Evidence map›Paper›PMID 34713355›Full record

ArticleEmergency radiology2022

Revisiting racial disparities in ED CT utilization during the Affordable Care Act era: 2009-2018 data from the NHAMCS.

Ragheed Al-Dulaimi, Phuong-Anh Duong, Brian Y Chan, Matthew J Fuller, Andrew B Ross, Dell P Dunn

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Article in Emergency radiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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2citing papers in PubMed
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1 · What the graph read from it

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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

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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

2 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Ragheed Al-DulaimiDepartment of Radiology & Imaging Sciences, University of Utah School of Medicine, 30 North 1900 East #1A071, Salt Lake City, UT, 84132-2140, USA.
Phuong-Anh DuongDepartment of Radiology & Imaging Sciences, University of Utah School of Medicine, 30 North 1900 East #1A071, Salt Lake City, UT, 84132-2140, USA.
Brian Y ChanDepartment of Radiology & Imaging Sciences, University of Utah School of Medicine, 30 North 1900 East #1A071, Salt Lake City, UT, 84132-2140, USA.
Matthew J FullerDepartment of Emergency Medicine, University of Utah School of Medicine, Salt Lake City, UT, USA.
Andrew B RossDepartment of Radiology, School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA.
Dell P DunnDepartment of Radiology & Imaging Sciences, University of Utah School of Medicine, 30 North 1900 East #1A071, Salt Lake City, UT, 84132-2140, USA. Dell.Dunn@utah.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo examine the trends in CT utilization in the emergency department (ED) for different racial and ethnic groups, factors that may affect utilization, and the effects of increased insurance coverage since passage of the Affordable Care Act in 2010. MATERIALS AND

methodsData from the National Hospital Ambulatory Medical Care Survey (NHAMCS) for the years 2009-2018 were used for the analysis. The NHAMCS is a cross-sectional survey which has random and systematical samples of more than 200,000 visits to over 250 hospital EDs in the USA. Patient demographic characteristics, source of payment/insurance, clinical presentation, and disposition from the ED were recorded. Descriptive statistics and multivariate logistic regression were performed.

resultsBetween 2009 and 2018, the rate of uninsured patients in the ED decreased from 18.1% to as low as 9.9%, but this was not associated with a decrease in the disparity in CT utilization between non-Hispanic Black and non-Hispanic White patients. CT use rate increased 38% over the study period. Factors strongly associated with CT utilization include age, source of payment, triage category, disposition from the ED, and residence. After controlling for these factors, non-Hispanic White patients were 21% more likely to undergo CT than non-Hispanic Black patients, though no disparity was seen for Hispanic or Asian/other groups.

conclusionDespite increased insurance coverage over the sample period, racial disparities between non-Hispanic Black and non-Hispanic White patients persist in CT utilization, though no disparity was seen for Hispanic or Asian/other patients. The source of this disparity remains unclear and is likely multifactorial.

Indexed as

Healthcare DisparitiesPatient Protection and Affordable Care ActCross-Sectional StudiesEmergency Service, HospitalHospitalsHumansTomography, X-Ray ComputedUnited StatesAffordable Care ActCT utilizationEmergency radiologyEthnicityHealth disparitiesHealth equity

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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.