Evidence map›Paper›PMID 41208916›Full record

ArticleDigital health

Evaluation of race, ethnicity, and language mischaracterizations in the electronic medical record for Hispanic/Latinx patients.

Ricardo Crespo Regalado, Emily C Bulik-Sullivan, Andrew G Blank, Lauren D Raff, Arielle Johnston, Morgan Beauchamp, Yang Lee, Christina Cobos, Mayerlin Alpizar, Veronica Cifuentes and 3 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Digital health. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

13 authors.

Ricardo Crespo RegaladoUniversity of North Carolina, Chapel Hill School of Medicine, Chapel Hill, NC, USA.ORCID https://orcid.org/0009-0002-7746-1772
Emily C Bulik-SullivanUniversity of North Carolina, Chapel Hill School of Medicine, Chapel Hill, NC, USA.ORCID https://orcid.org/0000-0002-3279-7240
Andrew G BlankDivision of Hospital Medicine, Department of Medicine, University of North Carolina School of Medicine, Chapel Hill, NC, USA.
Lauren D RaffDepartment of Surgery, Division of Trauma and Acute Care Surgery, University of North Carolina School of Medicine, Chapel Hill, NC, USA.
Arielle JohnstonCollege of Arts and Sciences, University of North Carolina, at Chapel Hill, Chapel Hill, NC, USA.ORCID https://orcid.org/0009-0003-5689-9115
Morgan BeauchampCollege of Arts and Sciences, University of North Carolina, at Chapel Hill, Chapel Hill, NC, USA.
Yang LeeCollege of Arts and Sciences, University of North Carolina, at Chapel Hill, Chapel Hill, NC, USA.
Christina CobosCollege of Arts and Sciences, University of North Carolina, at Chapel Hill, Chapel Hill, NC, USA.
Mayerlin AlpizarCollege of Arts and Sciences, University of North Carolina, at Chapel Hill, Chapel Hill, NC, USA.
Veronica CifuentesCollege of Arts and Sciences, University of North Carolina, at Chapel Hill, Chapel Hill, NC, USA.
Robert AgansUniversity of North Carolina Gillings, School of Global Public Health, Chapel Hill, NC, USA.
Carlton MooreDivision of Hospital Medicine, Department of Medicine, University of North Carolina School of Medicine, Chapel Hill, NC, USA.ORCID https://orcid.org/0000-0001-7732-4829
Evan J RaffDivision of Hospital Medicine, Department of Medicine, University of North Carolina School of Medicine, Chapel Hill, NC, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: Accurate documentation of interpreter requirements and language preference within the electronic medical record (EMR) is essential for ensuring appropriate care and effective communication with patients who have non-English language preference (NELP). Our objective was to examine the accuracy of EMR documentation related to interpreter needs and language preferences for Hispanic patients at a large academic medical center. Methods: This was a cross-sectional study conducted at the University of North Carolina Medical Center from May 2023 to July 2023. A total of 156 Hispanic patients were surveyed based on their clinical records and self-reported language needs. The main measure was the accuracy of EMR documentation compared to patients' self-reported interpreter needs and preferred language. Results: Among 156 Hispanic inpatients, 30.13% had mischaracterized interpreter needs in the EMR, with discrepancies including missing documentation (22%) and direct contradictions (9.92%). Mischaracterizations were significantly associated with male gender (OR = 0.310; 95% CI [0.140, 0.685]; Conclusion: Significant inaccuracies in race, ethnicity, and language data documentation hinder equitable care. Addressing these gaps requires standardized documentation protocols, staff training, and objective language assessment tools to improve interpreter utilization and mitigate disparities for NELP patients.

Indexed as

Electronic medical recordhealth literacylimited English proficiencymedical interpretingpatient rights

Identifiers

PMID41208916
PMCPMC12592655

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.