Key Real-World Data Management Practices for Registry Evaluation and Quality Assurance

Clinical settings generate real-world data (RWD), which offers valuable insights into pharmaceutical effectiveness and safety. Agencies, such as the U.S. Food and Drug Administration (FDA), the European Medicines Agency (EMA), and Pharmaceuticals and Medical Devices Agency (PMDA) of Japan, are increasingly using Real-World Evidence (RWE) in their decision-making processes. Registries play a critical role in RWE studies by systematically collecting patient data. Implementing stringent quality control and quality assurance measures is essential to achieve RWD reliability.

This study identified the essential quality elements for registry-based RWD and developed a proposed data quality management checklist. A scoping review of peer-reviewed literature and regulatory guidelines published between 2001 and 2026 was conducted using PubMed, Embase, and the websites of major regulatory agencies. Eligible studies included those addressing RWD, RWE, and data quality checklist relevant to registry-based research.

In total, 30 sources, comprising 24 publications and 6 institutional guidelines, were included. The analysis identified two core dimensions of data quality: relevance (availability, sufficiency, and representativeness) and reliability (accuracy, completeness, provenance, and timeliness). We developed a quality assessment checklist that addresses the following four key domains: study design, data collection and management, regulatory compliance, and continuous improvement.

The proposed checklist offers a structured framework to enhance the reliability of RWD and enable systematic quality assessment. Future studies should assess its applicability across various research settings. This study supports robust data quality management, benefiting researchers, regulatory agencies, pharmaceutical companies, and healthcare institutions.