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

  • By

  • Anna Ostropolets

  • Vlad Korsik

  • Tatsiana Skuhareuskaya

  • Aleh Zhuk

  • Maryia Khitrun

  • Alexander Davydov

  • Dmitry Dymshyts

  • Christian Reich

  • George Hripcsak

  • Patrick Ryan

  • September 15, 2026

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Objective:

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.

Sources:

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