Increased Trends of Self-Optimized Submissions to NICE
Author(s)
Albert Kwarciak, MSc, Xingyao Liu, MSc, Julia Sus, MSc.
Kintiga, Cambridge, United Kingdom.
Kintiga, Cambridge, United Kingdom.
OBJECTIVES: A recent study by the Office of Health Economics analysed outcomes of health technology assessments (HTA) to the National Institute for Health and Care Excellence (NICE) from 2015 to 2024. They found an increasing share of optimised decisions, which involve restricting the recommendation to a narrower population compared to the licensed indication. Our research provides insight into the share of optimised decisions that have been initiated by the company, to identify potential trends and implications.
METHODS: A HTA database of all NICE submissions was searched for the period from January 2015 to May 2025, and all optimised decisions were identified. Thereafter, an examination was conducted comparing the licensed indication and the recommendations made by the committee. The examination also included a review of the company submission and the committee papers to determine whether it was the company who sought a restricted recommendation or otherwise.
RESULTS: Over the time period examined, NICE made 731 recommendations, which consisted of 298 optimised recommendations. Out of the optimised recommendations, 43 of them were identified as the company wanting to self-optimise the recommendation. The self-optimised trends are not linear. Only 5% of optimised recommendations in the calendar year of 2019 were self-optimised (1/15), jumping to 38% in the calendar of 2024 (9/24). The committee’s distribution for self-optimised decisions was balanced (A, 10; B, 11; C, 10; D, 8; HST, 3), with there also being no clear pattern across the External Assessment Groups (EAG). The Liverpool EAG worked on the least number of self-optimised submissions (2), and Southampton with the most (9).
CONCLUSIONS: Overall, the increased number of optimised decisions naturally led to an increased number of submissions where the company sought a restricted recommendation. The causes of self-optimisation are likely to be heterogeneous, but identified trends raise alarms about a more challenging reimbursement landscape in the United Kingdom.
METHODS: A HTA database of all NICE submissions was searched for the period from January 2015 to May 2025, and all optimised decisions were identified. Thereafter, an examination was conducted comparing the licensed indication and the recommendations made by the committee. The examination also included a review of the company submission and the committee papers to determine whether it was the company who sought a restricted recommendation or otherwise.
RESULTS: Over the time period examined, NICE made 731 recommendations, which consisted of 298 optimised recommendations. Out of the optimised recommendations, 43 of them were identified as the company wanting to self-optimise the recommendation. The self-optimised trends are not linear. Only 5% of optimised recommendations in the calendar year of 2019 were self-optimised (1/15), jumping to 38% in the calendar of 2024 (9/24). The committee’s distribution for self-optimised decisions was balanced (A, 10; B, 11; C, 10; D, 8; HST, 3), with there also being no clear pattern across the External Assessment Groups (EAG). The Liverpool EAG worked on the least number of self-optimised submissions (2), and Southampton with the most (9).
CONCLUSIONS: Overall, the increased number of optimised decisions naturally led to an increased number of submissions where the company sought a restricted recommendation. The causes of self-optimisation are likely to be heterogeneous, but identified trends raise alarms about a more challenging reimbursement landscape in the United Kingdom.
Conference/Value in Health Info
2025-11, ISPOR Europe 2025, Glasgow, Scotland
Value in Health, Volume 28, Issue S2
Code
HTA199
Topic
Health Policy & Regulatory, Health Technology Assessment
Topic Subcategory
Decision & Deliberative Processes
Disease
No Additional Disease & Conditions/Specialized Treatment Areas