ArticleJournal of racial and ethnic health disparities2025
Leveraging Multiple Administrative Data Sources to Reduce Missing Race and Ethnicity Data: A Descriptive Epidemiology Cross-Sectional Study of COVID-19 Case Relative Rates.
Article in Journal of racial and ethnic health disparities, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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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
1 citing paper in PubMed.
- Comparing Multiple Imputation Methods to Address Missing Patient Demographics in Immunization Information Systems: Retrospective Cohort Study.JMIR public health and surveillance · 2025Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundUnderstanding race and ethnicity (RE) differentials improves health outcomes. However, RE data are consistently missing from electronic laboratory reports, the primary source of COVID-19 case metrics. We addressed the missing RE differentials and compared vaccinated and unvaccinated cases from March 1, 2020, to May 30, 2023, in New York State (NYS), excluding New York City.
methodsThis descriptive epidemiology cross-sectional study linked the NYS Electronic Clinical Laboratory Reporting System (ECLRS) with NYS Immunization Information System (NYSIIS) to address the missing RE data in the ECLRS system. The primary metric was the COVID-19 case relative risk (RR) for each RE relative to white individuals.
resultsThere were 4,212,741 COVID-19 cases with 39% (1,624,818) missing RE data in ECLRS; missing RE data declined to 17% (726,023) after matching with NYSIIS. For those aged 65 years or older (after matching), 42% were missing in 2020, which declined by 17% by 2023. In May 2021, COVID-19 RRs for vaccinated individuals were 1.09 (95% CI 0.90-1.32), 1.11 (95% CI 0.87-1.43), 1.13 (95% CI 0.93-1.39), and 1.89 (95% CI 1.01-3.52), and for unvaccinated individuals were 1.73 (95% CI 1.66-1.82), 0.84 (95% CI 0.78-0.92), 3.10 (95% CI 2.98-3.22), and 3.49 (95% CI 3.05-3.98) respectively for Hispanic, Asian/Pacific Islander, Black people, and American Indian/Alaska Native individuals.
conclusionMatching case data with vaccine registries reduce missing RE data for COVID-19 cases. Disparity was lower in vaccinated than in unvaccinated individuals indicating that vaccination mitigated RE disparities early in the pandemic. This underscores the value of interoperable systems with automated matching for disparity analyses.
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