Handling Uncertainty in Health Technology Assessment Processes

28 June 2026, 1:30 PM – 4:55 PM | 13:30 – 16:55 (local time)

Faculty

  • Elisabeth Fenwick, PhD – Chief Scientific Officer, OPEN Health, United Kingdom
  • Natalia Kunst, PhD – Senior Research Fellow, Centre for Health Economics, University of York, United Kingdom
  • Lotte Steuten, PhD – Deputy Chief Executive, Office of Health Economics, United Kingdom

Course Overview

Due to scarce healthcare resources, decisions must be made regarding which interventions should be reimbursed or adopted within health systems. In many countries, model-based economic evaluations are used as part of the Health Technology Assessment (HTA) process to systematically evaluate the expected health effects and costs associated with different decision options.

Because these assessments rely on incomplete information, uncertainty is often present and may influence the reliability of the results and the decisions derived from them. In extreme cases, poorly characterized uncertainty can lead to suboptimal decision making. Economic evaluations used for HTA purposes therefore require a coherent analytical framework that structures the decision-making process and explicitly evaluates the uncertainty surrounding expected outcomes.

This course introduces participants to the different types of uncertainty encountered in decision-analytic modeling for HTA and presents methods used to assess and manage these uncertainties. Participants will gain an understanding of how uncertainty analyses inform decision making and how results should be reported in accordance with current methodological guidance and good-practice recommendations.

Through examples and applied exercises, the course will demonstrate practical approaches for evaluating uncertainty and interpreting the results of these analyses within HTA decision contexts.

Learning Objectives

Participants will learn how to:

  • Describe the key steps involved in model-based economic evaluations for health technology assessment purposes
  • Define the main types of uncertainty encountered in decision-analytic modeling
  • Discuss methods used to assess and address different forms of uncertainty in economic evaluations
  • Interpret and report the results of uncertainty analyses conducted for HTA decision making

Course Format

The course will combine lectures with applied examples and interactive exercises. Participants will review different approaches used to assess uncertainty in model-based economic evaluations and will practice interpreting the results of uncertainty analyses in the context of HTA decision making.

Hands-on exercises will allow participants to explore selected methods and discuss how these analyses can inform healthcare decision processes.

Participant Requirements

Participants should have familiarity with basic economic evaluation and health technology assessment concepts and methodologies.