OBJECTIVES: In 2019, the National Institute for Health and Care Excellence (NICE) found that patient organisations perceived their current involvement as insufficient, and that more transparency was needed when accounting for patient feedback in the final decisions. We aim to assess how the role of patient input is presented in NICE decision making since 2019.

METHODS: All NICE Final Appraisal Determinations (FADs) – describing the decision-making – published between January 2021 – January 2023 were reviewed. Terminated appraisals were excluded due to insufficient documentation. Using a pre-determined extraction sheet the main characteristics of the appraisal (e.g., type, disease area, rarity, patient population, and final recommendation), areas of patient input (e.g. prognosis, unmet need, clinical outcomes, treatment pathway, equality considerations, patients quality-of-life (QoL), impact on family/caregivers, impact of side effects) and details of the input (e.g. quantitative/qualitative) were recorded. Results were analysed using summary statistics and compared to previous results from the literature.

RESULTS: 201 FADs were screened of which 43 were excluded. The majority of appraisals were in chronic diseases (93%) with 51% of all FADs in oncology. 19% of FADs were in rare diseases and the majority of technologies (92%) received positive recommendation. Patient input was mentioned in 87% of FADs. Input was most frequently reported for QoL (60%), unmet need (43%) and clinical outcomes (42%). 4% of appraisals used quantitative input from patients. While all the rare disease FADs recorded patient input, none were quantitative. There was no clear pattern between NICE recommendations or disease area or chronic nature and patient input. Compared to previous reviews, the extent of patient input has increased.

CONCLUSIONS: NICE has made important progress in including patient input in the decision-making process; however, the range of areas is limited. There is also further opportunity to explore quantitative patient input, especially in rare diseases where data is limited.