Evidence map›Paper›PMID 39226057›Full record

ArticleJAMA network open2024

Error Rates in Race and Ethnicity Designation Across Large Pediatric Health Systems.

Gary L Freed, Brittany Bogan, Adam Nicholson, Deborah Niedbala, Susan Woolford

Abstract read
In one paragraph

Article in JAMA network open, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Assessing insurance claims as a measure for outpatient antimicrobial stewardship.Antimicrobial stewardship & healthcare epidemiology : ASHE · 2025
    Article
  9. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Gary L FreedMichigan Child Health Equity Collaborative, Ann Arbor.
Brittany BoganC. S. Mott Children's Hospital and Von Voigtlander Women's Hospital, Ann Arbor, Michigan.
Adam NicholsonCorewell Health Helen DeVos Children's Hospital, Grand Rapids, Michigan.
Deborah NiedbalaChildren's Hospital of Michigan, Detroit.
Susan WoolfordMichigan Child Health Equity Collaborative, Ann Arbor.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Importance: Without knowledge of the degree of misattribution in racial and ethnic designations in data, studies run the risk of missing existing inequities and disparities and identifying others that do not exist. Further, accuracy of racial and ethnic designations is important to clinical care improvement efforts and health outcomes. Objective: To determine the error rate of racial and ethnic attribution in the electronic medical records (EMRs) across the 3 largest pediatric health systems in Michigan. Design, Setting, and Participants: This cross-sectional study collected race and ethnicity data from parents in outpatient clinics, emergency departments, and inpatient units at the 3 largest pediatric health systems in Michigan. A total of 1594 parents or guardians participated at health system A, 1537 at health system B, and 1202 at health system C from September 1, 2023, to January 31, 2024. Parent or guardian report of race and ethnicity for a child was used as the gold standard for comparison with the designation in the EMR. Exposure: Race and ethnicity designations in the EMR. Options for race designation across the health systems ranged from 6 to 49; options for ethnicity, from 2 to 10. Main Outcomes and Measures: Matching occurred in 3 stages. First, the exact racial and ethnic designations made by parents for their child were compared with what was found in the EMR. Second, for any child whose parent selected more than 1 racial category or for whom more than 1 appeared in the EMR, the designation of a minoritized racial group was used for matching purposes. Third, starting with the product of stage 2, racial designations were combined or collapsed into 6 (health systems A and C) or 5 (health system B) designations. Results: A total of 4333 survey responses were included in the analysis. The greatest error rate across the health systems occurred with the exact match of parental report of racial designation with the EMR, which ranged from 41% to 78% across the health systems. Improvement in the matching rate for each health system occurred with consolidation of race options provided. Differences between the health systems narrowed at the final consolidation to varying from 79% to 88% matching. Ethnicity matching between the EMR and the parental report ranged from 65% to 95% across the health systems. Missing race or ethnicity data in the EMR was counted as a nonmatch. Rates of missing racial data varied across the health systems from 2% to 10%. The health system with the greatest number of options for race and ethnicity had the highest error rates. Conclusions and Relevance: Although there will always be some misattribution of race and ethnicity in the EMR, the results of this cross-sectional study suggest that significant error in these data may undermine strategies to improve care. It is unclear whether those in an organization who determine the number of potential categories are the same persons who use those data to investigate potential disparities and inequities.

Indexed as

Electronic Health RecordsEthnicityRacial GroupsAdolescentChildChild, PreschoolCross-Sectional StudiesFemaleHumansInfantMaleMichiganPediatrics

Identifiers

PMID39226057
PMCPMC11372483

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.