• Health Policy and Management
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• v.31 no.2
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• pp.217-224
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• 2021

The objective of this study is to investigate the healthcare status of South Korea and other member countries of the Organization for Economic Cooperation and Development (OECD) using OECD health statistics 2020. We employed the position value for relative comparison index to measure the healthcare status in five following components: demand, supply, accessibility, quality, and cost. The Mann-Kendall test was used to analyze for increasing or decreasing trend of the position value for relative comparison values from 2000 to the recent year. Results showed that Korea was positioned above than the OECD median values in most of components, but lower than the median values in certain indices including healthcare employment, primary care, and mental health care. This study sheds some light on healthcare issues to be improved and the policy-makes can take into account for prior setting process.

• Health Policy and Management
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• v.29 no.1
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• pp.90-97
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• 2019

This study investigated the healthcare status of South Korea and member states of the Organization for Economic Cooperation and Development (OECD). By employing the position value for relative comparison index, healthcare status was measured through the following components: demand, supply, accessibility, quality, and cost. Statistical analysis was conducted through the Mann-Kendall test from analyzing trends from 2000 onwards. Results showed that while Korea, on average, scores higher than the OECD average in most of the investigated components, it is below average in certain indexes including primary care and mental health care. Considering the various health issues that have been raised about these indexes, it is important these components be improved upon by policy-makers.

• Health Policy and Management
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• v.33 no.2
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• pp.203-213
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• 2023

This study examined the trend of healthcare status and compared the status of South Korea and other member of the Organization for Economic Cooperation and Development (OECD) using the OECD health statistics 2022. We used the OECD health statistics from 2022 and a position value for relative comparison (PARC) index to compare the five elements of the healthcare system. The study also used a Mann-Kendall test to analyze the trend of the PARC values from 2000 to the present year. The findings of the study indicate that many South Korea's PARC values were higher than the OECD median. But practicing physician in supply part and medical cost were lower than OECD median but the trend significantly increased. Medical accessibility part and quality of care part except primary care, and mental health had a high relative position but the trend did not increased significantly. After outbreak of coronavirus disease 2019, there were changes in medical accessibility. Health screening and vaccinations showed an overall decline in 2020 compared to 2019. These results suggest that policymakers need to take necessary steps for a sustainable healthcare system in the country.

• Health Policy and Management
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• v.31 no.4
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• pp.491-507
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• 2021

Background: This study aims to measure regional healthcare differences in Korea, and define relatively underserved areas. Methods: We employed position value for relative comparison index (PARC) to measure the healthcare status of 250 areas using 137 indicators in five following domains: healthcare demand, supply, accessibility, service utilization, and outcome. We performed a sensitivity analysis using t-SNE (t-distributed stochastic neighboring embedding). Results: Based on PARC values, 83 areas were defined as relatively underserved areas, 49 of which were categorized as moderate and 34 as severe. The provincial regions with the most underserved areas were Gyeongbuk (16 areas), Gangwon (13), Jeonnam (13), and Gyeongnam (12). Conclusion: This study suggests a relative comparison approach to define relatively underserved areas in healthcare. Further studies incorporating various perspectives and methods are required for policy implications.

• Health Policy and Management
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• v.27 no.1
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• pp.88-94
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• 2017

The aim of this study was to investigate the current and trend of healthcare status of South Korea compared to Organization for Economic Cooperation and Development (OECD) countries. We used the position value for relative comparison (PARC) method for measuring the healthcare status of South Korea by five parts of healthcare policy (demand, supply, accessibility, quality, and cost). Additionally, we conducted Mann-Kendall test for analyzing the trend of PARC from 2000 to the present. Demand, supply, accessibility, and quality of healthcare of Korea were located upon the average of OECD countries, and showed an increasing trend from 2000 to the present. However, primary care and screening for cervical cancer were placed at a lower level compared the OECD average. In conclusion, the current state of healthcare in Korea seems to be generally beyond the average among OECD countries. However, some parts, including primary care, need to be improved.

• Health Policy and Management
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• v.32 no.1
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• pp.113-121
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• 2022

This study aims to compare the healthcare status of South Korea and other member of the Organization for Economic Cooperation and Development (OECD) using the OECD health statistics 2021. We used the position value for relative comparison (PARC) index to measure the five elements of the healthcare system, demand, supply, accessibility, quality, and cost. For the statistical analysis, Mann-Kendall test was performed to examine the trend of the PARC values from 2000 to the most recent year. The results showed that supply, demand, accessibility, and quality were above median than the OECD median and the cost was below median. In sectors such as primary care, health employment and mental health care were below median average. With these result, necessary steps for a sustainable healthcare should be taken into effort by policy makers.

• Health Policy and Management
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• v.28 no.1
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• pp.98-103
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• 2018

This study aims to evaluate the status of Korean healthcare among Organization for Economic Cooperation and Development countries and to monitor the trend of health care status since 2000. The position value for relative comparison (PARC) index was selected to gauge the level of healthcare status in demand, supply, accessibility, quality, and cost as per healthcare policy aspects. The Mann-Kendall test was conducted to allocate healthcare status of Korea since 2000. The PARC values indicate strength and weakness of Korean healthcare system by the mathematical comparisons. Korea positioned higher in demand, supply, accessibility, and quality. Yet, there are shortages in human resources and primary care. In conclusion, we suggest utilizing this study provides evidence to prioritize health care problems that can lead to establishing healthcare policy.

• Health Policy and Management
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• v.30 no.1
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• pp.131-138
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• 2020

The purpose of this study was to compare the health status of South Korea with those of Organization for Economic Cooperation and Development (OECD) countries and examine the trends. Position vAlue for Relative Comparison (PARC) was used as a gauge for comparison, and five sectors of the health care system were measured: demand, supply, accessibility, quality, and cost. The Mann-Kendall test was used as a statistical analysis method to examine trend of PARC values obtained from 2000 to recent years. According to the results, the demand, supply, accessibility, and quality sectors were higher than the OECD average, while the cost was lower than the average. However, there is a recent trend of sharp increases in health care costs. Some indicators: health employment, quality of primary care and mental health care were lower than the OECD average, and health determinants showed a worsening trend. Therefore, policy-makers need to take this into account and make efforts for sustainable health care.

• Health Policy and Management
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• v.33 no.2
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• pp.129-140
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• 2023

Background: This study aims to compare the burden of disease in Korea with other Organization for Economic Cooperation and Development (OECD) countries using the OECD health statistics from 1985 to 2020. Methods: We analyzed potential years of life lost (YLL) per 100,000 population using the Positive value for relative comparison (PARC) index, trend test, and average annual percentage change (AAPC) with logistic regression analysis. Results: The relative disease burden was good for many diseases, but the disease burden was severe for a few diseases in Korea. Diseases with a high relative burden of disease in Korea are as follows; intentional self-harm (YLL2020 575.6, AAPCYLL 2.6%; PARC2020 -1.000, AAPCPARC -15.8%), malignant neoplasms of the liver (YLL2020 136.6, AAPCYLL -3.9%; PARC2020 -1.000, AAPCPARC 0.0%), malignant neoplasms of the stomach (YLL2020 9.0, AAPCYLL 3.2%; PARC2020 -0.556, AAPCPARC -22.9%), Parkinson's disease (YLL2020 575.6, AAPCYLL 2.6%; PARC2020 -1.000, AAPCPARC -15.8%). Conclusion: Diseases with a high burden of disease are needed to be prioritized in the planning and execution of healthcare policies that can contribute to the efficient use of healthcare resources.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 1998.10a
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• pp.318-324
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• 1998

This study was conducted to derive optimal design floods by Generalized Extreme-value(GEV) distribution for the annual maximum series at ten watersheds along Han, Nagdong, Geum, Yeongsan and Seomjin river systems. Adequacy for the analysis of flood data used in this study was established by the tests of Independence, Homogeneity, detection of Outliers. L-coefficient of variation, L-skewness and L-kurtosis were calculated by L-moment ratio respectively. Parameters were estimated by the Methods of Moments and L-Moments. Design floods obtained by Methods of Moments and L-Moments using different methods for plotting positions in GEV distribution were compared by the relative mean and relative absolute error. It was found that design floods derived by the method of L-moments using weibull plotting position formula in GEV distribution are much closer to those of the observed data in comparison with those obtained by method of moments using different formulas for plotting positions in view of relative mean and relative absolute error.