• Journal of the Korean Society of School Health
• /
• v.25 no.1
• /
• pp.105-113
• /
• 2012

Purpose: The purpose of this study was to identify the statistical indicators of OECD and Korea for student health among Korea's approval statistics. Methods: Searching for health indicators by using Health at a Glance 2009, Society at a Glance 2009, and Education at a Glance 2009 through the formal OECD web site in 2010, and investigating the approval statistics through the Korean formal organizational web sites and published data in 2012. Results: Among OECD indicators, indicators for adolescent health were smoking and alcohol consumption, nutrition, physical activity, overweight and obesity, bullying, risk behaviors, and poverty children. However, most of Korea student health indicators were missing except poverty children and life satisfaction, because OECD has taken chiefly data from Health Behavior in School-aged Children survey (HBSC), international study, which has not been carried out in Korea. The Ministry Of Education, Science And Technology (MEST) and the Ministry of Health and Welfare, and National Youth Policy Institute in Korea have produced the major statistics for student health which was only 11 (1.3%) among 858 approval statistics. Conclusion: Identifying a current Korea school health is essential through participating actively to OECD whose statistic indicators are internationally comparable with Students Physical Development Survey, MEST's approval statistics, using Korea Student Health Examination. It was also suggested that quantitative and qualitative expansions for Korea student health statistics by the activation of approval statistics including processed statistics, and by researchers' easy expanded access to a raw data.

• Health Policy and Management
• /
• v.20 no.1
• /
• pp.1-18
• /
• 2010

This article examines social determinants of population health in OECD countries, where life years, infant mortality, and PYLL are used as proxy variables of health. The unit of analysis is a country which is the OECD affiliate. A panel regression estimation is chosen as a method, using OECD Health Data. The results are: the increasing national health expenditure affected positively to improve population health. Education was rather a significant determinant of health than income level. The government direct investment for public health did not contribute positively to enhance population health. The expansion of health care coverage was working positively for improving health, but with a time lag. The supply of doctors was a most influential determinant of health. In case of Korea, the coverage expansion of health care was the most important determinant of health. The supply of doctors was, however, not a positive factor for better health, which is different result with the case of OECD countries.

• Health Policy and Management
• /
• v.13 no.4
• /
• pp.48-65
• /
• 2003

Detailed analyses of total health expenditure and its sub­categories are essential for the evidence­based health policy(EBHP). These analyses, again, should be based on timely and reliable data that are comparable across countries. The System of Health Accounts (SHA), published by the OECD in 2000, provides an integrated system of comprehensive and internationally comparable accounts. The author has implemented the SHA manual into Korean situation, and examined overall expenditure estimate and its basic functional breakdown following the manual. This study explains how pharmaceutical expenditure is estimated. The results are, then, analyzed particularly from the international perspective. Both administrative data in Statistical Yearbooks (National Health Insurance, Medical Aid, Industrial Accident Compensation Insurance) and survey data on Health and Nutrition are used for the estimation. Per capita pharmaceutical expenditure in Korea (183 US$ PPPs) was far less than the OECD average (308 US$ PPPs) in 2001, but pharmaceutical expenditure share in total health expenditure (20.3％) was higher than the average (16.7％). This can be explained by the fact that there is a statistically significant correlation between pharmaceutical expenditure share and per capita GDP of each country. Korean people follow the tendency of relatively low­income countries to spend less than OECD average for health care, but follow again their tendency to spend more on drugs than on other health care services. In consideration of results and analysis as above, per capita pharmaceutical expenditure in Korea is expected to grow in the future, but the growth rate of the pharmaceutical expenditure is expected to be less than that of overall health expenditure.

• Health Policy and Management
• /
• v.14 no.2
• /
• pp.99-116
• /
• 2004

This study estimates the determinants of national health expenditures of OECD countries using panel regression method. The data used are OECD Health Data(2003) covering 33 countries and from 1970 to 2001. This study shows several important different results compared to the previous studies. Further this study estimates the determinants of Korean case using data from 1m to 2000, and compare with the results of OECD panel. The main findings are as follows. The income elasticity of health expenditures is estimated below 1.0, but is shown above 1.0 when the different health systems of each country are controlled. The women's labor participation influences strongly positive effect on the health expenditures. The diffusion of new technologies is positively related with the increasing expense. The increasing government expenditures have a tendency not to contain health expenses, but to increase expenses. The expansion of public health insurance holders is containing the expenses, and the increasing number of doctors is pushing expenditures. This implies the health expenditures are influenced more by the induced demand of providers rather than the moral hazard of patients. However, the above result is opposite in Korean case. The existence of primary care doctors affects slightly up warding rather than containing expenditures. Finally the determinants are seriously depending upon which factors are included in the model and which statistical model is chosen. Therefore it must be cautious to interpret the results of statistical model.

• Management & Information Systems Review
• /
• v.32 no.1
• /
• pp.87-109
• /
• 2013

This study analyzed technical efficiencies of health service industry of OECD countries with DEA and SFA approaches using 10 year data from OECD Health Database. The results can be summarized as follows: First, Korea was found the best practice among 15 OECD countries based on CRS nondirectional SBM models. Second, it was found that some inefficiencies were due to environmental factors. Third, we found that environmental factors were important factors in efficiencies of health service industry by observing that there were large efficiency changes after adjusting slacks due to environmental factors. From the above, Korea led the OECD countries in health service industry and was the most competent. But this study has some limitation since the quality and cost of health care was not taken into account.

• Health Policy and Management
• /
• v.18 no.3
• /
• pp.110-127
• /
• 2008

Expenditures on pharmaceuticals of different concepts were estimated and their functional, financing and providers' breakdowns were examined in line with the OECD's System of Health Accounts (SHA) manual. This study also shows the way such estimates are made. The results are then analyzed particularly from the international perspective. Data from both Household Survey by the National Statistical Office and the National Health and Nutritional Survey by the Ministry of Health and Welfare of Korea were used to estimate pharmaceutical expenditures that. are financed by out-of-pocket payments of the household, while national health insurance data etc. were used for estimation of pharmaceutical expenditures that are financed by public funding sources. The 'per capita expenditure on pharmaceutical/medical non-durables' in Korea stood at 380 US$ PPPs, less than the OECD average of 443 US$ PPPs in 2006, but its share of the per capita health expenditure of 25.9% noticeably outnumbered the OECD average of 17.1%, due partly to low per capita health expenditure as a denominator of the ratio. This indicates that Koreans tend to spend less on health care than an OECD average, while tending to spend more on pharmaceuticals than on other health care services, much like the pattern found in relatively low income countries. An international pharmaceuticals pricing mechanism is most likely responsible for such a tendency. In addition, it is to be noted that the percentage comes down to 21.0%, when expenditures on both medical non-durables and herbal medicine, which is locally quite popular among the elderly, have been excluded.

• Health Policy and Management
• /
• v.31 no.4
• /
• pp.409-422
• /
• 2021

The growing use of prescription analgesic opioids has rapidly escalated the treatment of chronic pain since the 1990s; however, it is also highly needed to control opioid-related issues, including opioids misuse, abuse, and addiction. In 2018, Organization for Economic Cooperation and Development (OECD) secretariat administered the survey on opioids use and policies to OECD countries and presented it at the Health Committee meeting of December 2018. This study aimed to review the opioids use in OECD countries and their policies to prevent and reduce associated harms, also seek the available policy lessons from OECD countries. More recently, opioids prescribing rate have been increased 14.7% between 2011-2013 and 2014-2016 and steadily focused on the main substance misused and abused in Korea. In addition, policy efforts have contributed to developing a guideline for prescribing opioids to steer the appropriate use of prescription analgesic opioids since 2000 in Korea, so it is not enough to control opioids compared with other OECD countries. Therefore, taking a people-centered and public health perspective, it will consider the health system policies and interventions at a national level to improve their preparation and approach to control opioid-related issues.

• Korean Journal of Health Education and Promotion
• /
• v.31 no.1
• /
• pp.45-56
• /
• 2014

Objectives: This study aimed to examine how the relationship between socioeconomic factors at the macro level and suicide mortality rate of Korea was different from that of other OECD countries. Methods: We created OECD panel data of 29 OECD countries from 1985 to 2006 and analyzed the relationship between socioeconomic factors and suicide mortality rate for separate age and sex groups using a fixed-effect model. Economic factors included per capita GDP, per capita GDP growth rate, unemployment rate, and women's economic participation rate. Social factors included birth rate, alcohol consumption, and the percentage of population 65 and older. Results: Unemployment rate had a positive relationship with suicide in other countries but it had a negative relationship in some groups of Korea. Women's economic participation rate was both positively and negatively related with suicide in Korea but it did not relate to suicide in others. The negative relationship of birth rate and the positive relationship of alcohol consumption with suicide were evident in Korea, which were not found in other countries. The percentage of population 65 and older was negatively correlated in some female groups in Korea, while no significant relationship was found in other countries. Conclusions: Korea was substantially different from other OECD countries in the relationship between socioeconomic factors and suicide mortality rate.

• Journal of Environmental Health Sciences
• /
• v.39 no.2
• /
• pp.130-137
• /
• 2013

Objectives: The OECD QSAR Application Toolbox was developed by the Organisation for Economic Cooperation and Development (OECD) to facilitate the practical use of QSAR approaches in regulatory contexts as well as to reduce the need for additional animal testing. In this study, human health and the ecotoxicity of chemicals were predicted by applying the OECD QSAR Application Toolbox and the results were compared with experimental data in order to evaluate the applicability of this program. Methods: Read-across, trend analysis, and QSAR of OECD QSAR Application Toolbox were used for the prediction of toxicity. Results: The toxicity prediction was conducted on 6,354 chemicals for which toxicity data have been produced on the six endpoints of skin sensitization, skin irritation, eye irritation, mutagenicity, and acute toxicities of fish and Daphnia. From the total of 6,354, we obtained prediction results for 1,621 chemicals (25.5%). Conclusions: The predicted properties of mutagenicity, skin sensitization, and acute aquatic toxicities were reasonably good when compared with experimental data, but other endpoints were not due to the limitation of applicable chemical groups.

• Journal of the Korea Society of Computer and Information
• /
• v.22 no.10
• /
• pp.145-150
• /
• 2017

This study aims to analyze panel data using OECD Health data of 34 years to examine how significant the inequality of income is to the inequality of health. The data was from OECD's pooled Health data of 32 countries from 1980 to 2013. The process of determining analysis model was as follows; First, through the descriptive statistics, we examined averages and standard deviation of variables. Second, Lagrange multiplier test has done. Third, through the F-test, we compared Least squares method and Fixed effect model. Lastly, by Hausman test, we determined proper model and examined effective factor using the model. As a result, rather than Pooled OLS Model, Fixed Effect Model was shown as effective in order to consider the characteristics of individual in the panel. The results are as follows: First, as relative poverty rate(${\beta}=-19.264$, p<.01) grows, people's life expectancy decreases. Second, as the rate of smoking(${\beta}=-.125$, p<.05) and the rate of unemployment (${\beta}=-.081$, p<.01) grows, people's life expectancy decreases. Third, as health expenditure(${\beta}=.414$, p<.01) shares more amount of GDP and as the number of hospital beds(${\beta}=-.190$, p<.05) grows, people's life expectancy increases.