Disparities In Outcomes Among COVID-19 Patients In A Large Health Care System In California

Health Aff (Millwood). 2020 Jul;39(7):1253-1262. doi: 10.1377/hlthaff.2020.00598. Epub 2020 May 21.


As the novel coronavirus disease (COVID-19) pandemic spreads throughout the United States, evidence is mounting that racial and ethnic minorities and socioeconomically disadvantaged groups are bearing a disproportionate burden of illness and death. We conducted a retrospective cohort analysis of COVID-19 patients at Sutter Health, a large integrated health system in northern California, to measure potential disparities. We used Sutter's integrated electronic health record to identify adults with suspected and confirmed COVID-19, and we used multivariable logistic regression to assess risk of hospitalization, adjusting for known risk factors, such as race/ethnicity, sex, age, health, and socioeconomic variables. We analyzed 1,052 confirmed cases of COVID-19 from the period January 1-April 8, 2020. Among our findings, we observed that compared with non-Hispanic white patients, non-Hispanic African American patients had 2.7 times the odds of hospitalization, after adjustment for age, sex, comorbidities, and income. We explore possible explanations for this, including societal factors that either result in barriers to timely access to care or create circumstances in which patients view delaying care as the most sensible option. Our study provides real-world evidence of racial and ethnic disparities in the presentation of COVID-19.

Keywords: COVID-19; Coronavirus; Ethnic disparities; Health policy; Pandemics; Racial disparities; Socioeconomic status; Systems of care; health disparities.

MeSH terms

  • Adult
  • Age Factors
  • Aged
  • COVID-19
  • California / epidemiology
  • Cohort Studies
  • Coronavirus Infections / epidemiology*
  • Coronavirus Infections / prevention & control
  • Databases, Factual
  • Ethnicity / statistics & numerical data
  • Female
  • Healthcare Disparities / economics*
  • Healthcare Disparities / ethnology*
  • Humans
  • Insurance Coverage / statistics & numerical data*
  • Male
  • Middle Aged
  • Minority Groups / statistics & numerical data
  • Pandemics / prevention & control
  • Pandemics / statistics & numerical data*
  • Pneumonia, Viral / epidemiology*
  • Pneumonia, Viral / prevention & control
  • Poverty / statistics & numerical data*
  • Prevalence
  • Retrospective Studies
  • Risk Assessment
  • Sex Factors
  • Socioeconomic Factors
  • Survival Analysis