Modelling Cost-Effectiveness in Healthcare is an eight-week online course designed by faculty from the Department of Health Policy at LSE. It will equip students with the tools to design, analyse, and interpret cost-effectiveness analysis models. This is a technical course which teaches students how to develop a model, and analyse cost-effectiveness analyses that can inform resource allocation decisions. We sat down with Dr Alex Carter, Senior Lecturer in the Department of Health Policy, and course convenor, to find out more.
Firstly, could you start by telling us about your role at LSE?
"I'm a senior lecturer in the Department of Health Policy at LSE and I teach, I conduct research and I work with governments, policy makers, and companies who are making investments in health and healthcare."
Can you tell us some more about the Department of Health Policy?
"The Department of Health Policy is a relatively new department at LSE, and this reflects the growing importance of health policy and health economics in the world. Our activities continue to grow across these disciplines and we consistently teach several hundred students a year at a post graduate level. Research at the Department is rated extremely well by the Research Excellence Framework in the UK. This is achieved thanks to funding from leading national and international bodies. For example, starting this year, I am leading a work package that is part of a large EU Commission-funded project that is studying the economics of uncontrolled, chronic hypertension in Europe. Through close collaborations with governments, international health organisations, academic institutions and industry partners, our research has created and continues to create lasting changes in health planning and delivery around the globe."
What topics does the Modelling-Cost Effectiveness in Healthcare course cover?
"This course covers several fundamental concepts in economic evaluation/cost-effective analysis. It takes you through the steps towards building an economic evaluation, starting with the types of decision analytic model which we use, including decision trees, Markov models, and DICE (Discretely Integrated Conditional Effect Model). We cover the broader practical steps around how to populate decision analytic models with data, and how to conceive these models to ensure the choice of model is appropriate. Towards the end of the course, we explore the interpretation of these models in a very pragmatic way; how are they actually used in health policy and for decision making?"
Who would you recommend this course to and why?
"This course is deliberately designed for a wide range of individuals; professionals who are early to mid-career may benefit the most, but equally the knowledge is relevant to those who are later in their career and have an interest in economic evaluation. The sectors we think this course appeals to are public health professionals, consultants in pharmaceutical and medical technology industries, policy makers, those in policy-making roles, those emerging or established in health technology assessment roles, and early-career researchers. Clinicians are increasingly engaged in cost-effectiveness analysis, either directly or indirectly. For example, they may be presented with these models and may be expected to interpret them, or that they may be asked to create one based on their clinical expertise. This course can provide essential training for these activities. Finally, this course is designed to serve an international audience; economic evaluation and health technology assessment is an expanding field with more and more governments and policy makers using it to make more transparent resource allocation decisions."
How can students apply the skills they learn on the course into their work?
"The first thing the course will give the students is an end-to-end tutorial on how to build a model. These skills are really important because you can start to model a decision that’s of specific interest to you, and there are practical skills that you can take away. You’ll come away with a degree of confidence that you know the end-to-end process for developing a model and interpreting the results. You'll be better prepared for advanced methods by taking this course because it's a comprehensive education in how to develop a model, and apply the concept to your professional life. If you’re interested in data science and decision making with data, then understanding some basics of modelling is a key entry point for more advanced and increasingly important modelling methods, in healthcare but also in other sectors.”
Lastly, could you share with us what you've been working on recently?
"I've been working on several new projects that are related to health economic evaluation. An important and high-profile one is an EU horizon project in which I'm leading a health economics work package with a European consortium from the Netherlands, Germany, Spain, Italy, the UK and other countries, to investigate a new method of optimising the prescribing of hypertensive medications. This project is called Hypermarker, and we are about to have our first kick-off meeting. In this project, we're aiming to use metabolomic and genomic data to improve clinicians' ability to make personalised decisions about the medications hypertensive patients use. As hypertension is a leading cause of morbidity and mortality, the economic impact of improving long-term control of hypertension is significant."