Samenvatting

Abstract from EHRCON25-openEHR International Conference 2025. The increasing demand for structured high-quality clinical data for AI and decision support systems highlights the shortcomings of current healthcare data infrastructure, particularly its misalignment with FAIR [1] data principles (Findable, Accessible, Interoperable, Reusable). In radiotherapy, clinical information is fragmented across systems, each with its own data model. This heterogeneity limits secondary data use for applications like research, business intelligence, and AI. Although existing standards like DICOM [2] provide extensive technical imaging and treatment delivery persistence capabilities, the clinical context (e.g. diagnosis, toxicity, treatment intention) is not covered. openEHR has emerged as a promising solution, offering semantic consistency through archetype-based modeling and growing interoperability with standards like OMOP and FHIR [3]. This study aimed to evaluate openEHR as a unified data platform for radiotherapy at Isala