Health Economics and Decision Modelling

Core modules:

Introduction to Health Economics

This module is concerned with understanding the key elements in the theory of health economics. Students are introduced to some of the key principles and tools of microeconomics which are then used to examine the peculiarities of the market for health care. In particular, the module focuses on how the market for health care 'fails' and what the implications are for consumption, production and distribution. Students are encouraged to critically appraise the alternative approaches to overcoming some of these market failures.

15 credits

Economic Evaluation

This module introduces the basic principles of economic evaluation as applied to healthcare interventions.  The course introduces the concept of economic evaluation, the different types that are available and the various stages and techniques that need to be applied to generate results.  Current practice guidelines will be described so that students can understand the current policy context of the methods.  Also, as alternative techniques are described, their strengths and weaknesses will be highlighted, with the students being encouraged to critically appraise their appropriateness to different contexts.

15 credits

Cost-effectiveness Modelling for Health Technology Assessment

This module provides an introduction to mathematical modelling and its role in informing clinical policy and resource allocation decisions in international healthcare systems. The core of the module is cost-effectiveness modelling, interpretation and appraisal. Specific methods include problem definition and structuring, decision trees, and Markov/state transition modelling. The methods outlined in this module will be transferable to decision problems in other settings outside of healthcare. Lectures will be augmented by practical modelling sessions.

15 credits

Medical Statistics and Evidence Synthesis

This module introduces students to key concepts and methods used in medical statistics. The module is organised in two parts: 1) the design, analysis and reporting of randomised control trials, and 2) the synthesis of evidence from multiple clinical trials using meta-analysis methods and quantifying uncertainty using experts' beliefs. Classical (i.e. frequentist) and Bayesian meta-analysis methods will be presented with an emphasis on how evidence can be used to represent uncertainty about input parameters in decision analytical models.

15 credits

Study Design and Systematic Review Methods

This module provides an introduction to quantitative and qualitative research methods, combining theoretical instruction with practical exercises both in class and as part of MOLE activities. This unit provides a foundation in research methods which complements the other modules on this course. There is an emphasis on research methods used in the evaluation, assessment and analysis of technologies in healthcare.

15 credits

Valuing the Benefits of Health Care

This unit explores in detail specialist topics related to the valuation of healthcare benefits. The course content is based around three topics; the assessment of outcomes in economic evaluation, the quality adjusted life year (QALY) model and its weaknesses, and the use of alternative methods like willingness to pay. All topics will start with the basic critical appraisal of these methods developed in HAR6260 Economic Evaluation and explore in greater depths the weaknesses of conventional methods and the alternative formulations that are available.

15 credits

Further Statistical Methods for Health Economic Analysis

The module builds on key concepts introduced in HAR6170 Medical Statistics and Evidence Synthesis and HAR6260 Economic Evaluation in order to develop further the statistical skills needed in health economics. Students are introduced to a range of advanced statistical topics to address issues that arise in cost effectiveness analyses, including the analysis of cost data, time-to-event data, and treatment effect estimation using data from observational studies. The module is taught using a mixture of lectures, group discussions and hands-on computer practicals.

15 credits

Advanced Simulation Methods

This module provides an in-depth review of simulation rationale, techniques and methodologies with a particular focus on discrete event simulation and their practical application to inform healthcare decision making. From the fundamentals of a basic model the course will progress to modelling complex systems, validation, interpreting output and variance reduction techniques. The methods outlined in this module will be transferable to decision problems in settings other than healthcare. Lectures will be augmented by practical modelling sessions.Students need to have a basic level of knowledge of health economic modelling for this module.

15 credits

Dissertation

Full-time and part-time students will complete a research-based project with an external organisation (e.g. academic unit, consultancy or pharma industries or the NHS), or in an internal setting (internal placement within the Health Economics and Decision Science (HEDS) section, self- or funder-developed projects) within SCHARR for 3 months (Mid/Late June to September inclusive). The project will culminate in a written dissertation that will generally involve adapting or developing a new cost-effectiveness model or addressing a health economic problem that makes use of the competences from the programme's quantitative modules. The dissertation module provides students with an opportunity to practice and develop the skills acquired on the programme and to prepare them for future employment.

60 credits