Fully automated quantitative coronary angiography versus optical coherence tomography guidance for coronary stent implantation (FLASH): Study protocol for a randomized controlled noninferiority trial.

BACKGROUND: Artificial intelligence-based quantitative coronary angiography (AI-QCA) has been developed to provide a more objective and reproducible data about the severity of coronary artery stenosis and the dimensions of the vessel for intervention in real-time, overcoming the limitations of significant inter- and intraobserver variability, and time-consuming nature of on-site QCA, without requiring extra time and effort. Compared with the subjective nature of visually estimated conventional CAG guidance, AI-QCA guidance provides a more practical and standardized angiography-based approach. Although the advantage of intravascular imaging-guided PCI is increasingly recognized, their broader adoption is limited by clinical and economic barriers in many catheterization laboratories. METHODS: The FLASH (fully automated quantitative coronary angiography versus optical coherence tomography guidance for coronary stent implantation) trial is a randomized, investigator-initiated, multicenter, open-label, noninferiority trial comparing the AI-QCA-assisted PCI strategy with optical coherence tomography-guided PCI strategy in patients with significant coronary artery disease. All operators will utilize a novel, standardized AI-QCA software and PCI protocol in the AI-QCA-assisted group. A total of 400 patients will be randomized to either group at a 1:1 ratio. The primary endpoint is the minimal stent area (mm2), determined by the final OCT run after completion of PCI. Clinical follow-up and cost-effectiveness evaluations are planned at 1 month and 6 months for all patients enrolled in the study. RESULTS: Enrollment of a total of 400 patients from the 13 participating centers in South Korea will be completed in February 2024. Follow-up of the last enrolled patients will be completed in August 2024, and primary results will be available by late 2024. CONCLUSION: The FLASH is the first clinical trial to evaluate the feasibility of AI-QCA-assisted PCI, and will provide the clinical evidence on AI-QCA assistance in the field of coronary intervention. CLINICAL TRIAL REGISTRATION: URL: https://www. CLINICALTRIALS: gov. Unique identifier: NCT05388357.

Comparison of diagnosis-based risk adjustment methods for episode-based costs to apply in efficiency measurement.

BACKGROUND: The recent rising health spending intrigued efficiency and cost-based performance measures. However, mortality risk adjustment methods are still under consideration in cost estimation, though methods specific to cost estimate have been developed. Therefore, we aimed to compare the performance of diagnosis-based risk adjustment methods based on the episode-based cost to utilize in efficiency measurement. METHODS: We used the Health Insurance Review and Assessment Service-National Patient Sample as the data source. A separate linear regression model was constructed within each Major Diagnostic Category (MDC). Individual models included explanatory (demographics, insurance type, institutional type, Adjacent Diagnosis Related Group [ADRG], diagnosis-based risk adjustment methods) and response variables (episode-based costs). The following risk adjustment methods were used: Refined Diagnosis Related Group (RDRG), Charlson Comorbidity Index (CCI), National Health Insurance Service Hierarchical Condition Categories (NHIS-HCC), and Department of Health and Human Service-HCC (HHS-HCC). The model accuracy was compared using R-squared (R2), mean absolute error, and predictive ratio. For external validity, we used the 2017 dataset. RESULTS: The model including RDRG improved the mean adjusted R2 from 40.8% to 45.8% compared to the adjacent DRG. RDRG was inferior to both HCCs (RDRG adjusted R2 45.8%, NHIS-HCC adjusted R2 46.3%, HHS-HCC adjusted R2 45.9%) but superior to CCI (adjusted R2 42.7%). Model performance varied depending on the MDC groups. While both HCCs had the highest explanatory power in 12 MDCs, including MDC P (Newborns), RDRG showed the highest adjusted R2 in 6 MDCs, such as MDC O (pregnancy, childbirth, and puerperium). The overall mean absolute errors were the lowest in the model with RDRG ($1,099). The predictive ratios showed similar patterns among the models regardless of the  subgroups according to age, sex, insurance type, institutional type, and the upper and lower 10th percentiles of actual costs. External validity also showed a similar pattern in the model performance. CONCLUSIONS: Our research showed that either NHIS-HCC or HHS-HCC can be useful in adjusting comorbidities for episode-based costs in the process of efficiency measurement.

Cancer-Related Dysfunctional Beliefs About Sleep Mediate the Influence of Sleep Disturbance on Fear of Progression Among Patients With Surgically Resected Lung Cancer.

BACKGROUND: Lung cancer is associated with significant psychological distress, including fear of progression (FoP). Because insomnia and depression are highly prevalent and associated with FoP, we examined the association between FoP, insomnia, and depression in cancer patients. Furthermore, we tested the mediation effect of cancer-related dysfunctional beliefs about sleep (C-DBS) on this association. METHODS: We analyzed data collected from patients with surgically resected non-small cell lung cancer from a single-center randomized controlled study investigating digital healthcare applications. Baseline demographic and clinical variables were collected. In addition, self-reported questionnaires including the Fear of Progression Questionnaire-Short Form, Patients Health Questionnaire-9 items (PHQ-9), Insomnia Severity Index, and C-DBS were administered. RESULTS: Among the 320 enrolled patients with lung cancer, a regression model showed that FoP was predicted by age (ß = -0.13, P = 0.007), PHQ-9 (ß = 0.35, P < 0.001), and C-DBS (ß = 0.28, P < 0.001). Insomnia did not directly influence FoP, but C-DBS mediated the association. Depression directly influenced FoP, but C-DBS did not mediate this association. CONCLUSION: Among patients with surgically resected lung cancer, C-DBS mediated the effects of severity of insomnia on FoP. Depression directly influenced FoP, but C-DBS did not influence this association. To reduce FoP among patients with lung cancer, C-DBS should be addressed in the cognitive behavioral therapy module.

Do health preferences differ among Asian populations? A comparison of EQ-5D-5L discrete choice experiments data from 11 Asian studies.

INTRODUCTION: Many countries have established their own EQ-5D value sets proceeding on the basis that health preferences differ among countries/populations. So far, published studies focused on comparing value set using TTO data. This study aims to compare the health preferences among 11 Asian populations using the DCE data collected in their EQ-5D-5L valuation studies. METHODS: In the EQ-VT protocol, 196 pairs of EQ-5D-5L health states were valued by a general population sample using DCE method for all studies. DCE data were obtained from the study PI. To understand how the health preferences are different/similar with each other, the following analyses were done: (1) the statistical difference between the coefficients; (2) the relative importance of the five EQ-5D dimensions; (3) the relative importance of the response levels. RESULTS: The number of statistically differed coefficients between two studies ranged from 2 to 16 (mean: 9.3), out of 20 main effects coefficients. For the relative importance, there is not a universal preference pattern that fits all studies, but with some common characteristics, e.g. mobility is considered the most important; the relative importance of levels are approximately 20% for level 2, 30% for level 3, 70% for level 4 for all studies. DISCUSSION: Following a standardized study protocol, there are still considerable differences in the modeling and relative importance results in the EQ-5D-5L DCE data among 11 Asian studies. These findings advocate the use of local value set for calculating health state utility.

Comparative effectiveness of smartphone healthcare applications for improving quality of life in lung cancer patients: study protocol.

BACKGROUND: Although pulmonary rehabilitation is helpful for patients following lung cancer surgery, rehabilitation is not widely available, due in part to a lack of medical resources. Recent developments in digital health care have overcome the space limitations associated with in-person health care. This study will evaluate and compare the efficacy of three different smartphone healthcare systems in patients with lung cancer. METHODS: This single center randomized controlled study is designed to evaluate the efficacy of digital healthcare applications for lung cancer patients after thoracoscopic lung resection. A total of 320 patients will be enrolled and randomized 1:1:1:1 into four different groups, with one group each using the smartphone applications NOOM, Walkon, and Efilcare and the fourth being the control group without intervention. Questionnaires will be administered to patients at baseline and after 3, 6, and 12 months. The primary endpoint will be the score on the EuroQol five-dimension index. Secondary endpoints will include other questionnaires about quality of life and dyspnea. DISCUSSION: This prospective randomized controlled study may allow assessments and comparisons of the efficacy of various smartphone applications in patients who undergo lung cancer surgery. This process may enable the introduction of healthcare interventions that maintain quality of life in patients with lung cancer. Trial registration CRIS, KCT0005447. Registered 06 October 2020, https://cris.nih.go.kr/cris/search/detailSearch.do/19346.

Cost analysis of coronavirus disease 2019 test strategies using pooled reverse transcriptase-polymerase chain reaction technique.

BACKGROUND: This study aimed to compare the testing strategies for COVID-19 (i.e., individual, simple pooling, and matrix pooling) in terms of cost. METHODS: We simulated the total expenditures of each testing strategy for running 10,000 tests. Three parameters were used: positive rate (PR), pool size, and test cost. We compared the total testing costs under two hypothetical scenarios in South Korea. We also simulated country-specific circumstances in India, South Africa, South Korea, the UK, and the USA. RESULTS: At extreme PRs of 0.01% and 10%, simple pooling was the most economic option and resulted in cost reductions of 98.0% (pool size ≥80) and 36.7% (pool size = 3), respectively. At moderate PRs of 0.1%, 1%, 2%, and 5%, the matrix pooling strategy was the most economic option and resulted in cost reductions of 97.0% (pool size ≥88), 86.1% (pool size = 22), 77.9% (pool size = 14), and 59.2% (pool size = 7), respectively. In both hypothetical scenarios of South Korea, simple pooling costs less than matrix pooling. However, the preferable options for achieving cost savings differed depending on each country's cost per test and PRs. CONCLUSIONS: Both pooling strategies resulted in notable cost reductions compared with individual testing in most scenarios pertinent to real-life situations. The appropriate type of testing strategy should be chosen by considering the PR of COVID-19 in the community and the test cost while using an appropriate pooling size such as five specimens.

Health gap for multimorbidity: comparison of models combining uniconditional health gap.

PURPOSE: The aim of this study is to identify the best-fitting model in predicting the health gap of multimorbid status based on the health gap of uniconditional status. METHODS: This study analyzed data of adults aged 50 years or older derived from the cross-sectional, nationally representative 6th Korean National Health and Nutrition Examination Survey (KNHANES). We translated the EQ-5D utility score assessed from the KNHANES using the Korean EQ-5D-3L into the health gap by subtracting the EQ-5D utility score from one. The predicted health gap of multimorbid status was calculated based on the health gap of uniconditional status using the additive, multiplicative, and maximum limit models. We assessed the performance of the multimorbidity adjustment models based on the root mean square error and mean absolute error. We also examined the impact of multimorbidity adjustment on the estimated disease burden in the best-fitting model. RESULTS: Of the three approaches, the multiplicative adjustment model had the smallest root mean square error between the predicted and observed health gap of multimorbid status. The total number of prevalence-based years lived with the disability after adjusting for multimorbid status using the multiplicative model decreased compared to that without adjustment for multimorbid status. CONCLUSION: Using the appropriate methodology to adjust for multimorbidity in estimations of population health is becoming more important as the prevalence of multimorbidity increases, particularly in older populations. Further empirical research is required to develop additional general adjustment approaches that consider the independent co-occurrence of multiple diseases, and to understand how multimorbidity influences health gap.

Estimation of population-based utility weights for health states of chronic kidney disease, dialysis and kidney transplantation.

AIM: This study aimed to determine the utility of chronic kidney disease (CKD)-related health states in the Korean general population by using the standard gamble (SG) method. METHODS: Seven hypothetical CKD-related health states were developed and revised based on previous publications. Data from 242 individuals from the Korean general population were obtained via computer-assisted personal interviews and used to evaluate the CKD-related health states by using the visual analogue scale (VAS) and SG methods. Mean and median utility values were calculated for each health state. To assess the reliability of the valuation, some samples were retested and evaluated using intraclass correlation coefficients (ICC). RESULTS: In all health states, the utility weights from SG were higher than those from VAS. The difference in utility values between the two valuation methods ranged from 0.258 to 0.308. The utility value of CKD grade 3 was the highest and that of peritoneal dialysis (PD) was the lowest. The utility weights tended to decrease in accordance with the progression of CKD. CKD grade 3 was assigned a SG utility value of 0.878, whereas PD was assigned 0.507. The SG utility values of predialysis end-stage renal disease, haemodialysis, kidney transplantation (KT), and post-KT recovery states were 0.666, 0.547, 0.748 and 0.827, respectively. The mean ICC (SD) at the individual level was 0.746 (0.281) for the SG scores. CONCLUSION: Our results could be used to measure the burden of kidney disease or to evaluate the economic efficiency of CKD-related interventions.

Updating Disability Weights for Measurement of Healthy Life Expectancy and Disability-adjusted Life Year in Korea.

BACKGROUND: The present study aimed to update the methodology to estimate cause-specific disability weight (DW) for the calculation of disability adjusted life year (DALY) and health-adjusted life expectancy (HALE) based on the opinion of medical professional experts. Furthermore, the study also aimed to compare and assess the size of DW according to two analytical methods and estimate the most valid DW from the perspective of years lost due to disability and HALE estimation. METHODS: A self-administered web-based survey was conducted ranking five causes of disease. A total of 901 participants started the survey and response data of 806 participants were used in the analyses. In the process of rescaling predicted probability to DW on a scale from 0 to 1, two models were used for two groups: Group 1 (physicians and medical students) and Group 2 (nurses and oriental medical doctors). In Model 1, predicted probabilities were rescaled according to the normal distribution of DWs. In Model 2, the natural logarithms of predicted probabilities were rescaled according to the asymmetric distribution of DWs. RESULTS: We estimated DWs for a total of 313 causes of disease in each model and group. The mean of DWs according to the models in each group was 0.490 (Model 1 in Group 1), 0.378 (Model 2 in Group 1), 0.506 (Model 1 in Group 2), and 0.459 (Model 2 in Group 2), respectively. About two-thirds of the causes of disease had DWs of 0.2 to 0.4 in Model 2 in Group 1. In Group 2, but not in Group 1, there were some cases where the DWs had a reversed order of severity. CONCLUSION: We attempted to calculate DWs of 313 causes of disease based on the opinions of various types of medical professionals using the previous analysis methods as well as the revised analysis method. The DWs from this study can be used to accurately estimate DALY and health life expectancy, such as HALE, in the Korean population.

Years of Life Lost Attributable to COVID-19 in High-incidence Countries.

BACKGROUND: The coronavirus disease 2019 (COVID-19) pandemic is a major public health problem of international concern. It is important to estimate its impact of COVID-19 for health policy decision-making. We estimated the years of life lost (YLLs) due to COVID-19 in high-incidence countries. METHODS: We collected the YLLs due to COVID-19 in 30 high-incidence countries as of April 13, 2020 and followed up as of July 14, 2020. Incidence and mortality were collected using each country's formal reports, articles, and other electronic sources. The life expectancy of Japanese females by age and the UN population data were used to calculate YLLs in total and per 100,000. RESULTS: As of April 22, 2020, there were 1,699,574 YLLs due to COVID-19 in 30 high-incidence countries. On July 14, 2020, this increased to 4,072,325. Both on April 22 and July 14, the total YLLs due to COVID-19 was highest in the USA (April 22, 534,481 YLLs; July 14, 1,199,510 YLLs), and the YLLs per 100,000 population was highest in Belgium (April 22, 868.12 YLLs/100,000; July 14, 1,593.72 YLLs/100,000). YLLs due to COVID-19 were higher among males than among females and higher in those aged ≥ 60 years than in younger individuals. Belgium had the highest proportion of YLLs attributable to COVID-19 as a proportion of the total YLLs and the highest disability-adjusted life years per 100,000 population. CONCLUSION: This study estimated YLLs due to COVID-19 in 30 countries. COVID-19 is a high burden in the USA and Belgium, among males and the elderly. The YLLs are very closely related with the incidence as well as the mortality. This highlights the importance of the early detection of incident case that minimizes severe acute respiratory syndrome coronavirus-2 fatality.

The Burden of Disease due to COVID-19 in Korea Using Disability-Adjusted Life Years.

BACKGROUND: The world is currently experiencing a pandemic of coronavirus disease 2019 (COVID-19). In Korea, as in other countries, the number of confirmed cases and deaths due to COVID-19 have been rising. This study aimed to calculate the burden of disease due to COVID-19 in Korea. METHODS: We used data on confirmed cases and deaths due to COVID-19 between January 20 and April 24, 2020 provided by the Korea Centers for Disease Control and Prevention, the local governments and the public media to determine disability-adjusted life years (DALYs) by sex and age. Morbidity was estimated directly among the confirmed, cured, and fatal cases. Disability weights were adopted from previous similar causes on the severity of COVID-19 for the years of life lived with disability (YLDs). The years of life lost (YLLs) were calculated using the standard life expectancy from the 2018 life tables for each sex and age. RESULTS: The YLDs were higher in females (155.2) than in males (105.1), but the YLLs were higher in males (1,274.3) than in females (996.4). The total disease burden attributable to COVID-19 in Korea during the study period, was estimated to be 2,531.0 DALYs, and 4.930 DALYs per 100,000 population. The YLDs and the YLLs constituted 10.3% and 89.7% of the total DALYs, respectively. The DALYs per 100,000 population were highest in people aged ≥ 80 years, followed by those aged 70-79, 60-69, and 50-59 years, but the incidence was the highest in individuals aged 20-29 years. CONCLUSION: This study provided the estimates of DALYs due to COVID-19 in Korea. Most of the disease burden from COVID-19 was derived from YLL; this indicates that decision-makers should focus and make an effort on reducing fatality for preparing the second wave of COVID-19.

Cost-utility analysis of the National Health Screening Program for chronic kidney disease in Korea.

AIM: Although a National Health Screening Program (NHSP) for chronic kidney disease (CKD) has been implemented in Korea since 2002, its cost-effectiveness has never been determined. This study aimed to estimate the cost-utility of NHSP for CKD in Korea. METHODS: A Markov decision analytic model was constructed to compare CKD screening strategies of the NHSP with no screening. We developed a model that simulated disease progression in a cohort aged 20-120 years or death from the societal perspective. RESULTS: Biannual screening starting at age 40 for CKD by proteinuria (dipstick) and estimated glomerular filtration ratio had an ICUR of $66 874/QALY relative to no screening. The targeted screening strategy had an ICUR of $37 812/QALY and $40 787/QALY for persons with diabetes and hypertension, respectively. ICURs improved with lower cost strategies. The most influential parameter that might make screening more cost-effective was the effectiveness of treatment on CKD to decrease disease progression and mortality. CONCLUSIONS: The Korean NHSP for CKD is more cost-effective for patients with diabetes or hypertension than the general population, consistent with prior studies. Although it is too early to conclude the cost-effectiveness of the Korean NHSP for CKD, this study provides evidence that is useful in evaluating the cost-effectiveness of CKD interventions.

The Trends in Health Life Expectancy in Korea according to Age, Gender, Education Level, and Subregion: Using Quality-Adjusted Life Expectancy Method.

BACKGROUND: Quality-adjusted life expectancy (QALE) means life expectancy (LE) reflecting health-related quality of life and is one of the indicators of healthy LE. We determined the trends in QALE in Korea by age, gender, educational level, and subregion from 2005 to 2013. METHODS: We applied the Sullivan method to estimate QALE. We calculated QALE from 2005 to 2013 by gender and QALE for 2005 and 2010 by educational level at the national level. Furthermore, we estimated QALE for 2005, 2008, and 2011 by subregion according to metropolitan and provincial levels. RESULTS: Population health in Korea measured by LE and QALE at age 0 increased steadily from 2005 to 2013. Annual percent changes of LE and QALE in men were 0.52 and 0.73, respectively (P value < 0.05), and those in women were 0.47 and 0.71, respectively (P value < 0.05). Koreans with a higher educational level had longer LE and QALE than those with a lower educational level, but the differences in LE and QALE according to educational level narrowed from 2005 to 2010. The LE and QALE at age 0 for each of the 16 subnational regions in 2011 increased compared to 2005, but there was still a difference of up to 4.57 years in QALE between subnational regions. CONCLUSION: We showed that QALE could be easily calculated and be an appropriate measure for tracking the overall population's health level. The results from this study are expected to aid the Ministry of Health of Republic of Korea in setting up a goal for the National Health Plan.

Estimating Lifetime Duration of Diabetes by Age and Gender in the Korean Population Using a Markov Model.

BACKGROUND: Duration of type 2 diabetes is clinically important. Duration of morbidity is an independent and critical predictor of developing its complications. This study aims to explore an applicability of a Markov model to estimate the duration of diabetes in the Korean population. METHODS: We constructed the Markov model with two Markov states, diabetes and death, for estimation of duration of diabetes. The cycle of the Markov model was 1 year. Each diabetes onset by 5 years was considered from 30 to 85 years old or above. The endpoint of the Markov was 100 years old. Type 2 diabetes was operationally defined using the 10th revision of International Statistical Classification of Diseases and prescriptions of anti-diabetic drugs from the National Health Insurance Services-National Sample cohort. In each incident and existing prevalence cases, survival probabilities were obtained. Durations of diabetes from the Markov model were compared with those from the DisMod II program. Reductions of life expectancy due to diabetes were defined as differences of life expectancies between diabetic patients and the general public. Sensitivity analyses were also conducted using a cure rate and 95% confidence interval of survival probability. RESULTS: The duration of diabetes gradually decreased with incident age in both genders. In the early 30s, the duration was the largest at 48.9 and 41.9 years in women and men, respectively. In the average incident age group of type 2 diabetes, the late 50s, the reduction of life expectancy due to diabetes was estimated to be about two years in both genders. As annual cure probabilities increased, the durations of diabetes were reduced. CONCLUSION: This study estimated the duration of diabetes using a Markov model. The model seems to work well and diabetes could reduce life expectancy by about 2 years on average. This approach could be useful to estimate the duration of illness, calculate disability-adjusted life years, and conduct economic evaluation studies on interventions for diabetic patients.

Comparative Research for the Healthcare Budget and Burden of Disease in Perspective Resource Allocation.

BACKGROUND: Burden of disease can be used to prioritize the healthcare budget allocation. We analyzed the research and development (R&D) budget of the Ministry of Health and Welfare (MOHW) in 2018 and compared the results with those of the 2015 Korean National Burden of Disease (KNBD) study. METHODS: The 2018 MOHW R&D Project integrated implementation plan was used to analyze the R&D budget of the MOHW. The budget was allocated according to the KNBD disease group and according to the budget lines. The allocated budget was compared with the economic burden and the disability adjusted life years (DALYs) in 2015. Also, for budget targets for risk factors, DALYs of attributable risk factors were compared with corresponding budgets. RESULTS: In 2018, the MOHW major R&D budget of USD 435.1 million accounted for 3% of the total government budget. Within the disease specific R&D budget, 35.9% was allocated to communicable disease groups, 64.1% to non-communicable diseases, and 0% to injury and violence. Among level 2 disease groups, neoplasm was ranked first. Among risk factors, climate change and behavioral risk were targeted for R&D. CONCLUSIONS: It would be difficult to say that current R&D allocations focus to minimize the burden of disease. A mismatch was observed between the R&D budget and the burden of disease in terms of economic burden and DALYs. There was a similar finding for risk factors R&D. A novel approach for allocating government R&D funding that is based on the goal of minimizing the disease burden in the Korean population should be considered.

Disability Weights Measurement for 289 Causes of Disease Considering Disease Severity in Korea.

BACKGROUND: For the Korean Burden of Disease (KBD) 2015 study, we have amended disability weights for causes of disease adapting the methodology of the KBD disability weight 2012 study. METHODS: We conducted a self-administered web-based survey in Korea using ranking five causes of disease. A total of 605 physicians and medical college students who were attending in third or fourth grade of a regular course performed the survey. We converted the ranked data into paired comparison data and ran a probit regression. The predicted probabilities for each cause of disease were calculated from the coefficient estimates of the probit regression. 'Being dead (1)' and 'Full health (0)' were utilized as anchor points to rescale the predicted probability on a scale from 0 to 1. RESULTS: As a result, disability weights for a total of 289 causes of disease were estimated. In particular, we calculated the disability weights of 60 causes of disease considering severity level. These results show that prejudice about the severity of cause of disease itself can affect the estimation of disability weight, when estimating the disability weight for causes of disease without consideration of severity. Furthermore, we have shown that disability weights can be estimated based on a ranking method which can maximize efficiency of data collection. CONCLUSION: Disability weights from this study can be used to estimate disability adjusted life year and healthy life expectancy. Furthermore, we expected that the use of the ranking method will increase gradually in disability weight studies.

Trends and Patterns of Burden of Disease and Injuries in Korea Using Disability-Adjusted Life Years.

BACKGROUND: It is extremely important to objectively take a view of population health to provide useful information to decision makers, health-sector leaders, researchers, and informed citizens. This study aims to examine the burden of disease in Korea as of 2015, and to study how the burden of disease changes with the passage of time. METHODS: We used results from the Korean National Burden of Disease and Injuries Study 2015 for all-cause mortality, cause-specific mortality, and non-fatal disease burden to derive disability-adjusted life years (DALYs) by gender and age groups from 2007 to 2015. DALYs were calculated as the sum of the years of life lost (YLLs) and the years lived with disability (YLDs). RESULTS: In 2015, the burden of disease for Korean people was calculated at 29,476 DALYs per 100,000 population. DALYs caused by low back pain were the highest, followed by diabetes mellitus and chronic obstructive pulmonary disease. The burden of disease showed a consistently increasing trend from 2007 to 2015. Although YLLs have been on the decrease since 2011, the increase in YLDs has contributed to the overall rise in DALYs. The DALYs per 100,000 population in 2015 increased by 28.1% compared to 2007. CONCLUSION: As for the diseases for which the burden of disease is substantially increasing, it is needed to establish appropriate policies in a timely manner. The results of this study are expected to be the basis for prioritizing public health and health care policies in Korea.

Measuring the Economic Burden of Disease and Injury in Korea, 2015.

BACKGROUND: Disease burden can be represented by health-related parameters such as disability-adjusted life years and economic burden. Economic burden is an important index, as it estimates the maximum possible cost reduction if a disease is prevented. This study aimed to determine the economic burden of 238 diseases and 22 injuries in Korea in 2015. METHODS: Economic burden was estimated with a human resources approach from a social perspective, and direct and indirect costs were calculated from insurance claims data and a cause of death database. Direct costs were divided into medical costs (including hospital admission, outpatient visit, and medication use) and nonmedical costs (including transportation and caregiver costs). Indirect costs from lost productivity, either from the use of healthcare service or premature death, were analyzed. RESULTS: In 2015, the estimated economic burden was USD 133.7 billion (direct: USD 65.5 billion, indirect: USD 68.2 billion). The total cost of communicable diseases was USD 16.0 billion (11.9%); non-communicable diseases, USD 92.3 billion (69.1%); and injuries, USD 25.4 billion (19.0%). Self-harm had the highest costs (USD 8.3 billion), followed by low back pain (LBP, USD 6.6 billion). For men, self-harm had the highest cost (USD 7.1 billion), while LBP was the leading cost (USD 3.7 billion) for women. CONCLUSION: A high percentage of Korea's total socioeconomic disease burden is due to chronic diseases; however, unnoticed conditions such as infectious diseases, injuries, and LBP are high in certain age groups and differ by gender, emphasizing the need for targeted social interventions to manage and prevent disease risk factors.

The Korean National Burden of Disease Study: from Evidence to Policy.

Following the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD), disability-adjusted life years (DALYs) have been widely used as a summary measure of population health. The DALY metric is a comprehensive measurement of population health, enabling comparison among groups. However, the available data and reliance on estimates to supplement the data gap require contextualization at the national level, and the outcomes of which are more appropriate for national policymakers. The Korean National Burden of Disease (KNBD) study was initiated by the Research and Development Project of the Ministry of Health and Welfare, funded by a 5-year grant from 2013, to contextualize the GBD method to the Korean population. Here, we provide a comprehensive overview of the KNBD study with its achievements and challenges and discuss the implications for public health policies.