Intermediate Economic Evaluation Using R

The R statistical software provides an efficient, flexible, transparent, and extensible tool for building models for economic evaluation in healthcare. It is an increasingly popular alternative to less efficient, generalisable and powerful software such as spreadsheets. The tutors of this course have been at the forefront of developing R models and tools for economic evaluation.

Previously titled Economic Evaluation Modelling Using R

To best accommodate different levels of learning and accessibility, we have divided the original 4 day course into separate 2 day basic and intermediate levels. These will run alternate years, with the intermediate level course taking place in the 2026/27 programme.

Dates 10-11 June 2027
Fee £500
Format Online
Audience Open to all applicants (prerequisites apply)
Organisers Dr Howard Thom and Dr Mary Ward

Course profile

This course aims to teach the use of R for building Markov, semi-Markov, and discrete event simulation models for economic evaluation and how to conduct a value of information analysis in R.

Please click on the sections below for more information. 

This 2-day course will be online with roughly 50% lectures that will explain theory and demonstrate coding, and 50% practicals that give the participants exercises to implement what they have been shown. Lectures and practicals will be delivered live.

By the end of the course participants should be able to:

  1. build a Markov model in R;
  2. build a semi-Markov model in R;
  3. build a discrete event simulation in R;
  4. incorporate uncertainty in model inputs in an economic model; and
  5. conduct a value of information analysis in R.

This course is intended for anyone undertaking model based cost-effectiveness analyses. We welcome attendees from academia, government, or industry.

This course will cover :

Day 1

  1. reminder on R;
  2. advanced Markov models (more states, more treatments, modularised code); and
  3. semi-Markov models.

Day 2

  1. value of information analysis; and
  2. discrete event simulation.

The co-leads Dr Howard Thom and Dr Mary Ward are experts on model development in R. Dr Thom has developed dozens of models in R, including decision tree, Markov, semi-Markov, and discrete event simulation models.

To make sure the course is suitable for you and you will benefit from attending, please ensure you meet the following prerequisites before booking:

Knowledge

Experience with R to level of Chapter 2 of the R for Health Technology Assessment textbook (available for free at https://gianluca.statistica.it/books/online/r-hta/chapters/03.software/software) will be assumed, but a recap will be given of more advanced topics of functions and program flow.

Knowledge of cost-effectiveness analysis, specifically on Markov models, will be assumed. Attendees will be expected to read the cohort Markov models in Chapter 9 of the R for Health Technology Assessment textbook (https://gianluca.statistica.it/books/online/r-hta/chapters/10.markov_models/markov-models) in advance of the course, or be comfortable with the material.
Software

You must have R (version 4.1.0 or higher) and RStudio (version 2025.05.1 or newer) installed in advance of the course. Go to R Installation Instructions for help getting set up.
Recommendation

Use of two screens is preferable but not essential.

Before booking this course, please make sure you read the information provided above about the target audience and prerequisites. It is important that you have access to the relevant IT resources needed for the course and meet the knowledge prerequisites to ensure you can get the most from the course.

Bookings are taken via our online booking system, for which you must register an account. To check if you are eligible for free or discounted courses please see our fees and voucher packs page. All bookings are subject to our terms and conditions, which can be read in full here.

For help and support with booking a course refer to our booking information page, FAQs or feel free to contact us directly. For available payment options please see: How to pay your short course fees.

Bookings close two weeks before the start of each course. Once all courses have finished for the current academic year we close the booking system for updates, and re-open again in the Autumn. To be notified about our timescales for opening annual registrations and bookings sign up to our mailing list.

Participants are granted access to our virtual learning platform (Blackboard Ultra) 1 to 2 weeks in advance of the course. This allows time for any pre-course work to be completed and to familiarise with the platform.

To gain the most from the course, we recommend that you attend in full and participate in all interactive components. We endeavour to record all live lecture sessions and upload these to the online learning environment within 24 hours. This allows course participants to review these sessions at leisure and revisit them multiple times. Please note that we do not record breakout sessions.

All course participants retain access to the online learning materials and recordings for 5 months after the course. 

University of Bristol staff and postgraduate students who do not wish to attend the full course may instead register for access to the 'Materials and Recordings' version of this course: Further information and bookings.

100% of attendees recommend this course*.
*Attendee feedback from 2026.

Here is a sample of feedback from the last run of the course:

"Everything went well, particularly the lectures and practical sessions for DES. It was also helpful to have access to the course materials in advance which helped me feel less nervous and well-prepared throughout the course." - Course feedback, April 2026

"I’m really satisfied with the course and would recommend it to anyone getting into the R world. I especially like how Mr. Thom delivers his lectures. You can clearly understand the crucial points and how to apply them. Following his teaching was truly enjoyable." - Course feedback, April 2026

"Lectures were really amazing, breaking down a very complex topic. I really enjoyed the module structure too." - Course feedback, April 2026

"The blend of lectures and practical sessions worked very well." - Course feedback, April 2026

"The lecturers were engaging and clearly interested in the topic they were speaking on. I feel like the basics of HE modelling in R were covered, and we also touched on some more advanced topics." - Course feedback, April 2026

"The timekeeping was excellent, with instructors consistently covering all the material within the scheduled time. The teaching was clear throughout even though we moved through a lot of content in a condensed time period." - Course feedback, April 2026