FACTORS INFLUENCING NICE EARLY USE ASSESSMENTS OF DIGITAL HEALTHTECH AND THEIR ALIGNMENT WITH THE NHS 10 YEAR PLAN
Author(s)
Samuel Owusu Achiaw, MBChB, MPH, Martyna Maria Chabalowska, MSc, Neil Hawkins, MBA, MSc, PhD, Olivia Wu, MSc, PhD.
Health Economics and Health Technology Assessment (HEHTA), University of Glasgow, Glasgow, United Kingdom.
Health Economics and Health Technology Assessment (HEHTA), University of Glasgow, Glasgow, United Kingdom.
OBJECTIVES: The NICE Early-use HealthTech Guidance (previously the Early Value Assessment (EVA)) provides rapid, conditional guidance on promising medical technologies. By targeting national unmet needs, EVAs support the NHS’s long-term vision, including the 10 Year Health Plan. This study examines factors influencing recommendations of digital healthTechs and evaluates their alignment with NHS aspirations.
METHODS: A policy document analysis was conducted using an inductive thematic approach and the READ framework. Eligible EVAs were those that were on digital health technologies and fully published by the end of 2025. Data was extracted from NICE guidance documents (including committee discussions) and evidence generation plans. Factors shaping committee decisions to recommend technologies for early use or restrict them to research were identified. Technologies were further assessed to determine how they aligned with the three aspirational shifts outlined in the NHS 10 Year Health Plan.
RESULTS: Across 22 EVAs covering 142 technologies, 12 were recommended for use while evidence is generated, two restricted to research, and eight received mixed recommendations. Early-use technologies showed potential to address unmet needs by relieving capacity constraints, improving access or outcomes. Evidence on clinical effectiveness and cost-effectiveness was generally limited and lacked UK generalisability; technologies with no or minimal evidence, or likely to increase cost without clear patient benefit were restricted to research. Nineteen EVAs aligned with the NHS shift from analogue to digital, 10 with the shift from hospital to community care, and one with the shift from sickness to prevention.
CONCLUSIONS: Understanding the EVA decision processes can help developers, clinicians, and stakeholders identify technologies likely to be recommended for early use in the NHS and further shape innovation pipelines to meet NHS needs. Broader inclusion of diverse digital technologies (supporting various health/clinical needs and across various health conditions) in the EVAs is necessary to fully realise NHS long-term aspirations.
METHODS: A policy document analysis was conducted using an inductive thematic approach and the READ framework. Eligible EVAs were those that were on digital health technologies and fully published by the end of 2025. Data was extracted from NICE guidance documents (including committee discussions) and evidence generation plans. Factors shaping committee decisions to recommend technologies for early use or restrict them to research were identified. Technologies were further assessed to determine how they aligned with the three aspirational shifts outlined in the NHS 10 Year Health Plan.
RESULTS: Across 22 EVAs covering 142 technologies, 12 were recommended for use while evidence is generated, two restricted to research, and eight received mixed recommendations. Early-use technologies showed potential to address unmet needs by relieving capacity constraints, improving access or outcomes. Evidence on clinical effectiveness and cost-effectiveness was generally limited and lacked UK generalisability; technologies with no or minimal evidence, or likely to increase cost without clear patient benefit were restricted to research. Nineteen EVAs aligned with the NHS shift from analogue to digital, 10 with the shift from hospital to community care, and one with the shift from sickness to prevention.
CONCLUSIONS: Understanding the EVA decision processes can help developers, clinicians, and stakeholders identify technologies likely to be recommended for early use in the NHS and further shape innovation pipelines to meet NHS needs. Broader inclusion of diverse digital technologies (supporting various health/clinical needs and across various health conditions) in the EVAs is necessary to fully realise NHS long-term aspirations.
Conference/Value in Health Info
2026-11, ISPOR Europe 2026, Vienna, Austria
Value in Health, Volume 29, Issue 12S
Code
HTA156
Topic
Health Technology Assessment, Medical Technologies
Topic Subcategory
Decision & Deliberative Processes
Disease
No Additional Disease & Conditions/Specialized Treatment Areas