A comparison of factors associated with unmet healthcare needs in people with disabilities before and after COVID-19: a nationally representative population-based study

Abstract

Abstract Background People with disabilities, who require numerous healthcare services, are vulnerable to unmet healthcare needs. This study aimed to investigate and identify the factors that influence unmet healthcare needs among people with disabilities and to compare these factors before and after the COVID-19 pandemic in South Korea. Methods A propensity score matching analysis was conducted using two datasets from the National Survey of Disabled Persons collected in 2017 and 2020. The participants were matched based on variables known to influence healthcare utilization. Based on the Andersen model, logistic regression was performed to analyze the key characteristics of the factors associated with unmet healthcare needs, including predisposing, enabling, and need factors. Results Propensity score matching resulted in the inclusion of 1,884 participants in each group: an experimental group and control group. Before COVID-19, factors associated with unmet healthcare needs included sex, age, marital status, and education level (predisposing factors), instrumental activities of daily living dependency, satisfaction with medical staff’s understanding of disability, satisfaction with medical institutional facilities and equipment (enabling factors), subjective health status, and depressive symptoms (need factors). After COVID-19, factors included physical disability, instrumental activities of daily living dependency, and discrimination (enabling factors), and subjective health status, chronic diseases, depressive symptoms, and regular medical care (need factors). No significant predisposing factors affecting unmet healthcare needs were identified after COVID-19. Conclusions This study compared the factors affecting unmet healthcare needs among people with disabilities before and after COVID-19. Recognizing the different factors associated with unmet healthcare needs before and after COVID-19, (e.g., sex, type of disability, satisfaction with medical staff’s understanding of disabilities, medical institutional facilities and equipment considering the disabled, discrimination, chronic diseases, and regular medical care) may help governments and policymakers establish strategies to reduce and prevent unmet healthcare needs during and a future crisis.

Keywords

• Anderson model
• COVID-19
• Disabled persons
• Propensity score matching analysis
• Unmet healthcare needs