Decomposing Disability Inequality in Unmet Healthcare Needs and Preventable Hospitalizations: An Analysis of the Korea Health Panel

Abstract

Objectives: This study examines the inequality between people with and without disabilities regarding unmet healthcare needs and preventable hospitalization.Methods: We used the Korea Health Panel of 2016–2018; the final analytical observations were 43,512, including 6.95% of persons with disabilities. We examined the differences in contributors to the two dependent variables and decomposed the observed differences into explained and unexplained components using the Oaxaca-Blinder approach.Results: Unmet healthcare needs and preventable hospitalizations were 5.6% p (15.36% vs. 9.76%) and 0.68% p (1.82% vs. 0.61%), respectively, higher in people with disabilities than in those without, of which 48% and 35% were due to characteristics that the individual variables cannot explain. Decomposition of the distributional effect showed that sex, age, and chronic disease significantly increased disparities for unmet healthcare needs and preventable hospitalization. Socioeconomic factors such as income level and Medical aid significantly increased the disabled–non-disabled disparities for unmet healthcare needs.Conclusion: Socioeconomic conditions increased the disparities, but around 35%–48% of the disparities in unmet healthcare needs and preventable hospitalization were due to unexplained factors, such as environmental barriers.

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

“…Another study found that 17.0% of people with disabilities experienced unmet healthcare needs in 2017 compared to 8.8% of people without disabilities in 2016 [ 5 ]. These results confirm that people with disabilities have more difficulties accessing healthcare services [ 28 ]. Moreover, these difficulties increased after the outbreak of COVID-19.…”

Is there a gap between sexes regarding factors related to the unmet dental care needs of disabled adults? An analysis from a national survey on disabled persons

“…A study from Greece showed that unmet needs for dental care were 1.8 times higher in disabled people than those who were not, and approximately 25% of disabled people did not receive dental care for economic reasons [32]. Socioeconomic factors, such as income level, were identi ed as one of the reasons for this gap [33][34][35]. A study from the United Kingdom also showed that disabled people had a higher rate of unmet need for medical care than people who were not disabled, and that women had a higher rate of unmet need for medical care than men within the disabled group [36].…”

Unmet Healthcare Needs among the Elderly Korean Population: Before and during the COVID-19 Pandemic

“…Most policies for reducing the prevalence of UHN are generally centered on vulnerable populations, including the elderly [4,7,9,15,16]. Previous studies on the elderly population were mainly conducted to identify factors affecting UHN [4,5,[17][18][19][20] and grasp the healthcare needs of older people with chronic diseases and disability [15,17,21]. Prior studies were also conducted on the determinants of inequality in UHN [21][22][23].…”

“…Previous studies on the elderly population were mainly conducted to identify factors affecting UHN [4,5,[17][18][19][20] and grasp the healthcare needs of older people with chronic diseases and disability [15,17,21]. Prior studies were also conducted on the determinants of inequality in UHN [21][22][23]. According to previous studies, UHN among the elderly is due to various factors, including socio-demographic or economic variables, such as sex, age, education, and income level [11,[22][23][24].…”

“…According to previous studies, UHN among the elderly is due to various factors, including socio-demographic or economic variables, such as sex, age, education, and income level [11,[22][23][24]. In particular, most of the inequality was due to socioeconomic conditions, including gender, age, and income, that widened the disparities [21][22][23][24].…”