Standardizing Healthtech Evidence to Meet NICE Expectations
Author(s)
Victoria K Brennan, PhD1, Nicholas Redman, MSc, BSc2, Abi McArthur-Davies, PhD3.
1Director Strategic Market Access, OPEN Health group, London, United Kingdom, 2Open Health, London, United Kingdom, 3Open Health group, London, United Kingdom.
1Director Strategic Market Access, OPEN Health group, London, United Kingdom, 2Open Health, London, United Kingdom, 3Open Health group, London, United Kingdom.
OBJECTIVES: The National Institute for Health and Care Excellence (NICE) are currently in the process of reforming their “HealthTech” programme, creating uncertainty around their decision-making processes for Early Value Assessments (EVA).
This study aimed to reduce this uncertainty by updating a review of EVAs originally undertaken in 2024. The review examines key learnings from submitted evidence, insights into the types of evidence reviewed, and the recommendations made. Based on this update we consider how NICE’s approach to decision-making for EVAs may have changed since the previous review.
METHODS: All EVAs published between Oct 2024 and June 2025, plus updates to existing EVAs, were identified for review from the NICE website (www.nice.org.uk). For each EVA, the guidance document and evidence generation plan were reviewed. Data on the technologies, clinical and economic evidence, potential benefits, and evidence generation plans were extracted and analysed qualitatively (including the identification of common patterns in evidence types and recommendations) and quantitatively (including descriptive statistics).
RESULTS: Seven EVAs were identified, two for diagnostics and five for interventions. These involved 32 technologies, of which 25 were recommended. Indications included respiratory, orthopaedic, surgery, dermatology/oncology. Technologies included digital, artificial intelligence (AI), and robot assistance.
Comparative studies were prioritised by NICE for assessment. A common criticism was a lack of consistency in research methods and clinical outcomes across technologies within an EVA, along with limited use of validated tools.
Economic evidence was predominantly economic models developed by NICE, which ran comparative analyses. NICE commonly highlighted uncertainties around long-term data, intervention costs, and modelling assumptions.
CONCLUSIONS: HealthTech developers should adopt consistent outcome measures, standardised methodologies, validated tools and appropriate timepoints, alongside the generation of long-term clinical and economic data to better align with NICE’s evolving expectations.
This study aimed to reduce this uncertainty by updating a review of EVAs originally undertaken in 2024. The review examines key learnings from submitted evidence, insights into the types of evidence reviewed, and the recommendations made. Based on this update we consider how NICE’s approach to decision-making for EVAs may have changed since the previous review.
METHODS: All EVAs published between Oct 2024 and June 2025, plus updates to existing EVAs, were identified for review from the NICE website (www.nice.org.uk). For each EVA, the guidance document and evidence generation plan were reviewed. Data on the technologies, clinical and economic evidence, potential benefits, and evidence generation plans were extracted and analysed qualitatively (including the identification of common patterns in evidence types and recommendations) and quantitatively (including descriptive statistics).
RESULTS: Seven EVAs were identified, two for diagnostics and five for interventions. These involved 32 technologies, of which 25 were recommended. Indications included respiratory, orthopaedic, surgery, dermatology/oncology. Technologies included digital, artificial intelligence (AI), and robot assistance.
Comparative studies were prioritised by NICE for assessment. A common criticism was a lack of consistency in research methods and clinical outcomes across technologies within an EVA, along with limited use of validated tools.
Economic evidence was predominantly economic models developed by NICE, which ran comparative analyses. NICE commonly highlighted uncertainties around long-term data, intervention costs, and modelling assumptions.
CONCLUSIONS: HealthTech developers should adopt consistent outcome measures, standardised methodologies, validated tools and appropriate timepoints, alongside the generation of long-term clinical and economic data to better align with NICE’s evolving expectations.
Conference/Value in Health Info
2025-11, ISPOR Europe 2025, Glasgow, Scotland
Value in Health, Volume 28, Issue S2
Code
MT38
Topic
Medical Technologies
Disease
No Additional Disease & Conditions/Specialized Treatment Areas