculty and a group of tutors.
Background and objectives
It is our pleasure to announce a workshop and training event on the use of R for trial and model-based cost-effectiveness analysis (CEA). This follows our successful workshop on R for CEA in 2018.
Our event will begin with a half-day short course on R for decision trees and Markov models and the use of the BCEA package for graphical and statistical analysis of results; this will be delivered by Gianluca Baio of UCL and Howard Thom of Bristol University.
This will be followed by a one-day workshop in which we will present a wide variety of technical aspects by experts from academia, industry, and government institutions (including NICE). Topics will include decision trees, Markov models, discrete event simulation, integration of network meta-analysis, extrapolation of survival curves, and development of R packages.
We will include a pre-workshop virtual code challenge on a problem set by our scientific committee. This will take place over Github and a Slack channel with participants encouraged to submit final R code solutions for peer review on efficiency, flexibility, elegance and transparency. Prizes will be provided for the best entry.
Participants are also invited to submit abstracts for potential oral presentations. An optional dinner and networking event will be held on the evening of 8th July.
Registration is open until 1 June 2019 at https://onlinestore.ucl.ac.uk/conferences-and-events/faculty-of-mathematical-physical-sciences-c06/department-of-statistical-science-f61/f61-workshop-on-r-for-trial-modelbased-costeffectiveness-analysis
To submit an abstract, please send it to firstname.lastname@example.org with the subject “R for CEA abstract”. The word limit is 300. Abstract submission deadline is 15 May 2019 and the scientific committee will make decisions on acceptance by 1st June 2018.
Day 2: Workshop. Tuesday 9th July.
- 9:30-9:45. Howard Thom. Welcome
- 9:45-10:15. Nathan Green. Imperial College London. _Simple, pain-free decision trees in R for the Excel user
- 10:15-10:35 Pedro Saramago. Centre for Health Economics, University of York. Using R for Markov modelling: an introduction
- 10:35-10:55. Alison Smith. University of Leeds. Discrete event simulation models in R
- 10:55-11:10. Coffee
- 11:10-12:20. Participants oral presentation session (4 speakers, 15 minutes each)
- 12:20-13:45. Lunch
- 13:45-14:00. Gianluca Baio. University College London. Packing up, shacking up’s (going to be) all you wanna do!. Building packages in R and Github
- 14:00-14:15. Jeroen Jansen. Innovation and Value Initiative. State transition models and integration with network meta-analysis
- 14:15-14:25. Ash Bullement. Delta Hat Analytics, UK. Fitting and extrapolating survival curves for CEA models
- 14:25-14:45. Iryna Schlackow. Nuffield Department of Public Health, University of Oxford. Generic R methods to prepare routine healthcare data for disease modelling
- 14:45-15:00. Coffee
- 15:00-15:15. Initiatives for the future and challenges in gaining R acceptance (ISPOR Taskforce, ISPOR Special Interest Group, future of the R for CEA workshop)
- 15:15-16:30. Participant discussion.
- 16:30-16:45. Anthony Hatswell. Close and conclusions