An online course consisting of four modules over 6 weeks 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 Faculty and tutors

  • One ‘live’ question and answer session for each module with module leads

How It Works

The video lectures/exercises for each module will be released on the dates specified in the first column of the timetable below. You can then work through these in your account at any time you wish. The second column indicates how much time you should expect to dedicate to this. For each module there will be a one-hour live Q&A session with the tutors; this is the only fixed-time component and is scheduled to take place at 1pm British Summer Time on the dates shown in the third column of the timetable. Do not worry if you are unable to attend every live session; these will be recorded. Furthermore, in addition to the live Q&A sessions, there will be a discussion board available on the course platform, where you can leave messages regarding the course content. Students are encouraged to keep up with the timetable where possible as tutor support is only available during the timetabled dates.

Course Dates

The Advanced Course will take place from 5th June to 12th July 2023. See the timetable below for more detail. Please note that the exact programme is subject to change although the material covered will remain largely the same.


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 Karl Claxton

Karl Claxton is a Professor in the Department of Economics and Related Studies at the University of York. He is also a Senior Research Fellow in the Centre for Health Economics, University of York. He was a Harkness Fellow at the Harvard School of Public Health and from 1999 until 2007 he held an adjunct appointment at Harvard as an Assistant Professor of Health and Decision Sciences. His research interests encompass the economic evaluation of health care technologies.

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.

R Tutor Lead Nichola Naylor

Nichola Naylor is an Honorary Research Fellow at LSHTM, working across the Centre for Health Economics in London and the Centre for the Mathematical Modelling of Infectious Diseases. Her research interests for the past six years have included using economic methods to efficiently tackle antimicrobial resistance (AMR) and using R to promote open science. She recently joined Public Health England to lead health economics work contributing to the UK AMR strategy. She holds a PhD in Clinical Medical Research from the NIHR Health Protection Research Unit on Healthcare Associated Infections and Antimicrobial Resistance at Imperial College London, and an MSc in International Health Policy (Health Economics) from the London School of Economics and Political Science (2013).

Tutor David Glynn

David is a Research Fellow in the Team for Economic Evaluation and Health Technology Assessment (TEEHTA). His research interests include: value of information methodology, Bayesian methods, multimorbidity modelling and meta-epidemiology. David has held positions at the National Institute for Health and Care Excellence (NICE) and the National Collaborating Center for Mental Health. He holds a Master of Pharmacy from Robert Gordon University, a Master of Health Economics from the University of Aberdeen and a PhD in Economics from the University of York.

Tutor Jessica Ochalek

Jessica Ochalek is a Research Fellow in the Team for Economic Evaluation and Health Technology Assessment (TEEHTA). She joined in 2014 after completing the MSc in Health Economics at the University of York. Her MSc dissertation focused on estimating the effect of HIV status and low CD4 count on individuals' labour supply using an instrumental variable approach and data from Uganda. She also holds an MPH from Boston University and a BA in Global Studies from the University of Wisconsin – Milwaukee, and has experience working at OECD as well as the Center for Global Health and Development at Boston University. Her research interests are centred around the application of economic evaluation in low- and middle-income countries.

Tutor Shainur Premji

Shainur is a Research Fellow with the Team for Economic Evaluation and Health Technology Assessment (TEEHTA). Shainur holds a B.A. in International Relations, B.A. Honours in Economics, an M.Sc. in Health Research Methods, and Ph.D. in Health Economics. Shainur has over 15 years of progressive experience in program evaluation, health research, and health economics, and has worked in various academic, private, and public health settings. Shainur thrives in situations that require innovative, applied system-level thinking and complex research designs using a mix of qualitative and quantitative methods, including patient-level data applications for evidence-informed, applied decision-making.

How To Register

The course fee is payable in advance. You can pay immediately by card by clicking "Register" next to the relevant price below (Private/commercial or Public sector/academic) and completing the payment process online. If you require to pay via invoice, for example through your institution, please send an email to Nicola Bogle at he-evalcourses@openaudience.com stating your name, the course(s) that you wish to sign up for and the invoice address. You will be enrolled on the course once the invoice has been issued; however, please note that in order to be able to access the content, payment of the invoice must be received no later than by 8am BST on the course start date.


Please select "Register" 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 he-evalcourses@openaudience.com to request the discount.