This fact sheet dispels common misconceptions about OMOP conversions. It addresses fears of data loss, accuracy decline, vocabulary mapping errors, and excessive conversion time. Evidence from validation studies (e.g., DA France, LPD France, EMA on IMRD UK) shows minimal differences between native and OMOP datasets, with strong data integrity preserved. OMOP continues to evolve, adding oncology extensions and other domain-specific models to meet new analytical needs. It also retains native source codes, mapping them to standardized vocabularies for interoperability. By debunking myths, IQVIA demonstrates OMOP’s value in enabling scalable, reliable, and reproducible real-world analytics.

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