• Health Policy and Management
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• v.30 no.1
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• pp.112-119
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• 2020

Suicide has been a long-standing problem for global public health, along with almost 800,000 deaths from suicide worldwide in 2016, accounting for 1.4% of all deaths. South Korea was ranked first in suicide mortality in 2018 among countries in the Organization for Economic Cooperation and Development. This study aimed to suggest up-to-date information about suicide-related indicators such as the rate of suicidal ideation, suicide attempt, and suicide death, and its trends by applying sampling weight to make it nationally representative. In this study, we used the data sources: Korea National Health and Nutrition Examination (KNHANES, '07-13, '15-18), Korean Community Health Survey (KCHS, '08-09, '13, '17), Korean Wealth Panel Study (KOWEPS, '12-18), Korea Health Panel Survey (KHP, '10-13), and Statistics Korea (1983-2017). The rate of suicidal ideation as recent year was 4.73% (KNHANES, '17), 6.96% (KCHS, '17), 2.29% (KOWEPS, '18), and 5.39% (KHP, '13). That of suicide attempt as recent year was 0.51% (KNHANES, '18), 0.32% (KCHS, '17), and 0.15% (KOWEPS, '18). Annual percentage change (APC) of suicidal ideation was -15.4% (KNHANES, '07-13, '15, '17), -2.5% (KCHS, '08-09, '13, '17), -10.8% (KOWEPS, '12-18), and -10.9% (KHP, '10-13). APC of suicide attempt was -4.4% (KNHANES, '07-13, '15-18), -4.4% (KCHS, '08-09, '13, '17), and -13.6% (KOWEPS, '12-18). APC of death by intentional self-harm was -1.25% (Statistics Korea, '07-18). All suicide-related indicators were found to be decreasing in the overall from 2009. Individuals with lower income level were more likely to experience suicidal ideation and suicide attempts. Even though suicide rate had been continuously decreasing from its highest point in 2011 (suicide rate: 31.7 per 100,000 population) to 2017 (suicide rate: 24.3 per 100,000 population), it increased again in 2018 (suicide rate: 26.6 per 100,000 population). This information would be grounded on policy implementation for suicide prevention, thus continuous data observation is necessary.

• The Korean Journal of Applied Statistics
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• v.29 no.7
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• pp.1329-1346
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• 2016

Korea Health Panel (KHP) data and Korea National Health and Nutrition Examination Survey (KNHANES) data are collected by self-assess and self-report for individual's health status and medical use. Previous studies have claimed that the reliability for prevalence rates and health life expectancies obtained from these data should be validated. National Health Insurance Services in Korea recently released a sample cohort DB that contain all data related to the use of medical facilities for all entire Korea citizens. It has been shown that disease-specific prevalence rates calculated from these data are representative and reliable for the entire population. In this paper, we evaluate the reliability of prevalence rates derived from self-reported data such as KHP and KNHANES by comparing to the prevalence rates from the sample cohort DB. We found that both KHP and KNHANES underestimate prevalence rates and in turn overestimate health life expectancies. Moreover, the general trends of health life expectancies might be distorted (except for the sample cohort DB) because of sampling and non-sampling errors.

• Journal of the Korean Data and Information Science Society
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• v.28 no.1
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• pp.195-206
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• 2017

The purpose of this study was to identify factors affecting quality of health care. Methods: The data were derived from the 2011-2013 Korea health panel survey (beta version 1.0). The data were analyzed using SPSS 21.0 with descriptive statistics, ${\chi}^2$-test, and multiple logistic regression analysis. In general characteristics, common factors influencing the quality of health care were age, marital status, education level, and subjective health status. In variables related to health care utilization, unmet healthcare needs, and limitation of dental care utilization were the significant factors affecting quality of health care. The results of this study show that various factors influence quality of health care. These findings can be used to develop strategies to improve health care.

• Quality Improvement in Health Care
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• v.25 no.2
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• pp.44-55
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• 2019

Purpose: To investigate whether changes in Medical Aid (MA) status are associated with unmet need and catastrophic health expenditure (CHE). Methods: Data from the 2010 to 2014 Korea Health Panel (KHP) were used. The impact of changes in annual MA status ('MA to MA,' 'MA to MA Exit,' 'MA Exit to MA,' and 'MA Exit to MA Exit') on unmet need (all-cause and financial) and CHE (10% and 40% of household capacity to pay) were examined using the generalized estimating equation (GEE) model. Analysis was conducted separately for MA type I and II individuals. Results: In 1,164 Medical Aid type I individuals, compared to the 'MA to MA' group, the 'MA to MA Exit' group had increased likelihoods of all-cause and financial unmet need. This group also showed higher likelihoods of CHE at the 10% standard. The 'MA Exit to MA Exit' group showed increased likelihoods at the 10% and 40% CHE standards. In 852 type II recipients, the 'MA to MA Exit' group had higher likelihoods of CHE at the 10% standard. Conclusions: Type 1 MA exit beneficiaries had higher likelihoods of all-cause and financial unmet need, along CHE at the 10% standard. Type I 'MA Exit to MA Exit' beneficiaries also showed higher likelihoods of CHE at the 10% and 40% standards. In type II recipients, MA exit beneficiaries had higher likelihoods of CHE at the 10% standard. The results infer the importance of monitoring MA exit beneficiaries as they may be vulnerable to unmet need and CHE.

• The Korean Journal of Health Service Management
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• v.6 no.1
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• pp.77-86
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• 2012

Objective of the study represents experiences of medical utilization of Psychiatric Outpatients. This research draws on information obtained from the 2008 National-wide sampling study of the Korean Healthcare Panel(KHP) conducted. The results of our study suggest the significance of variables such as the gender(p<.001) in the social demographical characteristics, the medical security type(p<.016), medical institution utilization(p<.012) treatment type(p<.004) in the utilization factors. In the case of medical utilization cost, the financial support factor(p<.018) showed a significant relationship. Depending on the particularities of gender, medical security type, financial support, medical institution utilization, treatment type were determined through a multiple logistics regression analysis. Gender showed that, among Psychiatric outpatient age of 30-59 level was 5.358 times and 60 years and older, their the second medical examination level was 4.490 times higher than Psychiatric outpatients under the age of 29. Health insurance type showed for the others medical allowance was 6.712 times higher than job health insurance and the other treatment was 0.395 times lower than drug treatment. Psychiatric outpatients utilization are rooted in the thoughts and factor levels of the Psychiatric patients and must be understood from the Psychiatric outpatients's perspective. The point is not only to gauge the patients research during Psychiatric medical utilization. The important of social community mental healthcare services levels goes beyond the goal of enhancing healthcare.

• Korea Journal of Hospital Management
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• v.26 no.3
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• pp.68-83
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• 2021

Background: It is widely acknowledged that single bedrooms have many potential advantages compared to multiple bedrooms. However, Korea has a reimbursement system that patients have to pay the additional fee if they will use single bedroom or pay-bed (1-3 bedroom). There is little research on patients' bed selection and relationship between patient satisfaction and bed type in the Korean setting. Methods: Using the 2017 Korea Health Panel (KHP) Survey data, we modified bed type by two dichotomous variables: single bedroom vs. multiple bedroom (2+ bedrooms) and pay-bed (1-3 bedroom) vs. reimbursed bed (4+ bedroom). Multivariate logistic regression is performed to determine the factors affecting the patient's choice of room types. Multivariate regression analysis was conducted to examine how hospital room types are affecting patient satisfaction. Results: Single room and pay-bed (1-3 bedroom) use was influenced by patient age (19- years old), male, a person at work, hospitalizing in a clinic, and birth. After controlling variables of the behavioral model of medical utilization, the association between patient satisfaction and use of single bedroom & pay-bed (1-3 bedroom). Cause of hospitalization, major treatment, and recognition of unnecessary care are statistically significant variables on patient satisfaction. Conclusion: Although the single room is about the standard for newly built hospitals in western countries, it remains unclear that single room or pay-bed (1-3 bedroom) has positive effects on patient's outcomes and satisfaction. In this empirical study, the difference in patient satisfaction by bedroom type was not noticeable. In terms of bed management by hospital staff, securing patient credibility in hospital care is an important task. Patients' perception of whether medical staffs have encouraged unnecessary treatment or tests has a significant impact on patient's satisfaction.

• 한국노년학
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• v.39 no.3
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• pp.467-484
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• 2019

The purpose of this study is to explore latent classes of longitudinal medical expenses of older people and to analyze its predictors and its effects on subjective health. Among participants of the Korean Health Panel, the sample of this study includes 1,119 people who is 65-year-old or older and reported their medical expenses for nine consecutive years. The analyses were conducted in three steps. First, Growth Mixture Model (GMM) was applied to find distinct subgroups showing similar patterns in medical expenses. The results showed four groups which were classified as high medical expenditure maintenance group, medical expenditure increase group, low medical expenditure maintenance group, and medical expenditure reduction group. Second, the multinominal logistic regression found that the presence of spouse, economic participation, the number of chronic diseases, and the type of health insurance were significant predictors of latent classes in medical expenses. In particular, the greater the number of chronic diseases, the higher the likelihood of belonging to the high medical expenditure maintenance group. In addition, medical benefit recipients are more likely to belong to the low medical cost maintenance and medical cost reduction groups. Third, multiple regression analysis revealed that the older people in the groups with low or reducing expenses reported better subjective health than people with higher expenses. This study has its meanings in exploring the heterogeneity in longitudinal medical expenses among older people and its predictors and its associations with health outcome. The results of this research provide background information in establishing public health policy for older people.