Evidence map›Paper›PMID 41698401›Full record

ArticlePediatrics2026

Low-Value Emergency Care and Racial and Ethnic Differences Across US Children's Hospitals.

Robert H Rosen, John J Porter, Michael C Monuteaux, Samantha A House, Joyce Li, Mark I Neuman, Anne M Stack, Sara L Toomey, Lois K Lee

Abstract read
In one paragraph

Article in Pediatrics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

9 authors.

Robert H RosenRonald O. Perelman Department of Emergency Medicine, New York University Grossman School of Medicine, New York University Langone Health, New York, New York.
John J PorterDivision of Emergency Medicine, Boston Children's Hospital, Boston, Massachusetts.
Michael C MonuteauxDivision of Emergency Medicine, Boston Children's Hospital, Boston, Massachusetts.
Samantha A HouseGeisel School of Medicine at Dartmouth, Lebanon, New Hampshire.
Joyce LiDivision of Emergency Medicine, Boston Children's Hospital, Boston, Massachusetts.
Mark I NeumanDivision of Emergency Medicine, Boston Children's Hospital, Boston, Massachusetts.
Anne M StackDivision of Emergency Medicine, Boston Children's Hospital, Boston, Massachusetts.
Sara L ToomeyDepartment of Pediatrics, Harvard Medical School, Boston, Massachusetts.
Lois K LeeDivision of Emergency Medicine, Boston Children's Hospital, Boston, Massachusetts.

Funding

Understanding the Influence of Community-level Deprivation and Rural Residence in Cancer CareP20GM148278 · NIGMS · DARTMOUTH-HITCHCOCK CLINIC · PI LAURA Marie PAULIN, Sandra L Wong · 2023 to 2026
$11.6M
NIGMS NIH HHS P20 GM148278
6 · The paper itself

Abstract

objectivesTo examine (1) differences in low-value care (LVC) for common emergency conditions by race and ethnicity in US children's hospitals and (2) the association between hospital characteristics, including LVC rate, and the magnitude of within-hospital LVC differences by race and ethnicity. We hypothesized smaller LVC differences in hospitals with lower overall LVC rates.

methodsWe performed a cross-sectional study of children younger than 18 years discharged from the emergency department with asthma, bronchiolitis, headache, or minor head injury in the Pediatric Health Information System (PHIS) from January 2021 to June 2023. Exposures were patient race and ethnicity (non-Hispanic Black, "Black"; non-Hispanic white, "white"; Hispanic) and deidentified PHIS hospital. Outcomes were LVC by race and ethnicity within and across hospitals. We used multivariable logistic regression, reporting adjusted odds ratios (aORs) and 95% CI, to estimate hospital-level and condition-specific LVC differences and linear regression to examine the association between LVC differences and LVC rates.

resultsAmong 314 138 eligible encounters, overall LVC rates were as follows: asthma 18%, bronchiolitis 32%, headache 24%, and minor head injury 26%. White compared with Black and Hispanic patients had higher odds of LVC across multiple conditions in pooled and within-hospital analyses. The largest pooled differences were for white vs Black: asthma aOR (95% CI) = 1.51 (1.18-1.95) and headache 1.57 (1.43-1.72). Hospital LVC rate was not associated with magnitude of within-hospital LVC difference for any condition.

conclusionsLower hospital LVC rates were not associated with reduced LVC differences. Intentional focus on LVC differences is important when designing LVC reduction efforts.

Indexed as

Emergency Service, HospitalEthnicityHealthcare DisparitiesHospitals, PediatricAdolescentAsthmaBlack or African AmericanBronchiolitisChildChild, PreschoolCraniocerebral TraumaCross-Sectional StudiesFemaleHeadacheHispanic or LatinoHumans

Identifiers

PMID41698401
PMCPMC13222470

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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.