HAR691: Using Evidence in the Design and Development of Models


Introduction

This module sets out the process of developing decision-analytic models in health technology assessment (HTA), and explains how this process is informed by evidence. It explores conceptual modelling, including how to understand decision problems and how to apply this understanding to the specification and population of a relevant decision-analytic framework. Students are introduced to information retrieval methods and formal problem structuring processes as applied to HTA.

Objectives

This module aims to provide students with a detailed knowledge of the techniques used to conceptualise and analyse decision problems within international health technology assessment.

Learning outcomes

By the end of the module students will be able to:

  • Evaluate critically problem-structuring methods and their application in decision-analytic modelling.
  • Retrieve and differentiate a range of evidence used to inform decision-analytic models.
  • Specify a relevant conceptual model based on a typical HTA decision problem.

Teaching Methods

  • Bespoke online materials will be used to present the principles of information retrieval, problem structuring methods and conceptual modelling in the context of health technology decision-analytic modelling
  • Exercises based on case studies will be used to develop students' practical and critical skills in the application of information retrieval methods and problem structuring methods
  • Guided independent study will deepen students' understanding of the model development process

Assessment

Component Weighting
Assignment (3,000 words) 100%

The module will be assessed through a single assignment that will involve the development of a conceptual model, based on a real-life example of a health technology decision problem. Students will be required to discuss critically issues in problem-structuring methods in decision-analytic modelling, demonstrate the information retrieval methods used to identify relevant evidence, and present the processes used to arrive at the model specification.

The pass mark is 50%.