Evidence map›Paper›PMID 21092309›Full record

ArticleBMC health services research2010

Health plan administrative records versus birth certificate records: quality of race and ethnicity information in children.

Ning Smith, Rajan L Iyer, Annette Langer-Gould, Darios T Getahun, Daniel Strickland, Steven J Jacobsen, Wansu Chen, Stephen F Derose, Corinna Koebnick

Open access · goldAbstract readComparative Study
In one paragraph

Article in BMC health services research, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 40 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
40citing papers in PubMed, 3 pooled it
8.0field-weighted citation impact, top 3% of its field
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

40 citing papers in PubMed, 3 syntheses or guidelines pooled it, 64 citations in OpenAlex.

  1. Pooled it
  2. The quality of social determinants data in the electronic health record: a systematic review.Journal of the American Medical Informatics Association : JAMIA · 2021
    Pooled it
  3. Pooled it
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Illness severity indicators in newborns by COVID-19 status in the United States, March-December 2020.Journal of perinatology : official journal of the California Perinatal Association · 2022
    Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Race and ethnicity on MS presentation and disease course.Multiple sclerosis (Houndmills, Basingstoke, England) · 2020
    Review
  17. Article
  18. Article
  19. Article
  20. 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

9 authors at 1 institution in 1 country.

Ning SmithDepartment of Research and Evaluation, Kaiser Permanente Southern California, Pasadena, CA, USA.
Rajan L Iyer
Annette Langer-Gould
Darios T Getahun
Daniel Strickland
Steven J Jacobsen
Wansu Chen
Stephen F Derose
Corinna Koebnick
Kaiser Permanente · US

Funding

Complications of Severe Childhood ObesityR21DK085395 · NIDDK · KAISER FOUNDATION RESEARCH INSTITUTE · PI KOEBNICK, CORINNA · 2010 to 2011
$384k
NIDDK NIH HHS R21 DK085395NIDDK NIH HHS R21DK085395
6 · The paper itself

Abstract

backgroundTo understand racial and ethnic disparities in health care utilization and their potential underlying causes, valid information on race and ethnicity is necessary. However, the validity of pediatric race and ethnicity information in administrative records from large integrated health care systems using electronic medical records is largely unknown.

methodsInformation on race and ethnicity of 325,810 children born between 1998-2008 was extracted from health plan administrative records and compared to birth certificate records. Positive predictive values (PPV) were calculated for correct classification of race and ethnicity in administrative records compared to birth certificate records.

resultsMisclassification of ethnicity and race in administrative records occurred in 23.1% and 33.6% children, respectively; the majority due to missing ethnicity (48.3%) and race (40.9%) information. Misclassification was most common in children of minority groups. PPV for White, Black, Asian/Pacific Islander, American Indian/Alaskan Native, multiple and other was 89.3%, 86.6%, 73.8%, 18.2%, 51.8% and 1.2%, respectively. PPV for Hispanic ethnicity was 95.6%. Racial and ethnic information improved with increasing number of medical visits. Subgroup analyses comparing racial classification between non-Hispanics and Hispanics showed White, Black and Asian race was more accurate among non-Hispanics than Hispanics.

conclusionsIn children, race and ethnicity information from administrative records has significant limitations in accurately identifying small minority groups. These results suggest that the quality of racial information obtained from administrative records may benefit from additional supplementation by birth certificate data.

Indexed as

Birth CertificatesCaliforniaChildChild, PreschoolConfidence IntervalsDelivery of Health CareEthnicityFemaleHealthcare DisparitiesHealth PlanningHumansInfantInfant, NewbornMaleMedical Records Systems, ComputerizedOdds Ratio

Identifiers

PMID21092309
PMCPMC3001430
OpenAlexW1996503617

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.