[Real-world data in clinical research: a review of data models and supporting informatics systems]

Real-world data (RWD) are increasingly used for secondary purposes in evidence-based medicine; however, differences between data collected in various healthcare systems pose challenges to generating reliable real-world clinical evidence (RWE). The Observational Medical Outcomes Partnership Common Data Model (OMOP CDM) is an international data model and toolset that provides a harmonized structure and semantics for heterogeneous data sources, thereby supporting large-scale, reproducible research and the production of comparable results. The data model enables data holders to retain their data within local systems, while only aggregated analytical outputs are shared through a federated network connecting multiple databases, in line with data protection and regulatory requirements. The aim of this narrative review is to describe the structure and operational logic of the OMOP CDM, to summarize the key principles of data standardization and data quality assessment, and to present international and national initiatives that apply this data utilization framework. The use of the data model facilitates the generation of high-quality, comparable and clinically relevant evidence, thereby enhancing patient safety, improving the quality of healthcare services and supporting clinical decision-making. Orv Hetil. 2026; 167(17): 661-672.