ArticleJournal of racial and ethnic health disparities2026
Race and Ethnicity Data in the Electronic Health Records: New Insights Through Comparison with American Community Survey Microdata.
Article in Journal of racial and ethnic health disparities, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 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
2 citing papers in PubMed.
- Evaluating the impact of discordant and missing demographic information on population health assessments using linked electronic health records and Census Bureau microdata.PLOS digital health · 2026Article
- Caring for Communities: Comparing Health Care System Patient Populations to Regional Populations.Journal of general internal medicine · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
The collection of race and ethnicity information varies across data sources which impacts our ability to conduct high quality research focused on population health, generally, and racial and ethnic disparities in health, specifically. This research examines concordance in racial/ethnic identification between two sources by linking individual-level electronic health record (EHR) data (2017-2019) from a public integrated health delivery system in North Carolina to American Community Survey (ACS) microdata (2001-2017). We find that concordance is high for individuals who identify as non-Hispanic Black, non-Hispanic White, and Hispanic but considerably lower for other non-White, non-Hispanic individuals, particularly for American Indian and Alaska Native patients. Given their detailed health information, EHR data have the potential to support research focused on population health and racial and ethnic disparities. Results from this study provide information regarding data quality and future applications of this work to expand population research.
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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.