Evidence map›Paper›PMID 39247491›Full record

ArticleHealth services insights2024

Identifying Patient Subpopulations with Significant Race-Sex Differences in Emergency Department Disposition Decisions.

Peter Lin, Nilay T Argon, Qian Cheng, Christopher S Evans, Benjamin Linthicum, Yufeng Liu, Abhishek Mehrotra, Laura Murphy, Mehul D Patel, Serhan Ziya

Abstract read
In one paragraph

Article in Health services insights, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

10 authors.

Peter LinDepartment of Statistics and Operations Research, University of North Carolina, Chapel Hill, NC, USA.ORCID https://orcid.org/0000-0002-2330-8396
Nilay T ArgonDepartment of Statistics and Operations Research, University of North Carolina, Chapel Hill, NC, USA.ORCID https://orcid.org/0000-0002-6814-0849
Qian ChengDepartment of Statistics and Operations Research, University of North Carolina, Chapel Hill, NC, USA.
Christopher S EvansInformation Services, ECU Health, Greenville, NC, USA.
Benjamin LinthicumDepartment of Emergency Medicine, University of North Carolina, Chapel Hill, NC, USA.
Yufeng LiuDepartment of Statistics and Operations Research, University of North Carolina, Chapel Hill, NC, USA.
Abhishek MehrotraDepartment of Emergency Medicine, University of North Carolina, Chapel Hill, NC, USA.
Laura MurphyDepartment of Emergency Medicine, University of North Carolina, Chapel Hill, NC, USA.
Mehul D PatelDepartment of Emergency Medicine, University of North Carolina, Chapel Hill, NC, USA.
Serhan ZiyaDepartment of Statistics and Operations Research, University of North Carolina, Chapel Hill, NC, USA.

Funding

Understanding and Addressing Disparities in Triage and Disposition Decisions in the Emergency DepartmentR03HS029078 · AHRQ · UNIV OF NORTH CAROLINA CHAPEL HILL · PI PATEL, MEHUL D. · 2022 to 2022
$100k
AHRQ HHS R03 HS029078
6 · The paper itself

Abstract

Background/objectives: The race-sex differences in emergency department (ED) disposition decisions have been reported widely. Our objective is to identify demographic and clinical subgroups for which this difference is most pronounced, which will facilitate future targeted research on potential disparities and interventions. Methods: We performed a retrospective analysis of 93 987 White and African-American adults assigned an Emergency Severity Index of 3 at 3 large EDs from January 2019 to February 2020. Using random forests, we identified the Elixhauser comorbidity score, age, and insurance status as important variables to divide data into subpopulations. Logistic regression models were then fitted to test race-sex differences within each subpopulation while controlling for other patient characteristics and ED conditions. Results: In each subpopulation, African-American women were less likely to be admitted than White men with odds ratios as low as 0.304 (95% confidence interval (CI): [0.229, 0.404]). African-American men had smaller admission odds compared to White men in subpopulations of 41+ years of age or with very low/high Elixhauser scores, odds ratios being as low as 0.652 (CI: [0.590, 0.747]). White women were less likely to be admitted than White men in subpopulations of 18 to 40 or 41 to 64 years of age, with low Elixhauser scores, or with Self-Pay or Medicaid insurance status with odds ratios as low as 0.574 (CI: [0.421, 0.784]). Conclusions: While differences in likelihood of admission were lessened by younger age for African-American men, and by older age, higher Elixhauser score, and Medicare or Commercial insurance for White women, they persisted in all subgroups for African-American women. In general, patients of age 64 years or younger, with low comorbidity scores, or with Medicaid or no insurance appeared most prone to potential disparities in admissions.

Indexed as

disposition decisionemergency departmentlogistic regressionRacerandom forestssex

Identifiers

PMID39247491
PMCPMC11378179

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