R for trial and model-based cost-effectiveness analysis
We are excited to announce the R for Health Technology Assessment (HTA) workshop that will be held on Friday 6th June, Monday 9th June and Tuesday 10th June 2025.
Friday 6th will be in-person day-long hybrid event hosted by Queen’s University Belfast, while other days will be online only. Our program will be announced in May. The overall goal is to present interesting and enlightening presentations on the use of R that will engage an audience of those working in the field of health technology assessment and related analysis. Sessions may cover some or all of the following:
- New methods and applications for economic modelling using R
- Efficient modelling for economic evaluation using dedicated R packages
- Improving modelling for HTA using R – Lessons from industry and academia
- Teaching economic evaluation and HTA using R
Details on travel to Queen’s University Belfast can be found here, and information on hotels here.
For any questions before the day, contact the team at RHTA@qub.ac.uk.
The call for abstracts is not restricted by topic.
Registration for the workshop can be made at this webpage. Please note that we can only accept payments via card.
The registration fee is structured as follows
| Attendance type | Standard price | LMIC and students discount* |
|---|---|---|
| Online only (6th, 9th & 10th June 2025) | £50 | £10 |
| In person (6th June) and online (9th & 10th June 2025) | £90 | £65 |
NB: LMIC relates to country of residence/occupation and not origin. When registering, you will be asked to give details of your student status or country of occupation.
We look forward to seeing you there!
Call for abstracts
Deadline 04 April 2025
We are seeking abstracts for the R for Health Technology Assessment (HTA) workshop that will be held on Friday 6th June, Monday 9th June and Tuesday 10th June 2025. Friday 6th will be in-person day-long hybrid event hosted by Queen’s University Belfast, while other days will be online only. Our call for abstracts is broad and relates to no specific topic area. The overall goal is to present interesting and enlightening presentations on the use of R that will engage an audience of those working in the field of health technology assessment and related analysis. While the call is broad, the following considerations will help guide abstract preparation.
We are inviting submissions aimed at an audience with a broad range of expertise with R. Abstracts aimed at beginners are welcome and should be accessible and offer teaching insights. Abstracts for more advanced R users are also invited and can be technically ambitious and presume a knowledge of R and HTA modelling methods. Naturally, more advanced presentations should still attempt to convey broad principles alongside technical detail in order to remain relevant for less expert attendees. Please clearly indicate in your abstract if your submission is aimed at more or less experienced R users.
We welcome any topic you consider interesting and worth sharing. We suggest keeping the scope of the presentation sufficiently narrow to permit a meaningful exposition of a method, use of code or output presentation. Abstracts exemplifying the application of particular packages (not necessarily your own) are welcome. We also welcome the presentations on problems that analysts have encountered and are seeking to prompt discussion on possible solutions. Such problem-related abstracts should address a clearly-defined issue and outline some candidate approaches in order to frame the discussion. We also welcome abstracts related to the practicalities of R modelling, such as cluster or cloud implementation, handling of large datasets and runtime or variance reduction. Submissions may relate to applied analyses or methods research. Similarly, they may relate to simulation modelling or data analysis. Please clearly indicate which best corresponds to your submission in your abstract.
Abstracts should be 300 words or less excluding title and author information. Structured abstracts are encouraged using the format: background; analysis; discussion. Include all co-author name and institutional affiliations.
Full programme
Day 1. Friday 6th June (In person and Remote)
| Session | Name | Institution | Title |
|---|---|---|---|
| 10:00-10:10 | Felicity Lamrock | Queen’s University Belfast | Welcome |
| 10:10-10:30 | Eline Krijkamp | Erasmus University Rotterdam | From spreadsheet to script: Streamlining data collection and probabilistic sensitivity analysis with Excel and R |
| 10:30-10:50 | Ayman Sadek | University of Bristol Technology Assessment Group (TAG) | Discrete event simulation and treatment sequencing cost-effectiveness model in second line highly active relapse remitting multiple sclerosis for a NICE Multiple Technology Appraisal |
| 10:50-11:10 | Javier Sanchez Alvarez | Abbvie | Unlocking Discrete Event Simulation Modelling in R using WARDEN |
| 11:10-11:40 | Break | ||
| 11:40-12:00 | Robert Smith | Dark Peak Analytics | Automating Economic Evaluation Reports Using R, RMarkdown, and LLMs |
| 12:00-12:20 | Stijn Peeters | Erasmus School of Health Policy & Management | Measuring Mental Health Quality of Life in R: A Psychometric Evaluation and Standardised MHQoL Toolbox |
| 12:20-12:40 | Raymond Henderson | Salutem Insights Ltd | Mapping the Landscape of Open Source Health Economic Models: A Systematic Database Review and Analysis: An ISPOR Special Interest Group Report |
| 12:40-13:00 | Mei Sum Chan | LCP Health Analytics | Automated NMA Results Slide Generation with multiNMA in R: Streamlining Evidence Synthesis |
| 13:00-14:00 | Lunch | ||
| 14:00-14:20 | Howard Thom | University of Bristol | Proof-of-concept for automatic export of Excel versions of R health economic models |
| 14:20-14:40 | Nathan Green | UCL | A Framework for Linked Models in Cost-Effectiveness Analyses |
| 14:40-15:00 | Jack Ettinger | Parexel | Making an R model that is fit for most purposes in the pharmaceutical industry: A global proof-of-concept cost-effectiveness template model in R |
| 15:00-15:20 | Rob Smith | Dark Peak Analytics | Closing remarks |
Day 2. Monday 9th June (Remote)
| Session | Name | Institution | Title |
|---|---|---|---|
| 9:00-9:10 | Felicity Lamrock | Queen’s Univeristy Belfast | Welcome |
| 9:10-9:30 | Harriet Fewster | York Health Economics Consortium Ltd | Investigating Input Correlation in Probabilistic Sensitivity Analysis |
| 9:30-9:50 | Olivia Adair | Queen’s Univeristy Belfast | A Shiny New Way to Evaluate Bowel Cancer Screening in Northern Ireland. |
| 9:50-10:10 | Luke Hardcastle | Dept. Statistical Science, University College London | The diffusion piecewise exponential model for survival extrapolation |
| 10:10-10:30 | Zachary Waller | Queen’s Univeristy Belfast | Blistering speed - is Rcpp really so scary? |
| 10:30-10:45 | Break | ||
| 10:45-11:05 | Ahmed Abdelsabour | PenTAG, University of Exeter | Visualising Non-Inferiority: An R Shiny Tool for Indirect Comparisons |
| 11:05-11:25 | Hesam Ghiasvand | Coventry University | Revealing Subgroup Cost-Effectiveness Using Group-Based Trajectory Modelling: A Simulation on the findings of a study in Maternal Health During Birth |
| 11:25-11:45 | David McAllister | University of Glasgow | RESIDE - RESIDE: Rapid Easy Synthesis to Inform Data Extraction |
| 11:45-12:05 | Jesus Perez | University of Glasgow / Datasky | TableTidier: Extracting and Harmonising Tabular Data for Secondary Research |
| 12:05-13:10 | Lunch | ||
| 13:10-14:00 | Dominic Muston, Gregory Chen, Anders Gorst-Rasmussen, Robert Hettle | MSD, Novo Nordisk, AstraZeneca | Enhancing Cooperation Between Clinical Evidence Generation and Economic Modeling in HTA: How R Can Help |
| 14:00-14:15 | Howard Thom | University of Bristol | Closing remarks |
Day 3. Tuesday 10th June (Remote)
| Session | Name | Institution | Title |
|---|---|---|---|
| 13:00-13:10 | Nathan Green | University College London | Welcome |
| 13:10-13:30 | Frederick W. Thielen | Erasmus School of Health Policy & Management | tatooheene: The R Package Toolbox for Health Economic Evaluations Aligned with the Dutch Guideline |
| 13:30-13:50 | Aaron Winn & Wael Mohammed | University of Illinois Chicago / Dark Peak Analytics | Building Efficient Microsimulation Models in R: A How-To Guide |
| 13:50-14:10 | Hong Xiao | Otsuka Pharmaceuticals, Inc | Enhancing HTA model adaptations with AI: Leveraging large language models and R-Shiny for local cost-effectiveness analyses |
| 14:10-14:25 | Break | ||
| 14:25-14:45 | Mate Szilcz | Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden | extRpolateS: A Shiny-Based Interactive Platform for Time-to-Event Data Modeling in Health Technology Assessments |
| 14:45-15:05 | Rachel O’Leary | Newcastle upon Tyne Hospitals NHS Foundation Trust (NuTH) | Robot-assisted surgery for orthopaedic procedures: a rapid economic evaluation using rdecision |
| 15:05-15:25 | Jorge Roa | Department of Health Policy, Stanford University School of Medicine, Stanford, California, USA. | Accurate uncertainty quantification in Bayesian calibration accounting for correlated targets |
| 15:25-15:40 | Break | ||
| 15:40-16:00 | Hawre Jalal | University of Ottawa | A Computationally Efficient and Fully Vectorized Probabilistic Analysis of Time-Dependent Markov Modeling |
| 16:00-16:50 | Rose Hart, Sven Klijn, Yevgeniy Samyshkin and Tom Ward | Dark Peak Analytics, Bristol Myers Squibb, GlaxoSmithKline | Defining and Overcoming Barriers to R in Health Economic Assessments: Insights and Pathways Forward |
| 16:50-17:00 | Dawn Lee | PenTAG, University of Exeter | Closing remarks |
