HTA R Us

Together with colleagues around the UK, we’re organising a workshop on the use of R for statistical modelling in health economic evaluation (broadly speaking, “cost-effectiveness analysis”).

It’s good that this is exciting news (contributing to taking my mind off all the politics & elections in the world…). But I think this really is exciting news, with a very good line up of speakers/talks. And I really think the objectives of this workshop are very interesting \(-\) I think, ultimately, we’ll aim at also creating a repository for files/examples/models/templates so that people can start using R for their health economic modelling more and more.

Details below \(-\) and Howard tells me the spaces are filling up very quickly…


One-day workshop on R for trial and model-based cost-effectiveness analysis

It is our pleasure to announce a one-day workshop on the use of R for trial and model-based cost-effectiveness analysis (CEA). CEA is often done using Excel but, despite its ease of use, Excel incurs the disadvantages of slow computational speed and a lack of transparency; our workshop aims to explore the use of R for CEA as an alternative. A wide range of technical aspects, including a discussion of the many available add-on packages, will be presented to help users get the most out of R for CEA. Presentations and public discussions will address the computational and transparency advantages of R over Excel for CEA and for easing collaboration. Our expert speakers have diverse experience in government (including NICE), academia, and industry. There will also be a contributed oral presentation session and a poster session for which we invite the submission of abstracts. Lunch and refreshments will be provided. A preliminary programme is below.

To register for this free event, please visit this website

There is no registration deadline, but places are limited so it is recommended to register soon.

[To submit an abstract, please send it to Howard Thom with the subject " R for CEA abstract“. The word limit is 300. Please specific whether the abstract is for oral or poster presentation, or if either is acceptable. Note that only 4 oral presentation slots are available. Abstract submission deadline is 15th May and the scientific committee will make decisions on acceptance by 1st June 2018.

Scientific committee:

  • Howard Thom. Bristol Medical School: Population Health Sciences, University of Bristol.
  • Claire Williams. Bristol Medical School: Population Health Sciences, University of Bristol.
  • Nicky Welton. Bristol Medical School: Population Health Sciences, University of Bristol.
  • Padraig Dixon. Bristol Medical School: Population Health Sciences, University of Bristol.
  • Gianluca Baio. Department of Statistical Science, University College London.
  • Anthony Hatswell. Delta Hat Analytics, UK; Department of Statistical Science, University College London.
  • Marta Soares. Centre for Health Economics, University of York
  • Dyfrig Hughes. Centre for Health Economics & Medicines Evaluation, Bangor University
  • Chris Jackson. Medical Research Council Biostatistics Unit, University of Cambridge
  • Boby Mihaylova. Health Economics Research Centre, Nuffield Department of Public Health, University of Oxford.
  • Iryna Schlackow. Health Economics Research Centre, Nuffield Department of Public Health, University of Oxford.

Preliminary Program

  • 9:30-9:45. Howard Thom. Welcome.
  • 9:45-10:15. Gianluca Baio. Department of Statistical Science, University College London.
    R you seriously saying we shouldn’t use Excel?
    This talk will showcase some of the R packages recently developed to aid the work of modellers working in health economic evaluations. The motivation and general philosophy of a few packages will be briefly presented. Examples of their use/advantages over more established, but often non-optimal computational tools, such as MS Excel will be demonstrated.
  • 10:15-11:25. Marta Soares. Centre for Health Economics, University of York
    Using R for Markov modelling: an introduction.
    This talk introduces the use of R for generic decision modelling detailing some of the advantages and disadvantages of this software package in relation to others commonly used, such as MS Excel. In this talk, I also present generic R code for Markov modelling, probabilistic sensitivity analyses and value of information analyses (using Monte Carlo simulation).
  • 10:25-11:05. Boby Mihaylova and Iryna Schlackow. Health Economics Research Centre, Nuffield Department of Public Health, University of Oxford.
    A policy model of cardiovascular disease in moderate-to-advanced chronic kidney disease
    This talk will present the design and structure in R of the SHARP CKD-CVD model, developed using the 5-years follow-up data of 10,000 patients with chronic kidney disease in the SHARP study. The model projects chronic kidney disease progression and cardiovascular complications and mortality using a set of multivariate risk, cost and QoL equations. We will demonstrate the R Shiny-based model interface to enable use by external analysts and will discuss issues related to model functionality and speed of execution.
  • 11:05-11:20. Coffee
  • 11:20-12:20. Participants oral presentation session (4 speakers, 15 minutes each)
  • 12:20-13:45. Lunch and poster presentations.
  • 13:45-14:00. Dyfrig Hughes. Centre for Health Economics & Medicines Evaluation, Bangor University
    Health technology assessors’ perspectives on R
    This session will present the perspectives of members of NICE evidence review groups, AWMSG secretariat and SMC independent assessors on sponsor submissions using R. The skill requirements, confidence and expertise of these groups in using R will also be discussed.
  • 14:00-14:15. Howard Thom.
    Value of information analysis in R.
    This session will cover the methods for value of information analysis that can be implemented in R, including linearization, brute force Monte Carlo simulation, parallel computing, meta-modelling, multilevel Monte Carlo and quasi Monte Carlo.
  • 14:15-14:25. Chris Jackson. Medical Research Council Biostatistics Unit, University of Cambridge
    Continuous-time multi-state models for disease progression
    This session will introduce the theory of modelling disease progression as a continuous-time multi-state process, and how this can be used in cost-effectiveness analysis. R software for continuous-time modelling of various patterns of observed data will be discussed.
  • 14:25-14:45. Claire Williams. Bristol Medical School: Population Health Sciences, University of Bristol.
    An overview of a suite of code and functions for CEA in R using continuous-time multi-state modelling
    This session will give a brief snapshot of the code already available in a tutorial paper detailing how to carry out Markov and semi-Markov modelling using the continuous-time multi-state modelling survival analysis framework. It will include how to carry out deterministic and probabilistic sensitivity analysis and appropriate graphical outputs.
  • 14:45-15:00. Coffee
  • 15:00-15:15. Anthony Hatswell. Delta Hat Analytics, UK; Department of Statistical Science, University College London.
    Existing frameworks for collaborative working
    This session will outline various ways of working currently used in collaborative efforts in the health economics and connected spheres. The pros and cons of each approach will be outlines, and how the use of R may be promoted under each of the scenarios.
  • 15:15-16:30. Participant discussion.
  • 16:30-16:45. Howard Thom. Close and conclusions.
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