Using OMOP and Other Real World Data Standards to Support Regulatory Submissions

The scope of the project includes developing awareness of data standards specific to real-world data to support regulatory purposes. Common data models (CDMs) and taxonomies that are specific to the most commonly used real-world data sources by industry, member companies and regulatory bodies across the globe will be in scope, such as electronic health record sources, patient reported outcomes, widely accepted claims data sources, and other commonly used observational data. OMOP and the OHDSI community will be the focus, and will be evaluated against other CDMs and standards (such as PCORnet, Sentinel and CDISC).

OMOP is fully endorsed by the EMA with a mature community and a code base, whereas other global health agencies have different guidance, with commonalities and differences. This leads to decreased quality and efficiency as data are transformed one or multiple times to match standards across regulatory bodies.

This project plans to develop a white paper detailing emerging and mature data standards for real-world data, such as OMOP, along with why different standards work better for different data types and use cases. The white paper will also look at the maturity of different standards, and communities and code available. This project aims to initiate dialogue about using these standards for submission purposes to help transportability and other issues.