• Journal of Preventive Medicine and Public Health
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• 제38권2호
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• pp.132-140
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• 2005

Objectives: To propose a risk-adjustment model from insurance claims data, and analyze the changes in cesarean section rates of healthcare organizations after adjusting for risk distribution. Methods: The study sample included delivery claims data from January to September, 2003. A risk-adjustment model was built using the 1st quarter data, and the 2nd and 3rd quarter data were used for a validation test. Patients' risk factors were adjusted using a logistic regression analysis. The c-statistic and Hosmer-Lemeshow test were used to evaluate the performance of the risk-adjustment model. Crude, predicted and risk-adjusted rates were calculated, and compared to analyze the effects of the adjustment. Results: Nine risk factors (malpresentation, eclampsia, malignancy, multiple pregnancies, problems in the placenta, previous Cesarean section, older mothers, bleeding and diabetes) were included in the final risk-adjustment model, and were found to have statistically significant effects on the mode of delivery. The c-statistic (0.78) and Hosmer-Lemeshow test ($x^2$=0.60, p=0.439) indicated a good model performance. After applying the 2nd and 3rd quarter data to the model, there were no differences in the c-statistic and Hosmer-Lemeshow $x^2$. Also, risk factor adjustment led to changes in the ranking of hospital Cesarean section rates, especially in tertiary and general hospitals. Conclusion: This study showed a model performance, using medical record abstracted data, was comparable to the results of previous studies. Insurance claims data can be used for identifying areas where risk factors should be adjusted. The changes in the ranking of hospital Cesarean section rates implied that crude rates can mislead people and therefore, the risk should be adjusted before the rates are released to the public. The proposed risk-adjustment model can be applied for the fair comparisons of the rates between hospitals.

• 보건행정학회지
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• 제26권4호
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• pp.359-372
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• 2016

Background: The purpose of this study was to develop risk-adjustment models for acute stroke mortality that were based on data from Health Insurance Review and Assessment Service (HIRA) dataset and to evaluate the validity of these models for comparing hospital performance. Methods: We identified prognostic factors of acute stroke mortality through literature review. On the basis of the avaliable data, the following factors was included in risk adjustment models: age, sex, stroke subtype, stroke severity, and comorbid conditions. Survey data in 2014 was used for development and 2012 dataset was analysed for validation. Prediction models of acute stroke mortality by stroke type were developed using logistic regression. Model performance was evaluated using C-statistics, $R^2$ values, and Hosmer-Lemeshow goodness-of-fit statistics. Results: We excluded some of the clinical factors such as mental status, vital sign, and lab finding from risk adjustment model because there is no avaliable data. The ischemic stroke model with age, sex, and stroke severity (categorical) showed good performance (C-statistic=0.881, Hosmer-Lemeshow test p=0.371). The hemorrhagic stroke model with age, sex, stroke subtype, and stroke severity (categorical) also showed good performance (C-statistic=0.867, Hosmer-Lemeshow test p=0.850). Conclusion: Among risk adjustment models we recommend the model including age, sex, stroke severity, and stroke subtype for HIRA assessment. However, this model may be inappropriate for comparing hospital performance due to several methodological weaknesses such as lack of clinical information, variations across hospitals in the coding of comorbidities, inability to discriminate between comorbidity and complication, missing of stroke severity, and small case number of hospitals. Therefore, further studies are needed to enhance the validity of the risk adjustment model of acute stroke mortality.

• Journal of Preventive Medicine and Public Health
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• 제39권1호
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• pp.13-20
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• 2006

Objectives: To propose a risk-adjustment model with using insurance claims data and to analyze whether or not the outcomes of non-emergent and isolated coronary artery bypass graft surgery (CABG) differed between the low- and high-volume hospitals for the patients who are at different levels of surgical risk. Methods: This is a cross-sectional study that used the 2002 data of the national health insurance claims. The study data set included the patient level data as well as all the ICD-10 diagnosis and procedure codes that were recorded in the claims. The patient's biological, admission and comorbidity information were used in the risk-adjustment model. The risk factors were adjusted with the logistic regression model. The subjects were classified into five groups based on the predicted surgical risk: minimal (<0.5%), low (0.5% to 2%), moderate (2% to 5%), high (5% to 20%), and severe (=20%). The differences between the low- and high-volume hospitals were assessed in each of the five risk groups. Results: The final risk-adjustment model consisted of ten risk factors and these factors were found to have statistically significant effects on patient mortality. The C-statistic (0.83) and Hosmer-Lemeshow test ($x^2=6.92$, p=0.55) showed that the model's performance was good. A total of 30 low-volume hospitals (971 patients) and 4 high-volume hospitals (1,087 patients) were identified. Significant differences for the in-hospital mortality were found between the low- and high-volume hospitals for the high (21.6% vs. 7.2%, p=0.00) and severe (44.4% vs. 11.8%, p=0.00) risk patient groups. Conclusions: Good model performance showed that insurance claims data can be used for comparing hospital mortality after adjusting for the patients' risk. Negative correlation was existed between surgery volume and in-hospital mortality. However, only patients in high and severe risk groups had such a relationship.

• 대한가정학회지
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• 제38권12호
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• pp.145-158
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• 2000

The purpose of this study was to examine the relative importance of parental expectations to adolescents'psychological, behavioral, school-based adjustment, and academic achievement. Subjects of this study consisted of 359 adolescents(177 boys and 182 girls) in Cheong-ju City. There was a statistically meaningful difference in the effect of parental expectations of academic performance on adolescents'adjustment according to sex of adolescents'. Maternal pressure, support form mothers, and paternal pressure were significant factors predicting adolescents'relative psychological adjustment and academic achievement. Support and pressure from mothers were associated with adolescents'behavioral adjustment. The research suggest that maternal pressure was the strongest risk factors in relation to the effects of parental expectations of academic performance on adolescents'adjustment.

• Journal of Preventive Medicine and Public Health
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• 제34권4호
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• pp.337-346
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• 2001

Objective : To determine the clinical risk factors associated with the mode of delivery decision and to compare cesarean section rates after adjusting for risk factors identified among Korean hospitals. Methods Data were collected from 9 general hospitals in two provincial regions by medical record abstraction during February 2000. A total of 3,467 cases were enrolled and analyzed by stepwise logistic regression. Performance of the risk-adjustment model (discrimination and calibration) was evaluated by the C statistic and the Hosmer-Lemeshow test. Crude rates, predicted rates with 95% confidence intervals, and adjusted rates of cesarean section were calculated and compared among the hospitals. Results : The average crude cesarean section rate was 53.2%, ranging from 39.4% to 65.7%. Several risk factors such as maternal age, previous history of cesarean section, placenta previa, placental abruption, malpresentation, amniotic fluid abnormality, gestational anemia, infant body weight, pregnancy-induced hypertension, and chorioamnionitis were found to have statistically significant effects on the mode of delivery. It was confirmed that information about most of these risk factors was able to be collected through the national health insurance claims database in Korea. Performance of the risk-adjustment model was good (c statistic=0.815, Hosmer-Lemeshow test=0.0621). Risk factor adjustment did lead to some change in the rank of hospital cesarean section rates. The crude rates of three hospitals were beyond 95% confidence intervals of the predicted rates. Conclusions : Considering that cesarean section rates in Korean hospitals are too high, it is apparent that some policy interventions need to be introduced. The concept and methodology of risk adjustment should be used in the process of health policy development to lower the cesarean section rate in Korea.

• 아동학회지
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• 제31권1호
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• pp.65-82
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• 2010

This study investigated the longitudinal effects of family risk factors, parent-child relationships, and language abilities of children in low-income families in terms of both school adjustment and academic performance. The subjects were 176 children aged 5 to 7 and their mothers. They participated in follow up studies over the next 3 years. The children were tested using the Wechsler Intelligence Scales and language tests; and classroom teachers rated their levels of both school adjustment and academic performance. Mothers reported parent-child relationships, maternal depression, and family economic resources. Data were analyzed using Pearson's correlation, and structural equation modeling (SEM). Our results indicated that there were direct effects of language abilities, and indirect effects of parent-child relationships and maternal depression upon children's school adjustment and academic performance. It was also revealed that language abilities had a mediating effect between parent-child relationship and school adjustment/ academic performance.

• 한국경제지리학회지
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• 제12권4호
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• pp.665-680
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• 2009

본 연구의 목적은 위험조정모형을 활용하여 미국 REITs의 부동산 유형별 성과 특성을 분석하는 것이다. 특히, REITs의 성과가 성장기, 정체기, 금융위기기에 각각 어떻게 차별적인 지를 살펴본다. 분석결과를 요약하면 다음과 같다. 첫째로, 초과 종합수익률의 관점에서 REITs 부동산 유형별 성과를 보면, 1기와 2기에는 정(+)의 초과 성과가 발생한 반면, 3기에는 부(-)의 초과 성과가 나타난다. 금융위기 시기인 3기의 경우, 부(-)의 수익률이 발생한 뿐만 아니라 수익률의 변동성도 큰 것으로 나타난다. 둘째로, 자본자산가격결정모형에 의해 추정한 베타값을 보면, <분석모형 (1)>의 결과에서 평균적인 REITs에 비해 호텔, 지역몰, 상업모기지는 고위험-고수익 특성을, 자유입지, 아파트, 조립식주택, 특수목적 부동산은 저위험-저수익 특성을 가진 것으로 나타난다. <분석모형 (2)>의 결과를 보면, 금융위기 하에서 투자상품으로서의 REITs의 성격이 저위험-저수익에서 고위험-고수익으로 변화하고 있다. 마지막으로, 위험조정모형 추정결과를 보면, <분석모형 (1)>과 <분석모형 (2)> 모두 체계적 위험은 요구수익률에 정(+)의 영향을 미치는 반면, 비체계적위험은 요구수익률에 부(-)의 영향을 미치는 것으로 나타난다. 위험조정모형을 통해 도출된 요구수익률을 실제수익률과 비교한 결과, 헬쓰케어 부문이 가장 높은 정(+)의 성과를 보이고 있다.

• 보건행정학회지
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• 제17권3호
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• pp.87-105
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• 2007

The purpose of this study was to analyze whether nonemergency, isolated coronary artery bypass graft (CABG) surgery for high- or low-risk patients biases the assessment of the risk-adjusted mortality rates of hospitals. This study used 2002 National Health Insurance claims data for tertiary hospitals in Korea. The study sample consisted of 1,959 patients from 23 tertiary hospitals. The risk-adjustment model used the patients' biological, admission, and comorbidity data identified in the claims. The subjects were classified into high- and low-risk groups based on predicted surgical risk. The crude mortality rates and risk-adjusted mortality rates for low-risk, high-risk, and all patients in a hospital were compared based on the rank and the four intervals defined by quartile. Also, the crude mortality rates of the three groups were compared with their 95% confidence intervals of predicted mortality rates. The C-statistic (0.83) and Hosmer-Lemeshow test ($X^2$=11.47, p=0.18) indicated that the risk-adjustment model performed well. Presenting crude mortality rates with their 95% confidence intervals of predicted rates showed higher agreements among the three groups than using the rank or intervals of mortality rates defined by quartile in the hospital performance assessment. The crude mortality rates for the low-risk patients in 21 of the 23 hospitals were located on the same side of their 95% confidence intervals compared to that for all patients. High-risk patients and all patients differed at only one hospital. In conclusion, the impact of risk selection by hospital on the assessment results was the smallest when comparing the crude inpatient mortality rates of CABG patients with the 95% confidence intervals of predicted mortality rates. Given the increasing importance of quality improvements in Korean health policy, it will be necessary to use the appropriate method of releasing the hospital performance data to the public to minimize any unwanted impact such as risk-based hospital selection.

• 보건행정학회지
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• 제27권2호
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• pp.149-156
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• 2017

Background: This study was conducted to evaluate the performance of the Hierarchical Condition Category (HCC) model, identify potentially high-cost patients, and examine the effects of adding prior utilization to the risk model using Korean claims data. Methods: We incorporated 2 years of data from the National Health Insurance Services-National Sample Cohort. Five risk models were used to predict health expenditures: model 1 (age/sex groups), model 2 (the Center for Medicare and Medicaid Services-HCC with age/sex groups), model 3 (selected 54 HCCs with age/sex groups), model 4 (bed-days of care plus model 3), and model 5 (medication-days plus model 3). We evaluated model performance using $R^2$ at individual level, predictive positive value (PPV) of the top 5% of high-cost patients, and predictive ratio (PR) within subgroups. Results: The suitability of the model, including prior use, bed-days, and medication-days, was better than other models. $R^2$ values were 8%, 39%, 37%, 43%, and 57% with model 1, 2, 3, 4, and 5, respectively. After being removed the extreme values, the corresponding $R^2$ values were slightly improved in all models. PPVs were 16.4%, 25.2%, 25.1%, 33.8%, and 53.8%. Total expenditure was underpredicted for the highest expenditure group and overpredicted for the four other groups. PR had a tendency to decrease from younger group to older group in both female and male. Conclusion: The risk adjustment models are important in plan payment, reimbursement, profiling, and research. Combined prior use and diagnostic data are more powerful to predict health costs and to identify high-cost patients.

• 한국경제지리학회지
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• 제10권3호
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• pp.245-262
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• 2007

본 연구는 호주의 LPT(Listed Property Trusts)의 성과 분석을 통해 펀드형 부동산 간접투자상품으로서 LPT의 성과와 특성을 분석하고, LPT 성과에 영향을 미치는 LPT의 자산관리 특성을 분석하여, 우리나라 부동산 간접투자제도의 발전을 위한 시사점을 도출하는 것을 목적으로 한다. 연구결과를 요약하면 다음과 같다. LPT는 1971년 최초로 설립된 이후 빠른 성장을 통해 호주의 대표적인 부동산간접투자제도의 지위를 차지하고 있다. LPT 성과 특성을 보면, LPT는 명목수익률 및 위험조정수익률의 관점에서 여타 금융상품에 비해 우월한 성과를 보이고 있으며, LPT를 영입함으로 복합자산 포트폴리오 다변화 효과를 누릴 수 있음을 확인하였다. 또한, LPT는 자산관리 방안으로 결합주식 구조를 활용하고 있는데, 결합주식 구조를 활용하는 LPT가 비결합 LPT보다 우수한 성과를 보이고 있으며, 결합주식 LPT의 포트폴리오 다변화 효과도 더 뛰어나, 결합주식 구조는 LPT가 고도 성장을 하는데 중요한 요인으로 작용하고 있음을 확인하였다. 마지막으로, 이러한 연구결과를 통해 LPT의 결합주식 구조를 우리나라 부동산투자회사 제도에 활용하는 방안, 개발사업의 활성화를 위한 LPT의 사례를 적용하는 방안 등을 모색하였다.