Clinical, behavioural and social factors associated with racial disparities in COVID-19 patients from an integrated healthcare system in Georgia: a retrospective cohort study

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Abstract

To identify sociodemographic, clinical and behavioural drivers of racial disparities and their association with clinical outcomes among Kaiser Permanente Georgia (KPGA) members with COVID-19.

Design

Retrospective cohort of patients with COVID-19 seen from 3 March to 29 October 2020. We described the distribution of underlying comorbidities, quality of care metrics, demographic and social determinants of health (SDOH) indicators across race groups. We also described clinical outcomes in hospitalised patients including length of stay, intensive care unit (ICU) admission, readmission and mortality. We performed multivariable analyses for hospitalisation risk among all patients with COVID-19 and stratifyied by race and sex.

Setting

KPGA, an integrated healthcare system.

Participants

5712 patients who all had laboratory-confirmed COVID-19. Of them, 57.8% were female, 58.4% black, 29.5% white, 8.5% Hispanic and 3.6% Asian.

Results

Black patients had the highest proportions of living in neighborhoods under the federal poverty line (12.4%) and in more deprived locations (neighbourhood deprivation index=0.4). Overall, 14.4% (n=827) of this cohort was hospitalised. Asian patients had the highest rates of ICU admission (53.1%) and mechanical ventilation (21.9%). Among all patients, Hispanics (adjusted 1.60, 95% CI (1.08, 2.37)), blacks (1.43 (1.13, 1.83)), age in years (1.03 (1.02, 1.04)) and living in a zip code with high unemployment (1.08 (1.03, 1.13)) were associated with higher odds of hospitalisation. COVID-19 patients with chronic obstructive pulmonary disease (2.59 (1.67, 4.02)), chronic heart failure (1.79 (1.31, 2.45)), immunocompromised (1.77 (1.16, 2.70)), with glycated haemoglobin >8% (1.68 (1.19, 2.38)), depression (1.60 (1.24, 2.06)), hypertension (1.5 (1.21, 1.87)) and physical inactivity (1.25 (1.03, 1.51)) had higher odds of hospitalisation.

Conclusions

Black and Hispanic KPGA patients were at higher odds of hospitalisation, but not mortality, compared with other race groups. Beyond previously reported sociodemographics and comorbidities, factors such as quality of care, lifestyle behaviours and SDOH indicators should be considered when designing and implementing interventions to reduce COVID-19 racial disparities.

Article activity feed

  1. SciScore for 10.1101/2020.07.08.20148973: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    Institutional Review Board StatementIRB: The KPGA institutional review board approved this study with a waiver of informed consent.
    Consent: The KPGA institutional review board approved this study with a waiver of informed consent.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Experimental Models: Organisms/Strains
    SentencesResources
    Race/ethnicity was categorized as non-Hispanic Black/AA (confirmed n=306; 68,3%), non-Hispanic White (n=81; 18%), and Other (n=61; 13,7%), which included Hispanic or Latino (n=16), Asian (n=15), Native American (n=1) and unknown/declined to report (n=29).
    non-Hispanic White
    suggested: None
    Software and Algorithms
    SentencesResources
    All data analysis was conducted using SAS 9.4 software.
    SAS
    suggested: (SASqPCR, RRID:SCR_003056)

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).


    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    This reinforces the clinical value of promoting fitness and an active lifestyle, preferably outdoors, to reduce the risk of infection and disease severity of a novel infectious agent such as SARS-COV-2.(36) This study has some limitations. Limited testing availability in the early stages of the pandemic — globally and in Georgia — led to prioritizing those with the most symptomatic and severe disease requiring admission, as well as testing healthcare workers to prevent further nosocomial infection. For this reason, we included in our analysis not only laboratory-confirmed but also persons under investigation seeking care with COVID-like symptoms. However, we acknowledge that not all PUIs would necessarily have SARS-COV-2. The target population in this analysis included only KPGA members that by definition have insurance and ready access to health care services. However, our analysis showed a diverse socioeconomic background of KPGA members. Merging racial/ethnic groups with low sample sizes into a combined “Other” race category was necessary for statistical power reasons but limits the interpretation of findings for this group. Finally, despite having some SDOH indicators in our member’s EHR, we also included neighborhood level data to extrapolate additional SDOH metrics. Ongoing investigation of drivers in COVID-19 disparities will benefit from more individual level SDOH data. Despite these limitations, by integrating underlying chronic disease management history, outpatient...

    Results from TrialIdentifier: No clinical trial numbers were referenced.


    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.


    Results from JetFighter: We did not find any issues relating to colormaps.


    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.