The Analysis Of Hospitalization Costs And The Study Of Outlier Detection Methods For New Rural Cooperative Medical Scheme In China

ObjectivesThe study was aimed to analyze the distribution of the NCMS hospitalization costs, inpatients'composition, the composition of the types of diseases and other aspects; to find the factors affecting the hospitalization costs based on the comprehensive analysis; to explore the methods for the outlier detection of hospitalization costs with a variety of statistical methods comparison. According to the problems in the operation of NCMS, we intended to put forward rationalization proposals for NCMS, to control unreasonable medical expenses, to provide the scientific basis for the formulation of the relevant policies and to promote the sustainable development of NCMS based on the analysis.Methods1. Analysis of the NCMS hospitalization costsThe subject of this study is the NCMS hospitalization cost data in the eight districts (A-H districts) surrounding some city in Hubei province from January to June 2009, a total of 71982 cases. The hospitalization cost data includes the following contents: inpatient demographic traits, days of hospitalization, admission time, coding of diseases, hospitalization cost and its composition (The hospitalization cost is composed of eight components, such as, medicine expense, hospital fee, general inspection fee, large-scale inspection fee, surgical fee, treatment fee, medical fee and other cost). Frequency and proposition were used to describe the data distribution. Chi-square test, Mantel-Haenszel test and Kruskal-Wallis H rank sum test were utilized in the univariate analysis of hospitalization costs. Generalized linear regression model and stepwise multiple linear regressions were constructed for multivariate analysis of hospitalization costs. The boostrap method was used to estimate the average hospitalization cost in each hospital level. The softwares used in the study included SAS 9.0, MATLAB 7.0 and Excel.2. Outlier detection of hospitalization costs(1) Taking the district NCMS management office as a unit, the outlier detection for all diseases.The subject of this study is the hospitalization costs in the A district second-level hospitals, a total of 3568 cases. We utilized three outlier detection methods based on the studentized residuals of the generalized linear regression, the shared nearest neighbour (SNN) similarity and support vector regression. The Kappa test was used to test the consistency of the results of these three methods.(2) Outlier detection for the single disease hospitalization costsThe subjects of study are the chronic bronchitis cases in the eight districts, a total of 880 cases. We utilized the support vector data description to detect the outliers for the hospitalization costs. The first method directly used the hospitalization costs. The second one utilized the kernel principal component analysis for data processing. The Kappa test was exploited to test the consistency of the results.The softwares used in the study included SAS 9.0, MATLAB 7.0, R 2.3.0 and LibSVM 3.1.Results1. The distribution characteristics of the NCMS inpatients and hospitalization costsThere are obvious differences among the hospitalization rates in the different districts, the highest 4.87 percent, the lowest, only 1.63%, the first half year average hospitalization rate was 2.63%, within the normal range. For all inpatients, female patients accounted for 54.57%, males accounted for 45.25%, and female inpatients were more than the male. The three most common diseases were respiratory diseases, accounting for 17.08%; certain infectious and parasitic diseases accounted for 16.84%; diseases of the circulatory system, accounting for 12.11%. The three most costly diseases were congenital malformations, deformations and chromosomal abnormalities, for example, the average cost of 11211.44 yuan; cancer,7664.82 yuan; blood and blood-forming organs and certain disorders involving the immune mechanism,7250.82 yuan. The average days of hospitalization was 10.9, the days of hospitalization were mainly concentrated in 4-8 days and 8-12 days, accounted for 40.86% and 20.79% respectively. The cumulative proportion within 12 days reached 78.83%. Among the hospitalization cost, the medicine expense accounted for the largest proportion of 50.72%, followed by hospital fee, accounting for 22.89%, while large-scale inspection fees accounted for the lowest proportion of 1.52%. There were 13877 surgery cases and 58105 non-surgery cases. Non-surgery cases accounted for 80.72%.2. Related factors of hospitalization costsThe result of univariate analysis suggested that the seven factors of gender, age, type of diseases, admission time, the number of days in hospital, whether surgery, and hospital admission status had significant effects (P<0.0001). According to the results of the generalized linear regression models for all levels of hospitalization costs, all these seven factors were significant (P<0.05). But there were differences among the very significant factors for all levels of hospitalization costs. The factors for the first level hospitals were age, type of diseases, whether surgery and days of hospitalization; compare with the first level hospitals, the factors for the second level hospitals increased admission time; the factors for the third level hospitals augmented admission status. It can be seen that age, types of diseases, whether surgery, days of hospitalization were the main factors affecting the hospitalization costs. 3. The average hospitalization cost regulation indices for all levels of medical institutions.The average hospitalization cost in general township hospitals should be controlled in less than 1000 yuan; For center township hospitals (surgical cases more than 30% of all hospitalization cases), average cost was controlled in the range of 1235-1365 yuan; For secondary hospitals in districts, average cost was controlled between 3320 and 3570 yuan.4. Analysis of hospitalization costs for extra regionally referral casesMale portion of extra region was higher than the one of intra region (P<0.0001). But the hospitalization cost of male case was significantly higher than the cost of female (P<0.0001). Among the compositons of hospitalization costs for extra regionally referral cases, the medicine expense accounted for 52.07%, it was lower than township hospitals, but it was higher than secondary hospitals; the hospitalization fee accounted for 30.64%, it was obviously higher than other level hospitals. Among high cost hospitalization cases, the two most frequent types of diseases were diseases of the circulatory system and cancers, they accounted for 24.90% and 24.29% respectively. For the hospitalization costs of extra regionally referral cases, hospitalization days was the major factor, gender and admission status could affect it.5. Results of outlier detection(1) Taking the district NCMS management office as a unit, the outlier detection for all diseases.The method based on studentized residuals of generalized linear regression had a certain consistency with the outlier detection method based on support vector regression (Kappa=0.3414, of ASE=0.0339, u=10.07, P<0.0001; and the consistent rate 93.8%), but the consistency of these two methods with SNN similarity method was poor, Kappa values were -0.0058 and 0.0082, respectively. At first, the three methods were effective methods for the outlier detection for hospitalization costs. Secondly, the results of Kappa identity tests demonstrated that there was difference between the mechanism of the outlier detection method based on SNN similarity and the first two methods, the SNN method could be used as the complement of the first two methods.(2) Outlier detection for the single disease hospitalization costsTwo outlier methods based on support vector data description were feasible. According to the relevant researches, kernel principal component analysis could improve the performance of the algorithm. Between the two above-mentioned methods, Kappa=0.4135, ASE=0.1287, u=3.213, P= 0.0013 and the consistent rate of 86.46%. It was proved that the two outlier detection methods had moderate consistency.ConclusionOur study shows that it is necessary to establish the information processing and analysis system for the healthy development of the NCMS. According to the results, drugs charges account for the largest proportion in hospital costs, it is the key point to control medicine expense for controlling increment of health care costs; hospitalization days is the most important factor for hospitalization costs, and shortening hospitalization days is an effective way to reduce hospitalization costs. There were differences among the disease compositions of all the districts, the prevention work should be streghtened according to the disease compostions. The average costs of the major diseases of cancer, congenital malformations and circulatory system diseases were high and their proportions of the hosptitalization costs were large, so the security system should be established to protect against these major diseases. The average hospitalization cost regulation indices for all levels of medical institutions with bootstrap method to control the hospitalization cost increment from marcolevel. The establishment of the outlier detection system made it possible to monitor the hospitalization costs for individual inpatients from microcosmic level. Moreover, taking a variety of outlier detection methods, it could screen out more outliers from different sides. All of them could reduce the unreasonable expenditure, regulate the operation and improve the supervision of the NCMS.Innovation1. In this study, there were four methods applied to detect the outliers in the NCMS hospitalization costs, including the outlier detection algorithms based on the studentized residuals of the generalized linear regression, the SNN similarity, support vector regression and support vector data description. From the mass data, these methods could rapidly detect the candidate outliers and greatly reduce the artificial monitoring workload. They made it possible to monitor the hospitalization costs from microcosmic level.The results of the consistency tests between each pair of outlier detection methods demonstrated that the methods with the same mechanisms had some consistency; Different methods with different mechanisms detected different outliers. With the organic combination of these methods, it improved the sensity of the outlier detection.2. Boostrap method was applied to conduct the interval estimation of the average hospitalization costs. We calculated the rational ranges for the average hospitalization costs of all levels of intra regional hospitals, which provided the scientific basis for the average hospitalization cost regulation.