This deliverable introduces the work done on the data quality metadata and the common data models for head and neck cancers and sarcomas within the IDEA4RC project.
At the start of the project, it soon became apparent that existing oncological data models, such as OMOP, OSIRIS, and mCODE, presented significant limitations for our scopes.
While OMOP provided a broad framework, its oncology-specific extensions were incomplete and not well-suited for representing longitudinal cancer progression, recurrence, and complex treatment pathways.
OSIRIS and mCODE, though promising, lacked maturity, with slow model finalisation and limited adoption in real-world clinical settings. Additionally, these models were often not user-friendly for clinicians and researchers without deep technical expertise, creating barriers to efficient data utilization and analysis.
The need for an oncology data model that balanced interoperability, usability, and research applicability became evident.
IDEA4RC sought to address these challenges by developing a dedicated data model tailored to the needs of cancer care and research. The model was designed to integrate with existing standards while offering a clinician-friendly structure that accurately represents cancer evolution over time.
A working group of experts iteratively refined the model, ensuring it was practical, intuitive, and aligned with real-world oncology workflows. By prioritising usability, longitudinal data representation, and seamless querying capabilities, the IDEA4RC data model filled a critical gap, enabling more effective data-driven cancer research and patient care.
You can download the deliverable here.