The following courses are designed to equip participants with the practical skills required to build and critically review health economic models in R.
Each course follows a consistent and engaging format, including: presentations to introduce core concepts, an interactive online coursebook, code demonstrations for hands-on learning, practical exercises with solutions for self-paced practice, live Q&A sessions to address individual questions.
Course Offerings
- Introduction to R for Health Economic Evaluation - This foundational course provides a robust understanding of R, in preparation for more advanced health economic modelling techniques.
- Partitioned Survival, State Transition, & Microsimulation Models - These courses deliver focused instruction on specific modelling methodologies, ensuring participants gain deep technical expertise.
- Making Health Economic Models Shiny, Automating HE Evaluation, & Data Visualization - Designed to enhance your data science skills, these courses cover creating interactive user interfaces, automating health economic reports, and crafting compelling visualizations in R.
Complete Pathway for Organizations
For teams within a single organization, we offer a comprehensive learning pathway. This includes all the courses listed above, with the option to add bespoke sessions tailored to your specific needs.
Click on the links below to find out more about each course
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Introduction to R for Health Economic Evaluation
CourseThis course provides an introduction to R and RStudio for those new to the language who would like a gradual introduction before progressing onto the more advanced modelling and data-science for HEOR materials.
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State Transition (Markov) Models in R
CourseThis course teaches delegates to build a custom state transition model in base R. It uses an example model with time dependent transition probabilities, events and tunnel states. We also show how to run OWSA, PSA and VOI analyses.
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Making Health Economic Models Shiny
CourseThis course teaches delegates to create interactive web applications for health economic models. Based on peer reviewed literature, it shows how to develop robust and fast decision models, and deploy shiny user-interfaces written in R.
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Efficient Microsimulation Modelling in R
CourseThis course teaches delegates to build microsimulation models in base R. It shows how to use vectorization, parallelization and C++ integration (through Rcpp) to considerably improve the run-time of microsimulation models.
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Data Visualisation for Health Economic Evaluation
CourseThis course covers the skills necessary to create customised visuals for health economic evaluation. It focuses on the use of the ggplot2 package to make cost-effectiveness acceptability curves (CEACs), planes (CE-Planes) and Tornado Diagrams.
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Version Control for Health Economists
CourseLearn how to use version control software Git from within RStudio and collaborate with colleagues using GitHub. Several examples of the review process for a health economic model using version control are provided.
Instructors
Robert Smith, PhD
Dark Peak Analytics | University of Sheffield
Rob is an expert in the use of R for health economic modelling. He has previously worked at the UK Joint Biosecurity Centre, the UK Health Security Agency, the World Health Organization and The University of Sheffield. He has consulted for a wide range of organisations including top 10 pharmaceutical companies, national health ministries and HTA bodies. He is a keen proponent of the use of R for HTA; serving as co-director of the international R-HTA consortium and the World Health Organisation’s Health Economic Assessment Tool Expert Advisory Group.
Felicity Lamrock, PhD
Queens University Belfast | National Centre for Pharmacoeconomics
Felicity is Programme Director for the MSc in Data Analytics at Queens University Belfast and a Statistical Advisor to the National Centre for Pharmacoeconomics. As well as teaching, Felicity has published tutorial papers on the use of R for health economic evaluation, and is a co-director of R-HTA consortium.
Dr Paul Schneider, PhD
Dark Peak Analytics
Paul is an expert in the development of software for HEOR. A medical doctor and epidemiologist by training, he has used R on various research projects, ranging from the modelling costs of breast cancer, and value of information analyses, to the monitoring of influenza in real-time using online data. He is a keen advocate of open science practices and has published several open-source papers with Rob on the use of shiny and R for health economic evaluation.
Testimonials
“This course was the best training I’ve attended. It covered many areas essential to understanding the content, including how to structure your model, vectorization, a variety of needed commands and their efficiency, creating custom functions, combining functions to create a model, plotting data, and so much more.”
Aaron Winn, Associate Professor, University of Illinois
“This course is a great resource for creating interactive decision models using R and shiny. It offered the team a great mix of presentations and hands-on exercises, with clear code walkthroughs that are perfect for both beginners and experienced modelers.”
Professor Ed Wilson, PenTAG (University of Exeter)
“The R Shiny course was really useful for our team and catered well for attendees at all skill levels. We all left considerably more confident about building Shiny applications for decision models in R. Having the codebase and coursebook to keep after the course was invaluable as this allowed us to continue to build on the skills we learnt on the day.”
Dawn Lee, Associate Professor, PenTAG, University of Exeter
“The course was great! The slides and explanations were clear. The exercises with solutions were really helpful, and loads of example code were made available. Having access to the recordings and the online book made the whole learning experience easier. ”
Dr Rami Cosulich, Research Associate, University of Sheffield
“This course provides an excellent playground with a variety of hands-on R material to experimentally improve my/your health economic modelling in R (Shiny).”
Sietse van Mossel, University of Twente
“An excellent course on building health economic models in R + a Shiny interface with many examples and expert instructors. I appreciated the personalized support received during the code clinics. This course suitable for Intermediate or Advanced R users.”
Ayman Sadek, Senior Research Associate, University of Bristol
“The main tutor Rob was an excellent teacher, very knowledgeable and explains things very clearly at a good pace. The course material and resources were also excellent. I would thoroughly recommend and endorse this course.”
Dr Louise Linsell, Principal statistician Visible Analytics
“The Dark Peak Analytics team is second to none. Very helpful, insightful, and friendly. Would highly recommend to anyone wanting to advance their HEOR skillsets in R. ”
Michael Kim, Takeda/UIC
“Really enjoyable course with clear information that is directly applicable to anyone learning R no matter what level. Really enjoyed how open the instructors were to questions. The materials were easily accessed and easy to follow ”
Matthew Keane, Health Economist, Novartis/University of Nottingham
“This microsimulation in R is really well structured and informative course. Especially, they provide you a bunch of codes that you can run on your own program. I definitely recommend this course to those who are interested in applying this knowledge to their study. ”
Sodam Kim, University of Illinois
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