ArticleMedical care2026
Geographic Variation in Missing Race and Ethnicity Data in Minimum Data Set 3.0.
Article in Medical care, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
backgroundRace and ethnicity measures in administrative data can vary geographically. The extent of this challenge in US nursing homes is not well described.
objectivesTo describe geographic variation in missing race and ethnicity data in the Minimum Data Set (MDS) 3.0 and Medicare claims, and to compare discrepancies across data sources. RESEARCH
designCross-sectional study. SUBJECTS: Medicare beneficiaries with MDS 3.0 records between 2014 and 2018. The Medicare Beneficiary Summary File provided demographic information. MEASURES: Missingness of MDS race and ethnicity data by state, and misclassification of Medicare race and ethnicity enrollment database (EDB) and Research Triangle Institute (RTI) variables compared with MDS. We calculate the sensitivity, specificity, and positive predictive value of the EDB and RTI variables relative to the MDS.
resultsAmong 18.1 million nursing home residents pooled across 2014-2018, geographic variation in missing race and ethnicity in the MDS 3.0 ranged from 1.2% to 14.7%. Compared with MDS, misclassification of residents classified as Hispanic in MDS ranged from 48.1% to 89.2% for EDB and 0.5% to 44.8% for RTI. Misclassification of residents classified as Asian American/Pacific Islander in MDS ranged from 29.4% to 77.2% for EDB and 12.7% to 65.4% for RTI. Misclassification of residents classified as Black ranged from 0% to 14.2% for EDB and 0% to 16.2% for RTI. Overall, the RTI variables provided better sensitivity and specificity of race and ethnicity than the EDB.
conclusionMissing race and ethnicity data in the MDS varies geographically, as do discrepancies between MDS and EDB and RTI variables. Thoughtful consideration of these issues is recommended when handling missing MDS race and ethnicity data.
Indexed as
Identifiers
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.