Evidence map›Paper›PMID 33820665›Full record

ArticleAmerican journal of preventive medicine2021

Racial Disparities in Potentially Avoidable Hospitalizations During the COVID-19 Pandemic.

Richard K Leuchter, Chad Wes A Villaflores, Keith C Norris, Andrea Sorensen, Sitaram Vangala, Catherine A Sarkisian

Open access · bronzeAbstract read
In one paragraph

Article in American journal of preventive medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed, 1 pooled it
1.3field-weighted citation impact, top 17% of its field
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

15 citing papers in PubMed, 1 synthesis or guideline pooled it, 20 citations in OpenAlex.

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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

6 authors at 2 institutions in 1 country.

Richard K LeuchterDepartment of Medicine, David Geffen School of Medicine, UCLA, Los Angeles, California. Electronic address: rleuchter@mednet.ucla.edu.
Chad Wes A VillafloresDivision of Geriatric Medicine, Department of Medicine, David Geffen School of Medicine, UCLA, Los Angeles, California.
Keith C NorrisDivision of General Internal Medicine & Health Services Research, David Geffen School of Medicine, UCLA, Los Angeles, California.
Andrea SorensenDivision of Geriatric Medicine, Department of Medicine, David Geffen School of Medicine, UCLA, Los Angeles, California.
Sitaram VangalaDepartment of Medicine Statistics Core, David Geffen School of Medicine, UCLA, Los Angeles, California.
Catherine A SarkisianDivision of Geriatric Medicine, Department of Medicine, David Geffen School of Medicine, UCLA, Los Angeles, California; Greater Los Angeles VA Healthcare System Geriatrics Research Education and Clinical Center (GRECC), Los Angeles, California.
University of California, Los Angeles · USGeriatric Research Education and Clinical Center · US

Funding

UCLA Clinical Translational Science InstituteUL1TR001881 · NCATS · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI ARLEEN F. BROWN, ARASH NAEIM · 2016 to 2026
$118.1M
The Center for Health Improvement of Minority ElderlyP30AG021684 · NIA · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI CATHERINE A SARKISIAN · 2002 to 2026
$19.7M
Midcareer Award in Patient-Oriented Community-Academic Partnered Aging ResearchK24AG047899 · NIA · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI SARKISIAN, CATHERINE A · 2014 to 2025
$2.0M
The University of California - Los Angeles (UCLA) Resident Scientist Training Program (RSTP)R38HL143614 · NHLBI · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI AJIJOLA, OLUJIMI A, DEMER, LINDA L. · 2020 to 2023
$1.1M
NCATS NIH HHS UL1 TR001881NHLBI NIH HHS R38 HL143614NIA NIH HHS K24 AG047899NIA NIH HHS P30 AG021684
6 · The paper itself

Abstract

introductionPotentially avoidable hospitalizations are disproportionately experienced by racial and ethnic minorities and expose these groups to unnecessary iatrogenic harm (including the risk of nosocomial COVID-19) and undue financial burden. In working toward an overarching goal of eliminating racial and ethnic health disparities, it is important to understand whether and to what extent potentially avoidable hospitalizations have changed by race and ethnicity during the COVID-19 pandemic.

methodsThis single-center pre-post study included patients admitted to any UCLA Health hospital for an ambulatory care-sensitive condition between March-August 2019 (prepandemic period) and March-August 2020 (postpandemic period). Investigators measured the change in the number of potentially avoidable hospitalizations (defined per the Agency for Healthcare Research and Quality guidelines) stratified by race and ethnicity and calculated the 95% CIs for these hospitalizations using a cluster bootstrap procedure.

resultsBetween March 1, 2020 and August 31, 2020, 347 of 4,838 hospitalizations (7.2%) were potentially avoidable, compared with 557 of 6,248 (8.9%) during the same 6-month period in 2019. Potentially avoidable hospitalizations decreased by 50.3% (95% CI=41.2, 60.9) among non-Hispanic Whites but only by 8.0% (95% CI= -16.2, 39.9) among African Americans (50.3% vs 8.0%, p=0.015).

conclusionsRacial disparities in potentially avoidable hospitalizations increased during the COVID-19 pandemic at a large urban health system. Given that the prepandemic rates of potentially avoidable hospitalizations were already higher among racial and ethnic minorities, especially among African Americans, this finding should cause alarm and lead to further exploration of the complex factors contributing to these disparities.

Indexed as

COVID-19PandemicsEthnicityHealthcare DisparitiesHealth Status DisparitiesHispanic or LatinoHospitalizationHumansSARS-CoV-2United States

Identifiers

PMID33820665
PMCPMC8319069
OpenAlexW3137149626

What OpenQuestion holds

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Registered trials

None linked

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.