Healthcare utilisation and unmet health needs in children with intellectual disability: a propensity score matching approach using longitudinal cohort data

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

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.

Factors that affect GP referral of a child with intellectual disability for a mild illness: A discrete choice experiment

BACKGROUND

General practitioners (GP) report multiple challenges when treating individuals with intellectual disabilities which may influence referral rates. The study aimed to establish factors that influence GP's decision-making when referring a child with intellectual disabilities to the emergency department.

METHOD

Discrete choice experiments (DCEs) are increasingly used in health research to further understand complex decision making. A DCE was designed to assess the relative importance of factors that may influence a GP's (N = 157) decision to refer.

RESULTS

A random parameters model indicated that perceived limited parental capacity to manage an illness was the most important factor in the decision to refer a child to the ED, followed by a repeat visit, a referral request from the parent, and a Friday afternoon appointment.

CONCLUSION

Understanding the factors that influence referral is important for service improvement and to strengthen primary care provision for this population and their families.

Current services and outcomes of formerly institutionalised and never-institutionalised US adults with intellectual and developmental disabilities: A propensity score matching analysis

BACKGROUND

Deinstitutionalization research shows better services and outcomes relative to institutional life but has not compared formerly institutionalised and never-institutionalised service users.

METHODS

We used propensity score matching (PSM) to match formerly institutionalised and never-institutionalised participants on six personal characteristics. Data came from the 2018 to 2019 National Core Indicators In-Person Survey. We excluded current institution residents, and states with 25% + of missing data on former institutionalisation.

RESULTS

Overall, 15.5% of participants in the 29-state full sample had lived in an institution for 1 year or more. Findings from the PSM sample showed that former-institution residents were more likely to use congregate living arrangements and less likely to live with family. They experienced more loneliness, less support-related choice, and had a consistent pattern of disability service-focused social connections.

CONCLUSIONS

Many former institution residents remain disadvantaged relative to matched peers. There is a need to identify factors to enhance services and outcomes following deinstitutionalization.