ArticleJournal of racial and ethnic health disparities2025
Making Oneself "Fit": Community Perspectives on Disaggregated Race and Ethnicity Data Collection and Reporting in Healthcare Settings.
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 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.
- A novel surname-based methodology to improve the disaggregation of Asian American ethnic subgroups in patients with ovarian cancer.Gynecologic oncology reports · 2026Article
- Decreasing missingness in race and ethnicity data by inclusion of preferred language for mapping to aggregate categories.Health affairs scholar · 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
8 authors.
Funding
Abstract
Patient race/ethnicity data collection in most U.S. health systems abide by federal standards, determined by the federal Office of Management and Budget. Yet, decades of research show that reliance on these categories alone limits understanding of within-group health disparities, systematically erasing key groups from health data. Because granular race/ethnicity data is complex and patients may be hesitant to disclose this personal information, it is important for health leaders to consider community perspectives when making decisions about race/ethnicity data procedures. As such, this study uses community focus groups to understand: (1) how individuals representing different racial/ethnic identities perceive the collection of race/ethnicity in healthcare settings; (2) differences in opinions between disaggregated race/ethnicity data collection instruments and those using federal standards; and (3) recommended practices for collecting race/ethnicity from patients. Participants self-selected into 13 focus groups and one key informant interview based on the race/ethnicity with which they most closely identified. Audio recordings from these groups were transcribed and evaluated using thematic content analysis. Among the 83 total participants in this study, there was a strong preference for more flexible and specific options for self-identifying race/ethnicity in healthcare settings. Participants also felt comfortable disclosing granular race/ethnicity to health providers but expressed discomfort with disclosing this information for other purposes. Recommendations for healthcare leaders include ensuring patients receive detailed communication about race/ethnicity data use and purpose, allowing multiple category selection, keeping the list of disaggregated response options short so as to not overwhelm patients, and providing a free text option to ensure inclusivity.
Indexed as
Identifiers
38411798What 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.