ArticleJournal of the American Medical Informatics Association : JAMIA2025
National COVID Cohort Collaborative data enhancements: a path for expanding common data models.
Article in Journal of the American Medical Informatics Association : JAMIA, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
5 citing papers in PubMed.
- Article
- Opportunities and Challenges in Using National EHR Networks for AI in Learning Health Systems.Learning health systems · 2026Article
- Evaluating Redundancy and Biases in EHR Social Determinants of Health Data Screening.medRxiv : the preprint server for health sciences · 2026Article
- Data science for pediatric infectious disease: utilizing COVID-19 as a model.Current opinion in infectious diseases · 2025Review
- Evaluating the safety of XBB.1.5-containing COVID-19 mRNA vaccines using a self-controlled case series study.Nature communications · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
12 authors.
Funding
Abstract
objectiveTo support long COVID research in National COVID Cohort Collaborative (N3C), the N3C Phenotype and Data Acquisition team created data designs to aid contributing sites in enhancing their data. Enhancements include long COVID specialty clinic indicator; Admission, Discharge, and Transfer transactions; patient-level social determinants of health; and in-hospital use of oxygen supplementation. MATERIALS AND
methodsFor each enhancement, we defined the scope and wrote guidance on how to prepare and populate the data in a standardized way.
resultsAs of June 2024, 29 sites have added at least one data enhancement to their N3C pipeline. DISCUSSION: The use of common data models is critical to the success of N3C; however, these data models cannot account for all needs. Project-driven data enhancement is required. This should be done in a standardized way in alignment with common data model specifications. Our approach offers a useful pathway for enhancing data to improve fit for purpose.
conclusionIn this initiative, we rapidly produced project-specific data modeling guidance and documentation in support of long COVID research while maintaining a commitment to terminology standards and harmonized data.
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What OpenQuestion holds
Registered trials
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.