Exploring Evidence Gaps in National Institute for Health and Care Excellence Early Value Assessments
Author(s)
Martin W. Njoroge, PhD, Vera T. Unwin, PhD, Anne E. Murray Cota, MBBS, MPH, Steve Williamson, MSc, Gareth Hopkin, PhD, Thomas Lawrence, BSc.
National Institute for Health and Care Excellence (NICE), Manchester, United Kingdom.
National Institute for Health and Care Excellence (NICE), Manchester, United Kingdom.
OBJECTIVES: The Early Value Assessment (EVA) program within the National Institute for Health and Care Excellence (NICE) enables a rapid assessment of digital products, devices and diagnostics for clinical effectiveness and value for money. Evidence generation plans (EGPs) are published alongside conditional recommendations for early use of technologies in the NHS. EGPs specify the key outcomes needed for assessing cost-effectiveness in the future. They also suggest a relevant study approach for data collection and include relevant time frames.This review explores the evidence gaps and recommended real-world evidence (RWE) study approaches described in the EGPs.
METHODS: NICE EVAs published between 1st July 2022 and 1st July 2024 were reviewed. Summary statistics were used to describe common themes in the evidence gaps and recommended study approaches. The evidence gaps were classified as ‘essential’ or ‘supportive’ gaps in the EGPs.
RESULTS: Of the 14 published EGPS, 57 unique technologies were included, mostly categorised as patient-facing (n=44, 77%) and digital health technologies used to drive clinical management (n=23, 40%). Most of the essential evidence gaps relate to the effectiveness of the technology compared to standard care, and/or at a sufficient time horizon (n=15, 29%). Prospective real-world implementation studies and parallel cohort studies were commonly recommended to address these gaps (n=6, 24.0% and n=6, 24.0% respectively). Supportive evidence gaps mostly concern user acceptance, engagement, usability and experience (n=7, 28%), which are proposed to be addressed largely by patient surveys (n=6, 31.3%).
CONCLUSIONS: The results show that fundamental evidence around the technology’s efficacy is common but of insufficient quantity for an NHS setting. Pragmatic real-word evidence approaches are frequently proposed in the EGPs where possible, but the frequency of proposed prospective cohort studies suggest RWE approaches are not always feasible. The technologies are mainly patient-facing, digital tools that support clinical management.
METHODS: NICE EVAs published between 1st July 2022 and 1st July 2024 were reviewed. Summary statistics were used to describe common themes in the evidence gaps and recommended study approaches. The evidence gaps were classified as ‘essential’ or ‘supportive’ gaps in the EGPs.
RESULTS: Of the 14 published EGPS, 57 unique technologies were included, mostly categorised as patient-facing (n=44, 77%) and digital health technologies used to drive clinical management (n=23, 40%). Most of the essential evidence gaps relate to the effectiveness of the technology compared to standard care, and/or at a sufficient time horizon (n=15, 29%). Prospective real-world implementation studies and parallel cohort studies were commonly recommended to address these gaps (n=6, 24.0% and n=6, 24.0% respectively). Supportive evidence gaps mostly concern user acceptance, engagement, usability and experience (n=7, 28%), which are proposed to be addressed largely by patient surveys (n=6, 31.3%).
CONCLUSIONS: The results show that fundamental evidence around the technology’s efficacy is common but of insufficient quantity for an NHS setting. Pragmatic real-word evidence approaches are frequently proposed in the EGPs where possible, but the frequency of proposed prospective cohort studies suggest RWE approaches are not always feasible. The technologies are mainly patient-facing, digital tools that support clinical management.
Conference/Value in Health Info
2025-11, ISPOR Europe 2025, Glasgow, Scotland
Value in Health, Volume 28, Issue S2
Code
HTA144
Topic
Health Policy & Regulatory, Health Technology Assessment, Real World Data & Information Systems
Topic Subcategory
Systems & Structure
Disease
No Additional Disease & Conditions/Specialized Treatment Areas