UTILITY DATA IN HEALTH TECHNOLOGY ASSESSMENTS IN THE UNITED KINGDOM BY THE NATIONAL INSTITUTE FOR HEALTH AND CARE EXCELLENCE
Author(s)
Sarah Jane Lyttle, BSc1, Eion Corbett, BSc1, Laura Klein, .1, Andrew Mumford, BSc2;
1Initiate Consultancy, London, United Kingdom, 2Initiate Consultancy, Chief Executive Officer, Northampton, United Kingdom
1Initiate Consultancy, London, United Kingdom, 2Initiate Consultancy, Chief Executive Officer, Northampton, United Kingdom
OBJECTIVES: National Institute for Health and Care Excellence (NICE) makes recommendations for the United Kingdom about the use of drugs to treat medical conditions. This research reviews the source and type of utility data included in final cost-effectiveness models for positive health technology assessments (HTA) decisions published by NICE between January and December 2025.
METHODS: Committee papers and public slides from the NICE website were reviewed. A spreadsheet guided extraction of data on disease area, trial phase, control, blinding, utility type and source, and any key issues related to utilities.
RESULTS: Of 84 HTAs identified, 55 led to positive NICE recommendations: 30 (55%) in oncology, 7 (13%) orphan drugs, and 27 (49%) other. Most HTAs (82%) used phase 3 trial data. Over half (56%) were double blind; 44% were placebo controlled, 38% active controlled, and the rest combination or single arm. For utilities, 40% were generic, 13% disease specific, and 36% combination. More than half (56%) sourced utilities from clinical trials, 11% from published literature, and 13% combined approaches. The rest used previous NICE submissions, real-world evidence (RWE, including registries), vignettes, or burden of illness studies. Issues with utilities were found in 64% of assessments, but only 7% were main drivers of uncertainty; 13% had major issues but not main drivers, and 11% had moderate issues. Thirty-seven percent of HTAs using clinical trial sources had issues with the source or type of utility data, compared with 50% of those that used published literature and 50% using RWE.
CONCLUSIONS: Utility data is critical in HTAs, but sources and types vary widely. NICE may favour utilities drawn from clinical trials rather than published literature or RWE.
METHODS: Committee papers and public slides from the NICE website were reviewed. A spreadsheet guided extraction of data on disease area, trial phase, control, blinding, utility type and source, and any key issues related to utilities.
RESULTS: Of 84 HTAs identified, 55 led to positive NICE recommendations: 30 (55%) in oncology, 7 (13%) orphan drugs, and 27 (49%) other. Most HTAs (82%) used phase 3 trial data. Over half (56%) were double blind; 44% were placebo controlled, 38% active controlled, and the rest combination or single arm. For utilities, 40% were generic, 13% disease specific, and 36% combination. More than half (56%) sourced utilities from clinical trials, 11% from published literature, and 13% combined approaches. The rest used previous NICE submissions, real-world evidence (RWE, including registries), vignettes, or burden of illness studies. Issues with utilities were found in 64% of assessments, but only 7% were main drivers of uncertainty; 13% had major issues but not main drivers, and 11% had moderate issues. Thirty-seven percent of HTAs using clinical trial sources had issues with the source or type of utility data, compared with 50% of those that used published literature and 50% using RWE.
CONCLUSIONS: Utility data is critical in HTAs, but sources and types vary widely. NICE may favour utilities drawn from clinical trials rather than published literature or RWE.
Conference/Value in Health Info
2026-05, ISPOR 2026, Philadelphia, PA, USA
Value in Health, Volume 29, Issue S6
Code
HTA70
Topic
Health Technology Assessment
Topic Subcategory
Decision & Deliberative Processes
Disease
No Additional Disease & Conditions/Specialized Treatment Areas