Racial/Ethnic Disparities in COVID Treatment/Hospitalization: Social Determinants & Special Populations

Background: The COVID-19 pandemic has exposed long-standing inequities in health, both in access to healthcare and allocation of treatments1,2. These Social Determinants of Health (SDoH)3,4 have reignited questions on whether ones’ ZIP code of residence yields greater impact than their genetic code as a predictor of their health5.
Objective: Our main question looked at an overall cohort of COVID+ individuals, determining whether there is health equity in the decision to hospitalize a patient who presents to the emergency department (ED) and, once hospitalized, equity in assigning treatment across race/ethnicity, controlling for county-level social determinants of health (SDoH) as ecological predictors6, age, sex, and comorbidities.
Methods: We conducted exploratory and descriptive analyses with other special populations, such as patients with dementia and patients who are pregnant, with particular focus on those experiencing housing instability. This study leverages prior research establishing racial/ethnic disparities in health access/treatment using individual-level factors (age, sex, race/ethnicity, and medical comorbidities). We utilized the National Covid Cohort Collaborative (N3C)7, one of the largest national repositories of harmonized clinical data, to study patterns in big health data.
Results: Our overall cohort was split into an ED group (808,956 individuals) and hospitalized group (253,805 individuals). From this initial cohort, we derived a cohort where patient-level SDoH is known (ED: 627,854 individuals, Hospitalized: 195,544 individuals) and a cohort where Housing Instability (HI) were reported (ED: 10,235 individuals, Hospitalized: 3,634 individuals). Across all three cohorts, significant factors in likelihood of hospitalization consistently included chronic lung disease (OR No SDoH = 2.18, p

The analyses described in this poster were conducted with data or tools accessed through the NCATS N3C Data Enclave https://covid.cd2h.org and N3C Attribution & Publication Policy v 1.2-2020-08-25b supported by NCATS U24 TR002306 and iTHRIV NCATS Award: UL1TR003015. This research was possible because of the patients whose information is included within the data and the organizations (https://ncats.nih.gov/n3c/resources/data-contribution/data-transfer-agreement-signatories) and scientists who have contributed to the on-going development of this community resource [https://doi.org/10.1093/jamia/ocaa196].

Students working on this project were part of the University of Virginia Data Justice Academy, supported in part by the Deloitte AI Institute for Government.

Contents of this poster do not necessarily reflect the views of the institution and/or the National Institutes of Health.