At the European OHDSI Symposium 2026 in Rotterdam, project partner NETCOMPANY presented a poster on disease-aware harmonisation of Parkinson’s disease research data to the OMOP Common Data Model (OMOP CDM). The work was carried out in the context of the AI-PROGNOSIS project.

Parkinson’s disease datasets present specific challenges, including study-defined events instead of real-world visits, free-text medical histories, heterogeneous medication descriptions, and disease-specific questionnaires that do not fit neatly into standard OMOP concepts.

To address these challenges, the team applied a systematic methodology for disease-aware harmonisation. The work included mapping more than 9,000 free-text medical condition entries to standardised SNOMED CT concepts, harmonising medication records into consistent RxNorm concepts, and defining custom OMOP concepts for Parkinson’s disease-specific questionnaires used in clinical care.

The poster also highlighted a reusable and reproducible blueprint for future Parkinson’s disease datasets across the OHDSI ecosystem.

As more neurodegenerative disease initiatives transition to OMOP, this work is expected to provide practical guidance for standardising complex, disease-specific data at scale.