Presentation (CTI)

OBJECTIVES: Real-World Data (RWD) plays a critical role in health policy, epidemiology, and pharmaco-economics. In Germany, researchers have relied on fragmented sources - claims from statutory health insurances (GKV), prescription datasets, physician panels, hospital data, and disease registries - often accessed through slow and complex processes. With the launch of the Health Data Lab (HDL) by August 2025, a centralized infrastructure will grant structured access to health data from all 75 million GKV-insured individuals.
METHODS: We compare HDL to major German RWD sources, both publicly available and restricted-access datasets. Comparison criteria include data access timelines, domains (inpatient, outpatient, prescriptions, socioeconomic indicators), costs, governance, regional granularity, analytical capabilities, and update frequency. We also evaluate analytical approaches particularly suited to HDL - such as descriptive/crosssectional analyses and target trial emulation - and identify designs limited by structural or regulatory constraints.
RESULTS: HDL provides access through a legally defined application process within a maximum of 3 months - improving predictability. It offers nationwide, longitudinal data with full population coverage. Although some sickness funds provide quicker access, their datasets often lack representativeness. HDL’s standardized, transparent application process and cost structure promotes equitable access. The platform enables both cross-sectional and longitudinal analyses and is especially powerful for research on regional aspects and rare diseases. To protect patient privacy, data output is limited to aggregate cells with >30 cases, with exceptions (n≥5) for rare conditions under specific safeguards.
CONCLUSIONS: HDL marks a structural advancement in German health data governance. While existing datasets may retain relevance for specific use cases, HDL is expected to become the gold standard for population-based RWD research. Researchers are advised to adapt their study designs to harness its scale, standardization, and analytical potential.