Determining societal preferences for valuing severity within NICE evaluations
Determining societal preferences for valuing severity within NICE evaluations
Theme 2: Measuring and Valuing Outcomes
Resources are limited and need to be allocated in an efficient and equitable manner, and health care resources are no exception. The Health Technology Assessment (HTA) process of the National Institute for Health and Care Excellence (NICE) guides the cost-effective use of limited health care resources. The baseline assumption is that a unit health gain, measured using Quality Adjusted Life Years (QALYs), is of uniform social value. However, its current Manual of 2022 outlining the reference case analysis specifies two ‘modifiers’ to this assumption. One of these modifiers concerns severity, defined in terms of “future health lost by people living with the condition with standard care in the NHS” (section 6.2.12). This is considered in terms of absolute and proportional QALY shortfalls.
Against this background, the aims of this project are: to elicit quantitative societal preferences on shortfall in future health from the English general public to refine the additional QALY weights used for severity to inform NICE technology appraisal decisions; and to use qualitative research methods to understand these preferences. The views of patient and public representatives will be considered across all aspects of the study design and interpretation of results. To deliver these aims, the project has four objectives across six work packages (WP):
To develop and finalise a preference elicitation protocol for eliciting public preferences for severity weighting, as defined by the NICE 2022 Manual, taking into account the findings from an ongoing NICE Listens exercise on severity (WP1, WP2);
To use qualitative research methods to understand the reasoning behind people’s choices when answering our elicitation tasks (WP3);
To elicit the quantitative preferences of a representative sample of the public in England for severity (WP4); and
To model the preference data to estimate weights for severity that can be applied to incremental health gains (using QALYs) from treatment (WP5).
Aki Tsuchiya, Donna Rowen, Tessa Peasgood, Allan Wailoo, Emily McDool, Tara Wickramasekera and Onur Cem Dogru.