Evidence map›Paper›PMID 35154951›Full record

ArticleCureus2022

Improving Patient Race and Ethnicity Data Capture to Address Health Disparities: A Case Study From a Large Urban Health System.

Ruben D Vega Perez, Lyndia Hayden, Jefri Mesa, Nina Bickell, Pamela Abner, Lynne D Richardson, Ka Ming Ngai

Abstract read
In one paragraph

Article in Cureus, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 citing papers in PubMed.

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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

7 authors.

Ruben D Vega PerezEmergency Medicine, Icahn School of Medicine at Mount Sinai, New York City, USA.
Lyndia HaydenOffice for Diversity and Inclusion, Icahn School of Medicine at Mount Sinai, New York City, USA.
Jefri MesaOffice for Diversity and Inclusion, Icahn School of Medicine at Mount Sinai, New York City, USA.
Nina BickellMedicine, Icahn School of Medicine at Mount Sinai, New York City, USA.
Pamela AbnerOffice for Diversity and Inclusion, Icahn School of Medicine at Mount Sinai, New York City, USA.
Lynne D RichardsonEmergency Medicine, Icahn School of Medicine at Mount Sinai, New York City, USA.
Ka Ming NgaiEmergency Medicine, Icahn School of Medicine at Mount Sinai, New York City, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

While research and efforts to promote health equity abound, the persistence of disparities by race and ethnicity underscores the limitations of fragmented interventions and the need for systematic, multipronged approaches to health equity. The foundational step towards reducing health disparities is the establishment of the basic information needed to identify and measure those differences, i.e., the accurate capture of race and ethnicity information of all patients. To that end, we present a case study outlining a multifaceted approach for improving the capture of race and ethnicity data in an outpatient setting culminating in a 76% improvement in the completeness of this information. The effectiveness of this plan and its scalability within a large urban health system may benefit similar institutions seeking to improve the collection of race and ethnicity information and the reliability of their data. To this aim, we present an approach relying on the assessment and evaluation of system needs, modification of data infrastructure to align with goals, training, and education of relevant stakeholders, implementation and responsive action to results, and acknowledging limitations and lessons learned. We emphasize that cross-departmental collaboration, stakeholder engagement, institutional support, and culture of anti-racism were essential to the success of this initiative.

Indexed as

capturing accurate race and ethnicity datadata qualityfeasibility of implementing system-wide interventionshealth equityproject demonstrates

Identifiers

PMID35154951
PMCPMC8815799

What OpenQuestion holds

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LicenceCC BY
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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.