Evidence map›Paper›PMID 35199327›Full record

ArticleJournal of racial and ethnic health disparities2023

Is the Gap Closing? Comparison of Sociodemographic Disparities in COVID-19 Hospitalizations and Outcomes Between Two Temporal Waves of Admissions.

Priscilla G Wang, Nicholas M Brisbon, Harrison Hubbell, John Pyhtila, Gregg S Meyer, Po-Yu Lai, Dellara F Terry

Abstract read
In one paragraph

Article in Journal of racial and ethnic health disparities, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Median Income and Clinical Outcomes of Hospitalized Persons With COVID-19 at an Urban Veterans Affairs Medical Center.Federal practitioner : for the health care professionals of the VA, DoD, and PHS · 2026
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  2. Observational
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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.

Priscilla G WangPopulation Health Management, Mass General Brigham, Wang Ambulatory Care Center 634, 15 Parkman Street, Boston, MA, 02114, USA. pgwang@partners.org.ORCID 0000-0002-7314-7092
Nicholas M BrisbonData and Analytics Organization, Mass General Brigham, Boston, MA, USA.
Harrison HubbellData and Analytics Organization, Mass General Brigham, Boston, MA, USA.
John PyhtilaData and Analytics Organization, Mass General Brigham, Boston, MA, USA.
Gregg S MeyerCommunity Division and Value-Based Care, Mass General Brigham, Boston, MA, USA.
Po-Yu LaiData and Analytics Organization, Mass General Brigham, Boston, MA, USA.
Dellara F TerryData and Analytics Organization, Mass General Brigham, Boston, MA, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveThe COVID-19 pandemic has disproportionately impacted minority communities, yet little data exists regarding whether disparities have improved at a health system level. This study examined whether sociodemographic disparities in hospitalization and clinical outcomes changed between two temporal waves of hospitalized COVID-19 patients.

methodsThis is a retrospective cohort study of primary care patients at Mass General Brigham (a large northeastern health system serving 1.27 million primary care patients) hospitalized in-system with COVID-19 between March 1, 2020, and March 1, 2021, categorized into two 6-month "wave" periods. We used chi-square tests to compare demographics between waves, and regression analysis to characterize the association of race/ethnicity and language with in-hospital severe outcomes (death, hospice discharge, intensive unit care need).

resultsHispanic/Latino, Black, and non-English-speaking patients constituted 30.3%, 12.5%, and 29.7% of COVID-19 admissions in wave 1 (N = 5844) and 22.2%, 9.0%, and 22.7% in wave 2 (N = 4007), compared to 2019 general admission proportions of 8.8%, 6.3%, and 7.7%, respectively. Admissions from highly socially vulnerable census tracts decreased between waves. Non-English speakers had significantly higher odds of severe illness during wave 1 (OR 1.35; 95% CI: 1.10, 1.66) compared to English speakers; this association was non-significant during wave 2 (OR 1.01; 95% CI: 0.76, 1.36).

conclusionsComparing two COVID-19 temporal waves, significant sociodemographic disparities in COVID-19 admissions improved between waves but continued to persist over a year, demonstrating the need for ongoing interventions to truly close equity gaps. Non-English-speaking language status independently predicted worse hospitalization outcomes in wave 1, underscoring the importance of targeted and effective in-hospital supports for non-English speakers.

Indexed as

COVID-19PandemicsHospitalizationHospitalsHumansRetrospective StudiesCOVID-19DisparitiesLanguageRaceSociodemographic

Identifiers

PMID35199327
PMCPMC8865177

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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.