Evaluation of Real-World Data Landscape in the United Kingdom: A Scoping Review
Author(s)
Nilixa Raval, MDS, MPH1, Nency Joshipura, MD1, Ami Vyas, MBA, MS, PhD2, Amit D. Raval, PhD3.
1Nyra Health LLC, Piscataway, NJ, USA, 2The University of Rhode Island, Kingston, RI, USA, 3University of North Texas Health Science Center, Fort Worth, TX, USA.
1Nyra Health LLC, Piscataway, NJ, USA, 2The University of Rhode Island, Kingston, RI, USA, 3University of North Texas Health Science Center, Fort Worth, TX, USA.
OBJECTIVES: The United Kingdom (UK) comprises England, Scotland, Wales, and Northern Ireland, with a population of over 67 million. Given the emphasis on real-world evidence from regulatory bodies, it is critical to understand the breath of real-world data (RWD) as a first step; therefore, we conducted a scoping review to summarize the RWD landscape within the UK.
METHODS: We systematically searched the bibliographic database, PubMed (from 2019 to March 2024), and European Medical Agency (EMA) RWD catalogues to identify published studies utilizing ≥ 1 RWD(s) [claims, electronic medical records (EMR), registries, or others].
RESULTS: Of 750 retrieved citations, 377 studies with 106 distinct RWD sources met inclusion. The most common sources of RWDs were EMRs followed by registries, claims, consortium, app-based or specific cohort data, and survey. CRPD Gold/Aurum, THIN/IQVIA, SAIL, OpenSAFELY, and Optimum were frequently utilized EMR sources originating from general practice settings, with representation to 4% to 25% of the UK population. Vocabulary for conditions was a mix of ICD-10, read code, or SNOMED-CT; whereas for medications, these were a mix of dm+d, gemscript, ATC or read code within the EMR databases. Trauma, rare diseases, oncology, cardio-metabolic registries were frequently utilized registries. Chart-review-based data from a volunteer survey of physicians was a common type of survey data. Most of the RWDs had a lag time of at least 6 months and required case-by-case data access upon the review of research projects. The majority of EMRs were available within common-data models and with the ability to link with hospital episode statistics, mortality registry, chemotherapy and radiotherapy medication databases.
CONCLUSIONS: The findings highlight the widespread use of RWDs across multiple therapeutic areas in the UK, with predominantly EMR sources. The ability to link across distinct databases shows potential for use across numerous therapeutic areas, enriching the depth of the database; albeit with limited recency.
METHODS: We systematically searched the bibliographic database, PubMed (from 2019 to March 2024), and European Medical Agency (EMA) RWD catalogues to identify published studies utilizing ≥ 1 RWD(s) [claims, electronic medical records (EMR), registries, or others].
RESULTS: Of 750 retrieved citations, 377 studies with 106 distinct RWD sources met inclusion. The most common sources of RWDs were EMRs followed by registries, claims, consortium, app-based or specific cohort data, and survey. CRPD Gold/Aurum, THIN/IQVIA, SAIL, OpenSAFELY, and Optimum were frequently utilized EMR sources originating from general practice settings, with representation to 4% to 25% of the UK population. Vocabulary for conditions was a mix of ICD-10, read code, or SNOMED-CT; whereas for medications, these were a mix of dm+d, gemscript, ATC or read code within the EMR databases. Trauma, rare diseases, oncology, cardio-metabolic registries were frequently utilized registries. Chart-review-based data from a volunteer survey of physicians was a common type of survey data. Most of the RWDs had a lag time of at least 6 months and required case-by-case data access upon the review of research projects. The majority of EMRs were available within common-data models and with the ability to link with hospital episode statistics, mortality registry, chemotherapy and radiotherapy medication databases.
CONCLUSIONS: The findings highlight the widespread use of RWDs across multiple therapeutic areas in the UK, with predominantly EMR sources. The ability to link across distinct databases shows potential for use across numerous therapeutic areas, enriching the depth of the database; albeit with limited recency.
Conference/Value in Health Info
2025-11, ISPOR Europe 2025, Glasgow, Scotland
Value in Health, Volume 28, Issue S2
Code
RWD79
Topic
Epidemiology & Public Health, Methodological & Statistical Research, Real World Data & Information Systems
Topic Subcategory
Data Protection, Integrity, & Quality Assurance, Distributed Data & Research Networks, Health & Insurance Records Systems
Disease
Cardiovascular Disorders (including MI, Stroke, Circulatory), No Additional Disease & Conditions/Specialized Treatment Areas, Oncology, Personalized & Precision Medicine, Rare & Orphan Diseases