The global healthcare data ecosystem has various complexities, which include the disparate nature of database types, medical ontologies, and data collection methods, not to mention added layers of complexity due to privacy and security concerns. The OMOP Common Data Model (CDM) has emerged as a game-changer using standardization as a way to revolutionize the way real-world evidence (RWE) is generated and utilized.

OMOP stands for Observational Medical Outcomes Partnership and standardizes and structures the content of observational data to enable efficient federated and standardized analytics that can produce reliable evidence. The OMOP standard is managed by the organization OHDSI (Observational Health Data Sciences and Informatics) which is multi-stakeholder, interdisciplinary, open-science collaborative to bring out the value of health data through large-scale analytics.

This presentation will give and introduction to OMOP and will focus on why OMOP is at the forefront of discussions in the healthcare community and what you need to know to leverage its full potential. In more detail, we will:

• Explore the origins and development of the OMOP CDM, exploring its fundamental principles and structure, and explaining how OMOP standardizes healthcare data to facilitate seamless integration and analysis.
• Show how OMOP's approach enhances data interoperability and benefits multi-country and multi-institutional studies, such as federated research network model and its global scalability.
• Explore the methodologies and tools used in OMOP-driven analytics, which offer solutions for faster, more reliable multi-database studies.
• Focus on the collaborative network and community of the global OMOP/OHDSI initiative and the role of community-driven innovation.
• Discuss how OMOP relates to other standardization methods, such as how FHIR and OMOP complement each other to enhance data interoperability.