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Published on in Vol 14 (2026)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/92727, first published .
OHDSI data landscape: 22 data sources, 144 institutions, 87% confidence, 11% shared codes.

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

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

Anna Ostropolets   1, 2 , MD, PhD ;   Vlad Korsik   3 , MD ;   Tatsiana Skuhareuskaya   3 , MD ;   Aleh Zhuk   3 , MD ;   Maryia Khitrun   3 , MD ;   Alexander Davydov   3 , MD ;   Dmitry Dymshyts   1 , MD ;   Christian Reich   4 * , MD, PhD ;   George Hripcsak   2 * , MD, MS ;   Patrick Ryan   2, 5 * , PhD

1 Observational Health Data Analytics, Johnson & Johnson, Raritan, NJ, United States

2 Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, NY, United States

3 Odysseus, an EPAM Company, Cambridge, MA, United States

4 Nemesis Health, New York, NY, United States

5 Observational Health Data Analytics, Johnson&Johnson (United States), Titusville, NJ, United States

*these authors contributed equally

Corresponding Author:

  • Anna Ostropolets, MD, PhD
  • Observational Health Data Analytics
  • Johnson & Johnson
  • Raritan, NJ 08869
  • United States
  • Email: ao2671@cumc.columbia.edu