The Association Among Individual and Contextual Factors and Unmet Healthcare Needs in South Korea: A Multilevel Study Using National Data

Lee, Seung Eun; Yeon, Miyeon; Kim, Chul-Woung; Yoon, Tae-Ho

doi:10.3961/jpmph.16.035

Cited by 17 publications

(24 citation statements)

References 28 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…For instance the degree of urbanity at county level, bearing in mind some counties are more urbanised than others and the rural urban disparities in Kenya [53]. This is consistent with studies elsewhere [54], moreover this study also noted a positive significant association between urban residence and cost-related unmet need. This confirms that place(region) does influence health seeking behaviour, like in this case of unmet need due to cost [55,56].…”

Section: Discussionsupporting

confidence: 90%

Cost–related unmet need for healthcare services in Kenya

Njagi

Arsenijevic

Groot

2020

BMC Health Serv Res

View full text Add to dashboard Cite

Background: The assessment of unmet need is one way to gauge inequities in access to healthcare services. While there are multiple reasons for unmet need, financial barriers are a major reason particularly in low-and middleincome countries where healthcare systems do not offer financial protection. Moreover, accessibility and affordability are paramount in achieving universal health coverage. This study examines the extent of unmet need in Kenya due to financial barriers, the associated determinants, and the influence of regional variations. Methods: We use data from the 2013 Kenya household health expenditure and utilization (KHHEUS) cross sectional survey. Self-reported unmet need due to lack of money and high costs of care is used to compute the outcome of interest. A multilevel regression model is employed to assess the determinants of cost-related unmet need, confounding for the effect of variations at the regional level. Results: Cost-related barriers are the main cause of unmet need for outpatient and inpatient services, with wide variations across the counties. A positive association between county poverty rates and cost-related unmet is noted. Results reveal a higher intraclass correlation coefficient (ICC) of 0.359(35.9%) for inpatient services relative to 0.091(9.1%) for outpatient services. Overall, differences between counties accounted for 9.4% (ICC~0.094) of the total variance in cost-related unmet need. Factors that positively influence cost-related unmet need include older household heads, inpatient services, and urban residence. Education of household head, good self-rated health, larger household size, insured households, and higher wealth quintiles are negatively associated with cost-related unmet need. Conclusion: The findings underscore the important role of cost in enabling access to healthcare services. The county level is seen to have a significant influence on cost-related unmet need. The variations noted in cost-related unmet need across the counties signify the existence of wide disparities within and between counties. Scaling up of health financing mechanisms would fundamentally require a multi-layered approach with a focus on the relatively poor counties to address the variations in access. Further segmentation of the population for better targeting of health financing policies is paramount, to address equity in access for the most vulnerable and marginalized populations.

show abstract

Section: Discussionsupporting

confidence: 90%

Cost–related unmet need for healthcare services in Kenya

Njagi

Arsenijevic

Groot

2020

BMC Health Serv Res

View full text Add to dashboard Cite

show abstract

“…Gender (female), lower education level, rural residents, lowest household income, poor self-reported health status, and often stress awareness increased the probability of unmet medical needs. This result is consistent with that of a previous study that analyzed factors that are related to unmet medical needs caused by financial burden [ 10 ]. Furthermore, Kim et al [ 8 ] reported that lower education level is associated with higher odds of unmet medical needs.…”

Section: Discussionsupporting

confidence: 93%

“…Although the association between chronic diseases and unmet medical needs was not significant in this study, a previous study showed that the crude relative risk for dying was 1.79 in elderly individuals who had unmet medical needs among those who suffered from two or more chronic conditions [ 11 ]. As result, the strongest predictor of unmet medical needs was self-reported health status, a finding supported by prior studies [ 6 , 10 ].…”

Section: Discussionsupporting

confidence: 81%

“…A total of 4,946 individuals were finally included in this study ( Figure 1 ). We assessed the unmet medical needs based on the KNHANES question: “During the past year, was there ever a time when you wanted medical care but could not get it?” A “yes” response was used to define an experience of unmet medical need [ 10 ]. Since independent variables show general characteristics, the following variables were used: sex, age, education, type of insurance, residence, marital status, economic activity, household income, and private health insurance.…”

Section: Methodsmentioning

confidence: 99%

See 1 more Smart Citation

Regional Disparity and Factors Influencing Unmet Medical Needs: A Study Based on the Sixth Korea National Health and Nutrition Examination Survey (2015)

Lim

2017

Osong Public Health Res Perspect

View full text Add to dashboard Cite

ObjectivesThis study aimed to determine regional differences and the factors that affect unmet medical needs.MethodsData from the 6th Korea National Health and Nutrition Examination Survey (2015) were used, and 4,946 health survey participants who provided responses on medical utilization and health behavior were included in the study.ResultsA statistically significant difference was observed in the incidence rate of unmet medical needs in terms of region. The independent variables that affected unmet medical needs were sex, age, education, region, household income, insurance type, smoking status, self-reported health status, and stress awareness. Gender (female), lower education level, rural residents, lowest household income, poor self-reported health status, and stress awareness increased the probability of unmet medical needs.ConclusionOur findings suggested that different policies and approaches should be considered for each population that is at risk to address the primary cause of the unmet medical needs. Further studies that include medical expenses and the relevant variables of an area should be conducted in the future.

show abstract

“…Accordingly, it can be assumed that elderly individuals in regions with serious neighborhood deprivation, increasingly experience inequalities in health care accessibility [17,18]. The association between neighborhood deprivation and unmet health care needs has been investigated in the general adult population [1,19–21] but not in the elderly population.…”

Section: Introductionmentioning

confidence: 99%

Neighborhood Deprivation and Unmet Health Care Needs: A Multilevel Analysis of Older Individuals in South Korea

Lee

Yeon

Kim

et al. 2019

Osong Public Health Res Perspect

Self Cite

View full text Add to dashboard Cite

ObjectivesIn this study the relationship between neighborhood deprivation and the unmet health care needs of elderly individuals (≥ 65 years) was examined. Some previous studies suggested that neighborhood characteristics affect access to health care, yet research on the unmet needs of older individuals is limited.MethodsMultilevel logistic regression analysis was used to assess the relationship of neighborhood-level factors with unmet health care needs due to costs, adjusting for individual-level factors, in individuals ≥ 65 years in the 2017 Korean Community Health Survey (n = 63,388).ResultsThere were 2.6% of elderly individuals who experienced unmet health care needs due to costs. Following adjustment for individual and neighborhood characteristics, the neighborhood deprivation in urban areas was found to have an inverse association with unmet needs (odds ratio = 0.50; 95% confidence interval = 0.24–1.06) for the most deprived quartile versus the least deprived quartile). However, in rural areas neighborhood deprivation was not a significant variable. Among the individual-level variables, household income was one of the strongest correlates with unmet needs in both urban and rural areas.ConclusionThe present findings suggest that targeted policy interventions reflecting both neighborhood and individual characteristics, should be implemented to reduce the unmet health care needs of elderly individuals.

show abstract

The Association Among Individual and Contextual Factors and Unmet Healthcare Needs in South Korea: A Multilevel Study Using National Data

Cited by 17 publications

References 28 publications

Cost–related unmet need for healthcare services in Kenya

Cost–related unmet need for healthcare services in Kenya

Regional Disparity and Factors Influencing Unmet Medical Needs: A Study Based on the Sixth Korea National Health and Nutrition Examination Survey (2015)

Neighborhood Deprivation and Unmet Health Care Needs: A Multilevel Analysis of Older Individuals in South Korea

Contact Info

Product

Resources

About