- Disability Weights for the Korean Burden of Disease Study: Focused on Comparison with Disability Weights in the Australian Burden of Disease Study.
-
Young Kyung Do, Seok Jun Yoon, Jung Kyu Lee, Young Hoon Kwon, Sang Il Lee, Changyup Kim, Kidong Park, Yong Ik Kim, Youngsoo Shin
-
J Prev Med Public Health. 2004;37(1):59-71.
-
-
-
 Abstract
 PDF
- OBJECTIVE
This study aimed to measure the disability weights for the Korean Burden of Disease study, and to compare them with those adopted in the Australian study to examine the validity and describe the distinctive features. METHODS: The standardized valuation protocol was developed from the Global Burden of Disease (GBD) study and the Dutch Disability Weights study. Disability weights were measured for 123 diseases of the Korean version of Disease Classification by three panels of 10 medical doctors each. Then, overall distribution, correlation coefficients, difference by each disease, and mean of differences by disease group were analyzed for comparison of disability weights between the Korean and Australian studies. RESULTS: Korean disability weights ranged from 0.037 to 0.927. While the rank correlation coefficient was moderate to high (rs=0.68), Korean disability weights were higher than the corresponding Australian ones in 79.7% of the 118 diseases. Of these, war, leprosy, and most injuries showed the biggest differences. On the contrary, many infectious and parasitic diseases comprised the greater part of diseases of which Korean disability weights were lower. The mean of the differences was the highest in injuries of GBD disease groups, and in cardiovascular disease, injuries, and malignant neoplasm of the Korean disease category. CONCLUSION: Korean disability weights were found to be valid on the basis of overall distribution pattern and correlation, and are expected to be used as basic data for broadening the scope of burden of disease study. However, some distinctive features still remain to be explored in following studies.
-
Summary
- Disability Weights for Diseases in Korea.
-
Jung Kyu Lee, Seok Jun Yoon, Young Kyung Do, Young Hoon Kwon, Chang Yup Kim, Kidong Park, Yong Ik Kim, Young Soo Shin
-
Korean J Prev Med. 2003;36(2):163-170.
-
-
-
Abstract
PDF
- OBJECTIVES
This study aimed to develop an evaluation protocol of disability weights using person trade-off, and to test the reliability of the developed protocol in a Korean context. METHODS: To develop the valuation protocol, the Global Burden of Disease (GBD) and the Dutch studies were replicated and modified. Sixteen indicator conditions were selected from the Korean version of disease classification, which was based on that of the GBD Study, and the person trade-off method referred to the Dutch method. RESULTS: The disability weights were valued in a two step panel study. The first step was a carefully designed group process by three panels, using person trade-off to establish the disability weights for sixteen selected indicator conditions. The second step consisted of interpolation of the remaining diseases, on a disability scale, by the individual members of three panels. The members of three panels were all medical doctors, with sufficient knowledge of the consequences of a broad variety of diseases. The internal consistency of the Korean disability weights was satisfactory. Considerable agreement existed within each panel and among the panels. CONCLUSIONS: It was feasible to use a modified evaluation protocol from those used in GBD and Dutch studies. This would provide a rational basis for an international comparative study of disability weights.
-
Summary
- Efficient DRG Fraud Candidate Detection Method Using Data Mining Techniques.
-
Duho Hong, Jung Kyu Lee, Min Woo Jo, Kidong Park, Sang Il Lee, Moo Song Lee, Chang Yup Kim, Yong Ik Kim
-
Korean J Prev Med. 2003;36(2):147-152.
-
-
-
Abstract
PDF
- OBJECTIVES
To develop a Diagnosis-Related Group (DRG) fraud candidate detection method, using data mining techniques, and to examine the efficiency of the developed method. METHODS: The study included 79, 790 DRGs and their related claims of 8 disease groups (Lens procedures, with or without, vitrectomy, tonsillectomy and/or adenoidectomy only, appendectomy, Cesarean section, vaginal delivery, anal and/or perianal procedures, inguinal and/or femoral hernia procedures, uterine and/or adnexa procedures for nonmalignancy), which were examined manually during a 32 months period. To construct an optimal prediction model, 38 variables were applied, and the correction rate and lift value of 3 models (decision tree, logistic regression, neural network) compared. The analyses were performed separately by disease group. RESULTS: The correction rates of the developed method, using data mining techniques, were 15.4 to 81.9%, according to disease groups, with an overall correction rate of 60.7%. The lift values were 1.9 to 7.3 according to disease groups, with an overall lift value of 4.1. CONCLUSIONS: The above findings suggested that the applying of data mining techniques is necessary to improve the efficiency of DRG fraud candidate detection.
-
Summary
|
KSPM
