Observational studyJournal of the American Medical Informatics Association : JAMIA2022
Transforming and evaluating the UK Biobank to the OMOP Common Data Model for COVID-19 research and beyond.
Observational study in Journal of the American Medical Informatics Association : JAMIA, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 29 papers, 1 of them a synthesis that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
29 citing papers in PubMed, 1 synthesis or guideline pooled it.
- A systematic review of data sources for artificial intelligence applications in pediatric brain tumors in Europe: implications for bias and generalizability.Frontiers in oncology · 2023Pooled it
- Review
- Extending the Observational Medical Outcomes Partnership Common Data Model to Support Observational Peripheral Vascular Disease Research.The Journal of surgical research · 2026Observational
- Data harmonization processes of cancer data into the observational medical outcomes partnership common data model.Scientific reports · 2026Article
- Extending the Observational Medical Outcomes Partnership (OMOP) Common Data Model for Critical Care Medicine: A Framework for Standardizing Complex ICU Data Using the Society of Critical Care Medicine's Critical Care Data Dictionary (C2D2).Critical care medicine · 2026Article
- Using ontologies to facilitate healthcare process mining and analysis.Journal of intelligent information systems · 2026Article
- Establishing standards: harmonising coding principles for a minimal cancer dataset in the OMOP Common Data Model.ESMO real world data and digital oncology · 2025Article
- Advancing Real-World Evidence Through a Federated Health Data Network (EHDEN): Descriptive Study.Journal of medical Internet research · 2025Article
- Multi-domain rule-based phenotyping algorithms enable improved GWAS signal.NPJ digital medicine · 2025Article
- KEEP: Integrating Medical Ontologies with Clinical Data for Robust Code Embeddings.Proceedings of machine learning research · 2025Article
- Breaking Digital Health Barriers Through a Large Language Model-Based Tool for Automated Observational Medical Outcomes Partnership Mapping: Development and Validation Study.Journal of medical Internet research · 2025Article
- Deep representation learning for clustering longitudinal survival data from electronic health records.Nature communications · 2025Article
- A machine learning approach to leveraging electronic health records for enhanced omics analysis.Nature machine intelligence · 2025Article
- Informatics assessment of COVID-19 data collection: an analysis of UK Biobank questionnaire data.BMC medical informatics and decision making · 2024Article
- Artificial intelligence-enhanced patient evaluation: bridging art and science.European heart journal · 2024Review
- Transforming Primary Care Data Into the Observational Medical Outcomes Partnership Common Data Model: Development and Usability Study.JMIR medical informatics · 2024Article
- Centralized and Federated Models for the Analysis of Clinical Data.Annual review of biomedical data science · 2024Review
- Conceptual design of a generic data harmonization process for OMOP common data model.BMC medical informatics and decision making · 2024Review
- Applying an ELSI lens to real-world data and novel genomic insights for personalized mental healthcare.Frontiers in genetics · 2024Review
- Cross Biobank Comparison of Phenomic Profiles.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2024Article
Corrections and comments
- Erratum issued
Authors and funding
12 authors.
Funding
Abstract
objectiveThe coronavirus disease 2019 (COVID-19) pandemic has demonstrated the value of real-world data for public health research. International federated analyses are crucial for informing policy makers. Common data models (CDMs) are critical for enabling these studies to be performed efficiently. Our objective was to convert the UK Biobank, a study of 500 000 participants with rich genetic and phenotypic data to the Observational Medical Outcomes Partnership (OMOP) CDM. MATERIALS AND
methodsWe converted UK Biobank data to OMOP CDM v. 5.3. We transformedparticipant research data on diseases collected at recruitment and electronic health records (EHRs) from primary care, hospitalizations, cancer registrations, and mortality from providers in England, Scotland, and Wales. We performed syntactic and semantic validations and compared comorbidities and risk factors between source and transformed data.
resultsWe identified 502 505 participants (3086 with COVID-19) and transformed 690 fields (1 373 239 555 rows) to the OMOP CDM using 8 different controlled clinical terminologies and bespoke mappings. Specifically, we transformed self-reported noncancer illnesses 946 053 (83.91% of all source entries), cancers 37 802 (70.81%), medications 1 218 935 (88.25%), and prescriptions 864 788 (86.96%). In EHR, we transformed 13 028 182 (99.95%) hospital diagnoses, 6 465 399 (89.2%) procedures, 337 896 333 primary care diagnoses (CTV3, SNOMED-CT), 139 966 587 (98.74%) prescriptions (dm+d) and 77 127 (99.95%) deaths (ICD-10). We observed good concordance across demographic, risk factor, and comorbidity factors between source and transformed data. DISCUSSION AND
conclusionOur study demonstrated that the OMOP CDM can be successfully leveraged to harmonize complex large-scale biobanked studies combining rich multimodal phenotypic data. Our study uncovered several challenges when transforming data from questionnaires to the OMOP CDM which require further research. The transformed UK Biobank resource is a valuable tool that can enable federated research, like COVID-19 studies.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.