Disruption of medical care among individuals in the southeastern United States during the COVID-19 pandemic

Abstract

Background: Widespread disruptions of medical care to mitigate COVID-19 spread and reduce burden on healthcare systems may have deleterious public health consequences.

Design and methods: To examine factors contributing to healthcare interruptions during the pandemic, we conducted a COVID-19 impact survey between 10/7-12/14/2020 among participants of the Southern Community Cohort Study, which primarily enrolled low-income individuals in 12 southeastern states from 2002-2009. COVID survey data were combined with baseline and follow-up data.

Results: Among 4,463 respondents, 40% reported having missed/delayed a health appointment during the pandemic; the common reason was provider-initiated cancellation or delay (63%). In a multivariable model, female sex was the strongest independent predictor of interrupted care, with odds ratio (OR) 1.63 (95% confidence interval [CI] 1.40-1.89). Those with higher education (OR 1.27; 95% CI 1.05-1.54 for college graduate vs ≤high school) and household income (OR 1.47; 95% CI 1.16-1.86 for >$50,000 vs <$15,000) were at significantly increased odds of missing healthcare. Having greater perceived risk for acquiring (OR 1.42; 95% CI 1.17-1.72) or dying from COVID-19 (OR 1.25; 95% CI 1.04-1.51) also significantly increased odds of missed/delayed healthcare. Age was inversely associated with missed healthcare among men (OR for 5-year increase in age 0.88; 95% CI 0.80-0.96) but not women (OR 0.97; 95% CI 0.91-1.04; p-interaction=0.04). Neither race/ethnicity nor comorbidities were associated with interrupted healthcare.

Conclusions: Disruptions to healthcare disproportionately affected women and were primarily driven by health system-initiated deferrals and individual perceptions of COVID-19 risk, rather than medical co-morbidities or other traditional barriers to healthcare access.

Figure 1.

Multivariable-adjusted odds ratios and 95% confidence intervals for the association of participant characteristics with missed or delayed healthcare. Model additionally adjusted for age.

Figure 2.

Differential association between age and missed healthcare appointments according to sex. A statistically significant interaction between sex and age (P=0.04) was observed. Age was inversely associated with odds of missing healthcare appointments among men but not among women. Other covariates in the multivariable model were assigned to their most common (mode) values of race/ethnicity (White), household income ($50,000+), education (college graduate or higher), insurance (Medicaid/Medicare), comorbidities (diabetes/ high blood pressure/heart disease/ kidney disease=yes; asthma/COPD/other chronic lung disease and rheumatoid arthritis/lupus/HIV/other autoimmune disorder=no), active cancer treatment (no), general health status (excellent/good), number of clinic visits (1-2), change in income during pandemic (no), change in employment during pandemic (no), COVID testing (not tested) and perceptions of risk of acquiring (unlikely) or surviving (likely) COVID-19.

Figure 3.

Predicted probabilities for missed or delayed healthcare by age, sex, general health status and income level. Predicted probabilities for missed or delayed healthcare according to age, sex and income level among those with excellent/very good general health status (1a-1c), good health status (2a-2c) or fair/poor health status (3a-3c). Other covariates in the multivariable model were assigned to their most common (mode) values of race/ethnicity, household income, education, insurance, comorbidities, active cancer treatment, general health status, number of clinic visits, change in income during pandemic, change in employment during pandemic, COVID testing and perceptions of risk of acquiring or surviving COVID-19 as listed in Figure 2.