Maximizing the Value of Real-World Data in HEOR: A Comparative Assessment of Claims and EMR Sources in Europe
Author(s)
Diehl M, Saikumar S, Furrer DE, Kulkarni A, Patel N, Hadker N
Trinity Life Sciences, Waltham, MA, USA
Presentation Documents
OBJECTIVES: Heterogeneity in the European RWD landscape, both regionally and across vendors, requires fit-for-purpose dataset selection in HEOR studies. Visibility into RWD elements is crucial for appropriate selection for region-specific, care setting specific use-cases. This research outlines the available data sources and evaluates their advantages and limitations.
METHODS: A framework was developed around European EMR and payer claims data to characterize each dataset’s ability to address research questions, including epidemiology and HCRU across Europe. A representative sample of third-party data vendors (e.g., TriNetX, IQVIA, Cegedim) was systematically compared with national payer databases, identifying country-specific nuances and dataset considerations specific to HEOR use-cases.
RESULTS: Payer-based claims datasets displayed higher utility in HEOR study design due to larger sample sizes, range of capture across care settings, and ability to track patients longitudinally relative to EMR datasets. Most European claims data (e.g., in Germany and France, and to a lesser extent in Italy) are sourced directly from public payer databases, with major limitations being publication requirements and extensive timelines to data access. EMR data, while providing higher clinical specificity, was limited by lack of consistent tokenization, capture across geographies, and care settings. Cegedim EMR, for example, covers 4.5M patients in France across 2,000 GPs, while covering only 9k patients in Italy across 550 GPs. IQVIA EMR data covers a comparable volume of patients in France (i.e., 4.7M), but is sourced more substantially from specialists (2.8M patients) compared to GPs (1.9M patients).
CONCLUSIONS: Myriad RWD is available for HEOR studies in Europe. Where substantial clinical or patient cohort specificity is required (e.g., TA-specific burden of illness), EMR data vendors with varying geographical and care setting coverage can meet this demand. For many other use-cases (e.g., epidemiology, HCRU quantification), payer claims data is preferred due to its capacity for longitudinal capture and breadth of coverage.
Conference/Value in Health Info
Value in Health, Volume 27, Issue 12, S2 (December 2024)
Code
RWD8
Topic
Epidemiology & Public Health, Real World Data & Information Systems, Study Approaches
Topic Subcategory
Electronic Medical & Health Records, Health & Insurance Records Systems
Disease
No Additional Disease & Conditions/Specialized Treatment Areas