Health care utilization before and after COVID-19 diagnosis: a multidisease matched-cohort study by sociodemographic factors

BACKGROUND: The COVID-19 pandemic substantially disrupted healthcare utilization across clinical conditions, populations, and care settings. Consistent and equitable access to care is essential to mitigate the long-term consequences of COVID-19, particularly among individuals with pre-existing conditions. While prior studies have documented broad patterns in healthcare use during the pandemic, limited evidence exists on how utilization shifts before and after a COVID-19 diagnosis, particularly across specific diseases, encounter types, and sociodemographic subgroups. METHODS: We conducted a matched retrospective cohort study using electronic health record data from MedStar Health between March 25, 2019, and June 30, 2021. A difference-in-differences design was used to compare changes in health care utilization between adult patients who tested positive for COVID-19 (exposure group) and those who tested negative (comparison group), across the 6-month periods before and after testing. Outcomes included encounters across outpatient, inpatient, emergency department, and virtual settings, overall and stratified by pre-existing conditions (heart failure, diabetes mellitus, kidney disease, malignant neoplasm, hypothyroidism, hyperthyroidism, anxiety disorder, depressive disorder, and drug poisoning/overdose), while accounting for demographic characteristics (sex, age, race/ethnicity, insurance type, state of residence) and census tract-level socioeconomic indicators (median household income, educational attainment, and poverty/food access). To estimate the absolute burden of health care utilization associated with COVID-19, we converted DiD rate ratios into excess encounters per 1,000 individuals in the exposed group. RESULTS: COVID-19 exposure was associated with a 4% overall reduction in health care utilization during the post-COVID period (RR = 0.96, p < 0.001, 262 fewer visits per 1,000 patients), primarily driven by decreased outpatient visits (RR = 0.96, p < 0.001). Significant declines were observed among adults aged ≥ 65 years (RR = 0.92, p < 0.001), males (RR = 0.90, p < 0.001), Black individuals (RR = 0.96, p < 0.001), and Medicare beneficiaries (RR = 0.91, p < 0.001). Geographically, encounter rates declined significantly in DC (RR = 0.93, p < 0.001) and Maryland (RR = 0.98, p = 0.023), but not in Virginia. Socioeconomic indicators also correlated with healthcare utilization: patients residing in areas with lower income (RR = 0.94, p = 0.003), lower educational attainment (RR = 0.95, p = 0.011), or higher rates of food stamp/SNAP participation (RR = 0.93, p < 0.001) experienced greater declines in utilization. Among clinical conditions, the largest reductions in healthcare visits were seen for patients with kidney disease (RR = 0.88, p < 0.001), drug poisoning/overdose (RR = 0.88, p < 0.001), hypothyroidism (RR = 0.91, p < 0.001), diabetes mellitus (RR = 0.94, p < 0.001), and heart failure (RR = 0.94, p = 0.002). In contrast, encounters for patient cohorts with hyperthyroidism (RR = 1.14, p = 0.004) increased notably, while those for depressive disorders (RR = 1.03, p = 0.072) showed a modest increase. No significant changes were observed in patient cohorts with anxiety (RR = 1.00, p = 0.83) and cancer (RR = 1.00, p = 0.81). CONCLUSIONS: COVID-19 exposure was associated with broad but varied changes in healthcare utilization during the post-COVID period. Several chronic conditions showed notable declines in encounter rates, although these patterns were not consistent across all conditions. The heterogeneity in utilization patterns suggests potential gaps in ongoing care and highlights the need for targeted efforts to support continued management of health conditions after COVID-19.