Real-World Use of Controlled Terminologies, Ontologies, and Vocabularies for Evidence Generation Across a Large International Observational Network: Challenges and Lessons Learned...

The useful part

Despite widespread adoption of standardized vocabularies, their effective use and long-term sustainability at scale remain poorly understood. This study aimed to examine real-world terminology and code use in data across a federated network of observational data sources. The survey covered 144 institutions across the United States, the United Kingdom, Europe, Asia, and Africa.

How it works

• Data on terminology use covered 60 sources, including 22 data sources that provided detailed code-level use information.
• We observed significant variations in terminology use, with 61 out of 89 terminologies used in the data present in less than 10% of the data sources.
• Code use even after data harmonization was also highly variable: less than 1% (95/742,337) of codes were found in all data sources.
• We outlined several of our subsequent process improvements: community contribution and stewardship pipelines, metadata for relationships, and informatics tools for assessment of the impact of terminology...
• Terminology and coding inconsistencies across observational data sources require a standardized terminology system.

What to take from it

Mapping and hierarchy completeness, terminology coverage, versioning, and terminology changes were among the most common challenges. Such a system is complex and time-consuming and needs community contribution and informatics solutions for harmonization to be scalable and sustainable. Even with a common reference standard, high heterogeneity of terminology and code use across different observational data sources remains.

Example or evidence

• We conducted a 2-part survey of researchers and data owners within the Observational Health Data Sciences and Informatics community on their terminology use, challenges, and needs, accompanied by the...