(A02) Ethnic differences in the indirect impacts of the COVID-19 pandemic on hospitalisations for non-COVID conditions in England: An observational cohort study using OpenSAFELY
Professor and Chair of Health Data Science Queen Mary, University of London, United Kingdom
Background: The COVID-19 pandemic disrupted healthcare and may have impacted ethnic inequalities in healthcare.
Objectives: To describe the impact of pandemic-related disruption on ethnic differences in hospital admissions for non-COVID conditions in England.
Methods: With the approval of NHS England, we conducted a cohort study using English primary care data, with linkage to hospital admission and death registry data, within the OpenSAFELY platform. The study population was adults, with at least 3 months registration at their primary care practice, who were not missing age, sex, region or deprivation information. Two cohorts were identified corresponding to pre-pandemic (01/03/2018-22/03/2020) and pandemic (23/03/2020-30/04/2022) time periods. We assessed eligibility at the start of each period. People were followed until the earliest of death, deregistration with their practice or end of the study period. Ethnicity (exposure) was identified from primary care records, supplemented with information from hospital data and grouped into five categories: White, Asian, Black, Other, Mixed. We identified hospitalisations (outcomes) related to diabetes, cardiovascular disease, respiratory disease, and mental health. For each outcome we 1) describe rate differences (pre-pandemic vs pandemic) and 2) use multivariable Cox regression to quantify ethnic differences in time to first hospitalisation relative to White ethnicity, in each cohort.
Results: Of 15,053,816 adults in the pandemic cohort with known ethnicity: 86.4% were White, 7.4% Asian, 2.6% Black, 1.4% Mixed ethnicity, and 2.2% Other ethnicities. For those of Black ethnicity, there were seven additional admissions for diabetic ketoacidosis per month during the pandemic, and relative ethnic differences narrowed during the pandemic compared to White (Pre-pandemic HR: 0.50, 95% CI 0.41, 0.60, Pandemic HR: 0.75, 95% CI: 0.65, 0.87). There were increased admissions for heart failure during the pandemic for all ethnic groups, with the greatest increases in those of White ethnicity. Relatively, ethnic differences narrowed for heart failure admission in those of Asian (Pre-pandemic HR 1.56, 95% CI 1.49, 1.64, Pandemic HR 1.24, 95% CI 1.19, 1.29) and Black (Pre-pandemic HR 1.41, 95% CI: 1.30, 1.53, Pandemic HR: 1.16, 95% CI 1.09, 1.25) ethnicity compared to White. For other outcomes the pandemic had minimal impact on ethnic differences.
Conclusions: Our study demonstrates there were pre-pandemic ethnic differences in hospitalisations which remained largely unchanged during the pandemic for most conditions. Key exceptions were hospitalisations for diabetic ketoacidosis and heart failure, which warrant further investigation to understand the causes.