The Rise of Optimization in NICE Guidance: A Two-Decade Review With a Focus on Prevention
Author(s)
Rachel E. A. Barr-Keenan, BDS (Hons), MFDS RCPSG (Glas)1, Liz Morrell, MA MSc PhD FHEA2.
1University of Oxford, Oxford, United Kingdom, 2university of oxford, Oxford, United Kingdom.
1University of Oxford, Oxford, United Kingdom, 2university of oxford, Oxford, United Kingdom.
OBJECTIVES: The National Institute for Health and Care Excellence (NICE) assesses the clinical and cost-effectiveness of medicines for NHS use in England. Recommendations may be full or optimised, the latter restricting use to a subpopulation rather than the full licensed indication. The proportion of optimised recommendations has increased in recent decades. This study describes patterns in NICE’s use of optimised recommendations, with a focus on preventive medicines.
METHODS: Data on all optimised recommendations issued by NICE over the last twenty years were extracted from published Technology Appraisals (TAs). Trends were analysed by year, therapeutic area, and preventive vs non-preventive classification. Descriptive statistics were used to evaluate patterns.
RESULTS: Optimised recommendations have grown at an average annual rate of 6.7% over the last twenty years, outpacing the overall growth in TAs, and greatly surpassing the average annual growth rate of 1% seen in full recommendations. Musculoskeletal therapies received optimised recommendations in 64% (n=70) of appraisals over the last twenty years - one of the highest proportions - whereas, cancer received optimised recommendations for only 18% (n=65). Other disproportionately affected areas include diabetes, endocrine and metabolic conditions, and neurological disorders. Preventive medicines were found to be 1.83 times more likely to receive an optimised recommendation than non-preventive medicines, based on analysis of 85 preventive and 1,110 non-preventive medicines. 44% of preventive medicines had their recommendations optimised between 2004/05-2024/25, versus only 29% of non-preventive medicines.
CONCLUSIONS: NICE is increasingly using optimisation, but the implications for patient access remain unclear. While optimisation may be seen as restricting access, it could alternatively enable access to treatments that might otherwise be rejected outright. Preventive medicines and certain therapeutic areas appear disproportionately affected. Optimisation may unintentionally undermine public health strategies reliant on widespread preventive treatment, and further research is needed to assess its broader impact.
METHODS: Data on all optimised recommendations issued by NICE over the last twenty years were extracted from published Technology Appraisals (TAs). Trends were analysed by year, therapeutic area, and preventive vs non-preventive classification. Descriptive statistics were used to evaluate patterns.
RESULTS: Optimised recommendations have grown at an average annual rate of 6.7% over the last twenty years, outpacing the overall growth in TAs, and greatly surpassing the average annual growth rate of 1% seen in full recommendations. Musculoskeletal therapies received optimised recommendations in 64% (n=70) of appraisals over the last twenty years - one of the highest proportions - whereas, cancer received optimised recommendations for only 18% (n=65). Other disproportionately affected areas include diabetes, endocrine and metabolic conditions, and neurological disorders. Preventive medicines were found to be 1.83 times more likely to receive an optimised recommendation than non-preventive medicines, based on analysis of 85 preventive and 1,110 non-preventive medicines. 44% of preventive medicines had their recommendations optimised between 2004/05-2024/25, versus only 29% of non-preventive medicines.
CONCLUSIONS: NICE is increasingly using optimisation, but the implications for patient access remain unclear. While optimisation may be seen as restricting access, it could alternatively enable access to treatments that might otherwise be rejected outright. Preventive medicines and certain therapeutic areas appear disproportionately affected. Optimisation may unintentionally undermine public health strategies reliant on widespread preventive treatment, and further research is needed to assess its broader impact.
Conference/Value in Health Info
2025-11, ISPOR Europe 2025, Glasgow, Scotland
Value in Health, Volume 28, Issue S2
Code
HTA328
Topic
Health Policy & Regulatory, Health Technology Assessment, Methodological & Statistical Research
Topic Subcategory
Decision & Deliberative Processes, Systems & Structure, Value Frameworks & Dossier Format
Disease
Diabetes/Endocrine/Metabolic Disorders (including obesity), Musculoskeletal Disorders (Arthritis, Bone Disorders, Osteoporosis, Other Musculoskeletal)