An "on demand" online course consisting of four modules and focusing on advanced methods of decision analytic modelling 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 methods 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 Foundation Course in Modelling Methods for Health Economic Evaluation. It is envisaged that participants will currently be undertaking modelling for health economic evaluation.

Teaching Methods

  • Four modules together with introductory, policy context and closing sections

  • ‘Bite-size’ video presentations from members of the Faculty for each module

  • Computer-based exercises using MS Excel

  • *NEW* Alternative ‘R’-based exercise track for those already familiar with R

  • Video ‘run-through’ of each exercise by members of the Faculty

  • Online discussion forums monitored by tutors

How It Works

The course comprises a combination of video lectures and exercises. Students are granted 2 months' access from enrolment and can work through the content at times that suit them. There is a discussion board available on the course platform, where you can leave messages regarding the course content. The Advanced course is expected to involve a student commitment totalling approximately 18 hours.


By the end of the course, participants will be able to:

  • Model and populate a Markov model with time-dependent probabilities based on the results of parametric survival modelling

  • Develop a probabilistic model to reflect parameter uncertainty and to run Monte Carlo simulation

  • Present the results of a probabilistic model using net monetary benefits and cost-effectiveness acceptability curves

  • Assess the expected value of perfect information


This is an advanced course focusing specifically on decision modelling. Participants would be expected to have attended a general advanced course in economic evaluation, and to be familiar with foundations level decision analysis (see Foundations course). Each module will involve computer work on exercises which will be built up over the course. A familiarity with Microsoft Excel is essential, as is a familiarity with ‘R’ for those wishing to follow the new R-based exercise track.


Course Lead Andrew Briggs

Andrew is Professor of Health Economics at the London School of Hygiene & Tropical Medicine. His main methodological focus of research has been health economic evaluation, particularly statistical methods for cost-effectiveness analysis. This includes statistical methods for estimation of parameters for cost-effectiveness models as well as statistical analysis of cost-effectiveness alongside clinical trials. He has a more general interest in epidemiological methods, in particular the use of prognostic scoring methods for predicting health outcomes and the relationship with heterogeneity in cost-effectiveness analysis.

Course Lead Mark Sculpher

Mark Sculpher, PhD, Professor and Director of the Team for Economic Evaluation and Health Technology Assessment, Centre for Health Economics, University of York. Mark has worked in the field of economic evaluation and health technology assessment for over 25 years. He has particular interest in decision analysis, pharmaceutical policy and uncertainty analysis.

Module Lead Claire Rothery

Claire Rothery is a Senior Research Fellow on the Programme on Economic Evaluation and Health Technology Assessment. She joined the Centre for Health Economics in 2006 after completing the MSc in Health Economics at York. She holds a MSci in Mathematics (2001), PhD in Theoretical Physics (2004), and MPhil in Medical Statistics (2005), all awarded by Queen's University Belfast, Northern Ireland. Claire’s research interests are centred on the development and application of decision analytic modelling methods and Bayesian approaches to Health Technology Assessment. She has specific interests in the use of constrained optimisation methods in economic evaluation and Value of Information analysis for informing research prioritisation decisions.

How To Register

The course fee is payable in advance. The easiest way to register is by clicking "Purchase" next to the relevant price below (Private/commercial or Public sector/academic) and completing the payment process online using a card. This will grant you immediate enrolment, which will then remain in place for 2 calendar months. If you require to pay via invoice, for example through your institution, please send an email to Nicola Bogle at [email protected] stating your name, the course(s) that you wish to sign up for, the invoice address, and your desired enrolment start date. Please note that you will only be able to begin on the specified start date if the invoice has been settled by this time.


Please select "Purchase" next to the relevant category adjacent. An additional 25% discount on top of the public sector/academic price is available for persons working for academic institutions, public sector or non-governmental organisations in countries defined as low or middle income (LMIC) by the World Bank. Please email Nicola Bogle at [email protected] to request the discount.