Care delay during the Covid-19 pandemic in Germany – a cross-sectional online survey in the Nako study
Datos Bibliográficos
During the COVID-19 pandemic, non-COVID-19 related healthcare utilization declined in Germany, resulting in care delay, including delays and cancellations of routine, chronic, and even acute care. The aim of this study was to investigate factors (i.e. regional differences and participant characteristics) associated with care delay during the pandemic in Germany using a cross-sectional survey. In October 2022, a total of 117,466 participants from the German National Cohort (NAKO) study completed an online questionnaire on pandemic-related topics, including care delay during the COVID-19 pandemic. Regional differences and participant characteristics associated with care delay were assessed using (multilevel) logistic regression. One third of participants reported having experienced care delay. Care delay did not differ across the 13 federal states or 32 districts in Germany for which sufficient data were available. In the medical practice setting, care delay was nearly equally provider- and patient-related and was reported mostly for routine check-ups. In the hospital setting, care delay was predominantly provider-related and reported for newly occurring conditions. The odds for care delay were higher in females vs. males (odds ratio (OR): 1.30; 95% confidence interval (CI): 1.27–1.34), and in participants with vs. without chronic conditions (e.g. mental disorders, OR: 1.41, 95%CI: 1.36–1.46 or cardiovascular diseases, OR: 1.20 95%CI: 1.16–1.24) and decreased with age (e.g. 70 + vs. 50–59 years, OR: 0.59, 95%CI: 0.57–0.62). Care delay during the COVID-19 pandemic depended on participant characteristics including age, sex, and preexisting chronic conditions but not on regional (i.e. state and district-level) differences in Germany
Biostatistics · Confidence interval · German · Health care · Odds · Odds ratio · Pandemic · Public health · COVID-19 and healthcare impacts · COVID-19 epidemiological studies · Healthcare Policy and Management · Epidemiology
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