Real-World Use of Controlled Terminologies, Ontologies, and Vocabularies for Evidence Generation Across a Large International Observational Network: Challenges and Lessons Learned From a Mixed Method Study - Summary - MDSpire
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Utilization of Standardized Terminologies, Ontologies, and Vocabularies for Evidence Generation in a Global Observational Network: Insights and Challenges from a Mixed Methods Analysis
To systematically examine terminology and code use across real-world data sources participating in a global federated network.
Approach:
Quantitative Assessment: Quantitative assessments of terminology content and usage patterns were conducted.
Qualitative Evidence: Qualitative evidence was gathered from expert interviews to identify recurring use patterns and operational challenges.
Key Findings:
Variation in data acquisition and coding can be addressed through Common Data Models (CDMs) and data harmonization.
The Observational Health Data Sciences and Informatics (OHDSI) network has implemented interoperable ontologies for standardized research tools.
Empirical evidence on the practical research use of individual terminologies within OHDSI Standardized Vocabularies is limited.
Previous literature identified issues in terminology systems, including incomplete domain coverage and hierarchical inconsistencies.
Interpretation:
This study systematically examines the scale, complexity, and limitations of terminology integration in applied observational research.
Limitations:
Limited empirical evidence regarding the practical research use of individual terminologies.
Uncertainty about how a centralized terminology system accommodates heterogeneous clinical data sources.
Conclusion:
This study delineates methodological, process-related, and informatics solutions needed to maintain a common terminology standard across diverse data sources.
by Anna Ostropolets, Vlad Korsik, Tatsiana Skuhareuskaya, Aleh Zhuk, Maryia Khitrun, Alexander Davydov, Dmitry Dymshyts, Christian Reich, George Hripcsak, Patrick Ryan