Does the National Institute for Health and Clinical Excellence take account of factors such as uncertainty and equity as well as incremental cost-effectiveness in commissioning health care services? A binary choice experiment

Abstract

Background: NICE is an independent organisation responsible for providing national guidance on the promotion of good health and the prevention and treatment of ill health in England and Wales. One of NICE’s main roles is to produce national guidance on the use of health technologies within the NHS. Despite the Institute’s recent efforts to clarify the way in which its Appraisal Committees reach their recommendations concerning the use of health technologies, there remains ambiguity about how cost-effectiveness evidence is interpreted alongside other considerations such as the degree of clinical need within the patient population, and the degree of uncertainty surrounding cost-effectiveness estimates. Objective: To explore whether the NICE takes account of factors such as uncertainty and equity as well as incremental cost-effectiveness in commissioning health care services. Methods: A binary choice experiment was undertaken using NICE’s three Appraisal Committees. The experiment included five attributes: (1) Incremental cost-effectiveness (2) Degree of economic uncertainty (3) Age of the target population (4) Baseline health-related quality of life (5) Availability of other therapies A choice questionnaire detailing 18 scenarios was administered to NICE’s Appraisal Committees. For each scenario, respondents were asked to indicate whether they would recommend the intervention under consideration or not. The stated preference data obtained from respondents were analysed using a random effects logit regression model. Results: A response rate of 46% was obtained from the Appraisal Committees. The regression model suggests that increases in cost-effectiveness, economic uncertainty, and the availability of other therapies are associated with statistically significant reductions in the odds of adoption (p<0.05). The transition from a very low to a comparatively high level of health-related quality of life is also associated with a statistically significant reduction in the odds of a positive recommendation. Smaller changes in health-related quality of life, and the age of the target population are not associated with a statistically significant reduction in the odds of a positive recommendation. Analysis of revealed preference data indicates that the model is capable of distinguishing between those technologies which the Appraisal Committees would be highly likely to recommend, and those technologies which appear to be less attractive, although further external validation is warranted. Conclusion: The modelling suggests that cost-effectiveness, uncertainty and certain equity concerns influence the NICE Appraisal Committees’ recommendations on the use of health technologies. The modelling results appear to support Rawlins and Culyer’s notion of a probabilistic cost-effectiveness threshold approach; the "mythical" £30,000 per QALY gained threshold assumed within the literature is not supported by this stated preference modelling analysis