Evidence map›Paper›PMID 36747155›Full record

Observational studyBMC public health2023

Disparities in COVID-19 testing and outcomes among Asian American and Pacific Islanders: an observational study in a large health care system.

Jiang Li, Davis Chhoa, Latha Palaniappan, Kevin J Hays, Alice Pressman, Nancy E Wang

Open access · goldAbstract readObservational Study
In one paragraph

Observational study in BMC public health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
2.1field-weighted citation impact, top 13% 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

8 citing papers in PubMed, 11 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.

Jiang LiPalo Alto Medical Foundation Research Institute, Center for Health Systems Research, Sutter Health, 795 El Camino Real, Palo Alto, CA, 94301, USA. lij14@sutterhealth.org.
Davis ChhoaStanford University School of Medicine, Stanford, USA.
Latha PalaniappanStanford University School of Medicine, Primary Care and Population Health, 900 Blake Wilbur Dr Rm W200, 2Nd Fl MC 5358, Stanford, CA, 94304, USA.
Kevin J HaysPalo Alto Medical Foundation Research Institute, Center for Health Systems Research, Sutter Health, 795 El Camino Real, Palo Alto, CA, 94301, USA.
Alice PressmanPalo Alto Medical Foundation Research Institute, Center for Health Systems Research, Sutter Health, 795 El Camino Real, Palo Alto, CA, 94301, USA.
Nancy E WangDepartments of Emergency Medicine and Pediatrics, Stanford University School of Medicine, 900 Welch Road - #350/MC: 5768, Palo Alto, CA, 94304, USA.
Stanford University · USSutter Health · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe COVID-19 pandemic has disproportionately impacted racial and ethnic minorities in the United States, including Asian Americans, Native Hawaiians and Pacific Islanders (Asian Americans and NH/PIs). However, few studies have highlighted nor disaggregated these disparities by Asian Americans and NH/PIs ethnic subgroups.

methodsThis retrospective, cross-sectional observational study aimed to assess variation of Asian Americans and NH/PIs COVID-19 testing and outcomes compared to non-Hispanic Whites (NHW). The study utilized data from the electronic health records (EHR) and the COVID-19 Universal Registry for Vital Evaluations (CURVE) from all patients tested for SARS-CoV-2 (n = 556,690) at a large, health system in Northern and Central California between February 20, 2020 and March 31, 2021. Chi-square tests were used for testing differences in the severity of COVID-19 (hospitalization, ICU admission, death) and patient demographic and clinical characteristics across the Asian Americans and NH/PIs subgroups and NHW. Unadjusted and adjusted Odds Ratios (ORs) were estimated for measuring effect of race ethnicity on severity of COVID-19 using multivariable logistic regression.

resultsOf the entire tested population, 70,564/556,690 (12.7%) tested positive for SARS-CoV-2. SARS-CoV-2 positivity of Asian subgroups varied from 4% in the Chinese and Korean populations, to 11.2%, 13.5%, and 12.5% for Asian Indian, Filipino, and "other Asian" populations respectively. Pacific Islanders had the greatest subgroup test positivity at 20.1%. Among Asian Americans and NH/PIs patients with COVID-19 disease, Vietnamese (OR = 2.06, 95% CI = 1.30-3.25), "Other Asian" (OR = 2.13, 95% CI = 1.79-2.54), Filipino (OR = 1.78, 95% CI = 1.34-2.23), Japanese (OR = 1.78, 95% CI = 1.10-2.88), and Chinese (OR = 1.73, 95% CI = 1.34-2.23) subgroups had almost double the odds of hospitalization compared to NHW. Pacific Islander (OR = 1.58, 95% CI = 1.19-2.10) and mixed race subgroups (OR = 1.55, 95% CI = 1.10-2.20) had more than one and a half times odds of hospitalization compared to NHW. Adjusted odds of ICU admission or death among hospitalized patients by different Asian subgroups varied but were not statistically significant.

conclusionsVariation of COVID-19 testing and hospitalization by Asian subgroups was striking in our study. A focus on the Asian Americans and NH/PIs population with disaggregation of subgroups is crucial to understand nuances of health access, utilization, and outcomes among subgroups to create health equity for these underrepresented populations.

Indexed as

Asian American Native Hawaiian and Pacific IslanderCOVID-19COVID-19 TestingHealthcare DisparitiesCross-Sectional StudiesDelivery of Health CareHumansPandemicsRetrospective StudiesSARS-CoV-2United StatesAsian AmericansCOVID-19COVID-19 TestingEthnic and racial minoritiesHealth services accessibilityHospitalizationImmigrantsMorbidity

Identifiers

PMID36747155
PMCPMC9900558
OpenAlexW4319298515

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.