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. 2020 Jun 25;4(4):e10233. doi: 10.1002/lrh2.10233

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© 2020 The Authors. Learning Health Systems published by Wiley Periodicals LLC on behalf of the University of Michigan.

This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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Experimental architecture. Box (1) shows the developed CQL on OMOP engine, box (2) the OHDSI data platform, box (3) the OMOP on FHIR data transformation tool, and box (4) the FHIR‐native stack used for cross‐platform validation. Box (1) shows our newly developed software, while boxes (2) to (4) are existing systems we leveraged. Pipelines (5) and (6) show the two validation methods. Both NM and WCM used the pipeline (5) architecture with their own data for phenotype execution. CQL, Clinical Quality Language; FHIR, Fast Healthcare Interoperability Resources; NM, Northwestern Medicine; OHDSI, Observational Health Data Sciences and Informatics; OMOP, Observational Medical Outcomes Partnership; WCM, Weill Cornell Medicine. [Correction added on 2 September 2020, after first online publication: Figure 2 has been revised.]