GUIDANCE ON REAL-WORLD DATA QUALITY FOR MEDICAL DEVICE ARTIFICIAL INTELLIGENCE TO INFORM HTA AND REIMBURSEMENT ACROSS THE EUROPEAN UNION: A SCOPING REVIEW
Author(s)
Silvia Moler, PhD1, Wendy Nieto Gutiérrez, MSc1, Marina Vilella, MSc1, Régis Lassalle, MSc2, Yannick Binois, MSc3, Lauriane Armand, MSc2, Sandrine Boulet, PhD3, Sarah Zohar, PhD4, Persephone Doupi, PhD5, Vilma Piironen, MSc5, Corinne Collignon, PhD6, Pauline Cohen, MSc2, Soledad Isern de Val, PhD1.
1Aragon Health Sciences Institute, Zaragoza, Spain, 2Health Data Hub, Paris, France, 3Institut National de Recherche en Sciences et Technologies du Numérique, Paris, France, 4Institut National de la Santé et de la Recherche Médicale, Paris, France, 5Finnish Institute for Health and Welfare, Helsinki, Finland, 6Haute Autorité de Santé, Paris, France.
1Aragon Health Sciences Institute, Zaragoza, Spain, 2Health Data Hub, Paris, France, 3Institut National de Recherche en Sciences et Technologies du Numérique, Paris, France, 4Institut National de la Santé et de la Recherche Médicale, Paris, France, 5Finnish Institute for Health and Welfare, Helsinki, Finland, 6Haute Autorité de Santé, Paris, France.
OBJECTIVES: Medical device artificial intelligence (MDAI) requires high-quality real-world data (RWD) for reliable performance. As the European Health Data Space (EHDS) expands secondary use of health data, clearer expectations are needed to support consistent evaluation and timely access. This scoping review mapped EU guidance on RWD quality for MDAI and its implications for HTA and reimbursement.
METHODS: A scoping review was conducted to identify guidance addressing RWD quality relevant to MDAI in EU HTA and reimbursement contexts. Three databases were searched and complemented by structured grey literature searches. Eligible documents included guidance, frameworks, checklists, reports, submission requirements, and related materials providing recommendations relevant to RWD quality. To contextualise the review findings, a descriptive mapping across EHDS countries for MDAI was conducted. Bibliographic and document characteristics were described. Each recommendation related to RWD quality was characterised according to the data quality domain, lifecycle stage, purpose, and the role of RWD in assessment and reimbursement decision-making.
RESULTS: Landscape showed variation across EHDS countries in HTA bodies, reimbursement institutions, and MDAI-related evidence generation schemes. Preliminary results included 36 guidance documents: 31 checklists (86.1%) and 5 other guidance documents (13.9%). Most were published from 2023 onwards, with an increasing trend up to 2025. Half targeted both data curators and data users (50.0%), while 13 (36.1%) targeted data users only. Most recommendations supported primary study assessment (69.4%), followed by product assessment (27.8%). Most documents were published in Q1 journals; checklists were mainly academically led, while other guidance documents were issued by professional societies, collaborations, or HTA bodies.
CONCLUSIONS: Guidance on RWD quality for MDAI is increasing but remains heterogeneous across EU contexts. Clearer, harmonised, lifecycle-oriented expectations are needed to support consistent HTA and reimbursement decisions, improve predictability, and facilitate timely access to safe and reliable MDAI.
METHODS: A scoping review was conducted to identify guidance addressing RWD quality relevant to MDAI in EU HTA and reimbursement contexts. Three databases were searched and complemented by structured grey literature searches. Eligible documents included guidance, frameworks, checklists, reports, submission requirements, and related materials providing recommendations relevant to RWD quality. To contextualise the review findings, a descriptive mapping across EHDS countries for MDAI was conducted. Bibliographic and document characteristics were described. Each recommendation related to RWD quality was characterised according to the data quality domain, lifecycle stage, purpose, and the role of RWD in assessment and reimbursement decision-making.
RESULTS: Landscape showed variation across EHDS countries in HTA bodies, reimbursement institutions, and MDAI-related evidence generation schemes. Preliminary results included 36 guidance documents: 31 checklists (86.1%) and 5 other guidance documents (13.9%). Most were published from 2023 onwards, with an increasing trend up to 2025. Half targeted both data curators and data users (50.0%), while 13 (36.1%) targeted data users only. Most recommendations supported primary study assessment (69.4%), followed by product assessment (27.8%). Most documents were published in Q1 journals; checklists were mainly academically led, while other guidance documents were issued by professional societies, collaborations, or HTA bodies.
CONCLUSIONS: Guidance on RWD quality for MDAI is increasing but remains heterogeneous across EU contexts. Clearer, harmonised, lifecycle-oriented expectations are needed to support consistent HTA and reimbursement decisions, improve predictability, and facilitate timely access to safe and reliable MDAI.
Conference/Value in Health Info
2026-11, ISPOR Europe 2026, Vienna, Austria
Value in Health, Volume 29, Issue 12S
Code
MT37
Topic
Health Technology Assessment, Medical Technologies, Real World Data & Information Systems
Topic Subcategory
Digital Health
Disease
No Additional Disease & Conditions/Specialized Treatment Areas