Preparing real-world data through common data model harmonization of cancer patient records in the COMNet platform at the Modena Oncology Center

ObjectivesThe transition from paper medical records to electronic health records (EHRs) has enabled the extraction of substantial real-world data, which can support future real-world evidence generation. This study aimed to convert heterogeneous oncology data from local EHR systems—collectively referred to as COMNet—into a standardized data model. In particular, the Observational Medical Outcomes Partnership Common Data Model (OMOP-CDM) was adopted to harmonize routinely collected clinical data into a common database, thereby enabling standardized secondary use and large-scale analyses.MethodsDemographic and clinical parameters routinely collected at the Modena Cancer Center were retrospectively extracted from COMNet and harmonized into the OMOP-CDM through an Extract–Transform–Load process supported by the European Health Data and Evidence Network (EHDEN).ResultsWe identified 85,026 persons with at least one recorded condition occurrence. Discrepancies were observed across OMOP-CDM domains—particularly in visit occurrence and drug exposure—reflecting changes in documentation practices and source systems over time. The temporal trend of data migration to the electronic platform revealed two significant peaks, corresponding to initial data entry and subsequent digitalization of hospital facilities and pharmacy records.DiscussionThe harmonization process revealed data inconsistencies, including incompleteness and missing data, reflecting challenges inherent in the transition from paper-based records to electronic systems and the coexistence of different legacy software platform.ConclusionsHarmonizing COMNet data into the OMOP-CDM produced a standardized real-world data resource that can support future observational research and participation in federated network studies. Ongoing initiatives, including the EHDEN project, are supporting the further development of COMNet to improve interoperability and enhance structured data capture.