BACKGROUND: The purpose of this study is to estimate empirically whether there is a difference in medical use among income groups, and if so, how much. This study applies econometric model to the most recent year of Korean Medical Panel, 2015. The model consists of outpatient service and inpatient service models. METHODS: The probit model is applied to the model which indicate whether or not the medical care has been used. Two step estimation method using maximum likelihood estimation is applied to the models of outpatient visits, hospital days, and outpatient and inpatient out-of-pocket cost models, with disconnected selection problems. RESULTS: The results show that there was the inequality favorable to the low income group in medical care use. However, after controlling basic medical needs, there were no inequities among income groups in the outpatient visit model and the model of probability of inpatient service use. However, there were inequities favorable to the upper income groups in the models of probability of outpatient service use and outpatient out-of-pocket cost and the models of the number of length of stay and inpatient out-of-pocket cost. In particular, it shows clearly how the difference in outpatient service and inpatient service utilizations by income groups when basic medical needs are controlled. CONCLUSION: This means that the income contributes significantly to the degree of inequality in outpatient and inpatient care services. Therefore, the existence of medical care use difference under the same medical needs among income groups is a problem in terms of equity of medical care use, so great efforts should be made to establish policies to improve equity among income groups.
Health Expenditures ; Humans ; Inpatients ; Korea ; Length of Stay ; Methods ; Models, Econometric ; Outpatients ; Socioeconomic Factors

Analysis and prediction of the care charges related to colorectal cancer in Korea are important for the allocation of medical resources and the establishment of medical policies because the incidence and the hospital charges for colorectal cancer are rapidly increasing. But the previous studies based on statistical analysis to predictthe hospital charges for patients did not show satisfactory results. Recently, data mining emerges as a new technique to extract knowledge from the huge and diverse medical data. Thus, we built models using data mining techniques to predict hospital charge for the patients. A total of 1,022 admission records with 154 variables of 492 patients were used to build prediction models who had been treated from 1999 to 2002 in the Kyung Hee University Hospital. We built an artificial neural network (ANN) model and a classification and regression tree (CART) model, and compared their prediction accuracy. Linear correlation coefficients were high in both models and the mean absolute errors were similar. But ANN models showed a better linear correlation than CART model (0.813 vs. 0.713 for the hospital charge paid by insurance and 0.746 vs. 0.720 for the hospital charge paid by patients). We suggest that ANN model has a better performance to predict charges of colorectal cancer patients.
Algorithms ; Colorectal Neoplasms/*economics/epidemiology ; Comparative Study ; *Decision Trees ; *Hospital Charges ; Humans ; Incidence ; Korea/epidemiology ; *Models, Econometric ; *Neural Networks (Computer) ; Predictive Value of Tests

OBJECTIVES: The purpose of this study was to determine the population-attributable risk (PAR) and estimate the total medical expenditure of the Korean National Health Insurance (KNHI) due to smoking. METHODS: We used data from the Korean Cancer Prevention Study of 1,178,138 Koreans aged 30 to 95. These data were available from 1992 to 2003 and covered a long-term follow-up period among the Korean population. RESULTS: The total medical expenditure of KNHI related to smoking increased by 27% from $324.9 million in 1999 to $413.7 million in 2003. By specific diseases, smokingattributable KNHI medical expenditure was the highest for lung cancer ($74.2 million), followed by stroke ($65.3 million), COPD ($50.1 million), CHD ($49 million) and stomach cancer ($30 million). A total of 1.3 million KNHI patients were suffering from smoking-related diseases in 2003. We predicted rises in total KNHI medical expenditure related to smoking to $675.1 million (63% increase compared with that of 2003) and in the total number of KNHI patients suffering from smoking-related diseases to about 2.6million (an approximate 100% increase compared with those in 2003) in 2015. CONCLUSIONS: We found a substantial economic burden related to the high smoking prevalence in South Korea.
Adult ; Aged ; Aged, 80 and over ; Female ; *Health Expenditures ; Humans ; Korea/epidemiology ; Male ; Middle Aged ; Models, Econometric ; National Health Programs/*economics ; Risk ; Smoking/adverse effects/*economics