Evidence map›Paper›PMID 42260864›Full record

ArticleMedicine2026

Racial and ethnic disparities in access to non-COVID-19 healthcare during the pandemic in the United States.

Abdullah A Alghamdi, Krzysztof Goniewicz, Juan Gómez-Salgado, Nawaf A Albaqami, Mohammad A Abahussain, Afnan M Alwasedi, Hassan Farhat, Ahmed M Al-Wathinani

Abstract read
In one paragraph

Article in Medicine, 2026. 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

8 authors.

Abdullah A AlghamdiDepartment of Emergency Medical Services, Price Sultan bin Abdulaziz College for Emergency Medical Services, King Saud University, Riyadh, Saudi Arabia.
Krzysztof GoniewiczDepartment of Security Studies, Polish Air Force University, Deblin, Poland.ORCID 0000-0003-4368-6850
Juan Gómez-SalgadoDepartment of Sociology, Social Work and Public Health, Faculty of Labour Sciences, University of Huelva, Huelva, Spain.
Nawaf A AlbaqamiDepartment of Emergency Medical Services, Price Sultan bin Abdulaziz College for Emergency Medical Services, King Saud University, Riyadh, Saudi Arabia.
Mohammad A AbahussainDepartment of Emergency Medical Services, Price Sultan bin Abdulaziz College for Emergency Medical Services, King Saud University, Riyadh, Saudi Arabia.
Afnan M AlwasediRadiology Department, Magnetic Resonance Imaging Section, King Faisal Specialized Hospital and Research Center, Riyadh, Saudi Arabia.
Hassan FarhatMajor Incident Preparedness and Resilience & Ambulance Service Group, Hamad Medical Corporation, Doha, Qatar.
Ahmed M Al-WathinaniDepartment of Emergency Medical Services, Price Sultan bin Abdulaziz College for Emergency Medical Services, King Saud University, Riyadh, Saudi Arabia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Access to healthcare-defined as the ability to obtain timely and necessary medical services - is critical during public health emergencies. The Coronavirus Disease 2019 (COVID-19) pandemic (2020-2021) substantially disrupted routine healthcare delivery in the United States, particularly affecting racial and ethnic minority groups who already face barriers to care. While previous studies have examined disparities in COVID-related outcomes, fewer have assessed racial differences in access to care for non-COVID-19 conditions over an extended pandemic period. This study investigated whether race and ethnicity were associated with limited or delayed access to non-COVID-19 healthcare services during the COVID-19 pandemic in the U.S. We used cross-sectional, nationally representative data from the National Health Interview Survey (NHIS) from July 2020 to December 2021. The analytic sample included 40,955 U.S. adults aged 25 years and older. Survey-weighted logistic regression models accounting for the NHIS complex sampling design (strata and primary sampling units) were used to estimate associations between race/ethnicity and 2 binary outcomes: inability to obtain needed non-COVID-19 medical care and delays in receiving such care, adjusting for demographic, socioeconomic, and health-related covariates. Complete-case analysis was used due to minimal missingness. Sensitivity analyses using alternative weight rescaling produced substantively similar results. All results are based on the weighted sample; however, unweighted results are provided in the appendix. Among respondents, 13.8% reported being unable to access needed care, and 21.5% reported delaying care during the pandemic. After adjustment, American Indian/Alaskan Native and multiracial individuals were significantly more likely to experience barriers to care, with lower odds of receiving needed care (odds ratio [OR] = 0.64; 95% confidence interval [CI]: 0.534-0.782) and higher odds of delay (OR = 1.5; 95% CI: 1.247-1.813). Non-Hispanic Asian respondents were least likely to delay care (OR = 0.67; 95% CI: 0.585-0.774). Racial and ethnic disparities in access to non-COVID-19 healthcare were observed throughout the pandemic period. The observed disparities are consistent with prior literature on inequities in healthcare access during public health emergencies and may help inform future research and policy discussions regarding healthcare access during future emergencies.

Indexed as

COVID-19EthnicityHealthcare DisparitiesHealth Services AccessibilityRacial GroupsAdultAgedCross-Sectional StudiesFemaleHumansMaleMiddle AgedPandemicsSocioeconomic Disparities in HealthUnited StatesCOVID-19disastersethnic groupshealthcare disparitieshealth services accessibilitylogistic modelsminority health

Identifiers

PMID42260864
PMCPMC13246066

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Registered trials

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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.