Application Of Data Mining Analysis On Serious Illness Insurance For Urban Residents In Guangxi

BackgroundAfter nearly two decades of efforts in our country, universal health care system has been initially formed. The basic medical needs of the majority of insured workers and residents have safeguard, and also established a medical insurance system of major workplace diseases. With the deepening of China’s medical reform and the continued expansion of health insurance coverage, medical insurance grows massive amounts of data. In contrast with this, when the amount of data grows extremely fast, people feel to cope with Data Ocean just like looking for a needle in a haystack due to a lack of rapid, efficient computer and information technology and method to extract useful information and knowledge. Therefore, we must be combined with an effective data processing method, extracted from vast amounts of medical insurance data for management decision-making information, then identifying the risk factors to provide more effective decision support.PurposeThis paper combine the urban residents’health care management demand with the data mining, not only adapting to the future development trend of medical insurance management, but also helping us to study the comprehensive situation of medical insurance for urban residents in Guangxi, to find and solve the key problems which restrict the development of the medical insurance, to provide effective suggestions for Guangxi medical insurance management and decision-making, and for the further promotion of Guangxi serious illness insurance providing scientific basis.MethodsUsing the data collection method and field interviewing with the people in charge of social security in Liuzhou and qinzhou, we collect the relevant operation policy of serious illness insurance, the dates of residents’outpatient and inpatient and the dates of reimbursement level, conducting an overall analysis of the two cities’operation to serious illness insurance.And it models and mines by using the decision tree, clustering analysis and outliers of SQL Server 2012. It analysis the disease risk of Liuzhou city residents and the main factors influencing the medical expenses.ResultsUrban residents’major disease risk by region has the maximum number of cases for the liunan district; the second is yufeng district, the third for liubei district. The medical expenses of serious illness insurance, residents’basic medical expense fund and insurance compensation is the same as the change of the distribution of the number of cases of a serious illness. Disease types are mainly chronic kidney disease, peptic ulcers, heart disease, diabetes and high blood pressure, etc. There are 1791 cases of disease among the top 10 disease types, for 11809 times’reimbursement, which is 57.11% of the total number of reimbursement.The situation of residents in medical institutions of different level:Tertiary medical institution is the main consumption choice, the highest of which is in hospital consumption, which is 125.5142 million Yuan, accounting for 84.64%. Individual citizens’pay rate is 23.26% on average; the highest for tertiary medical institutions, accounting for 23.75%, followed by secondary medical institutions which are 18.12%, the lowest is community health service stations that are 6.03%. Level 3 personal pay up to 29.28% of average outpatient service, followed by long-distance tertiary hospital accounting for 25.75% and the third is in hospital of tertiary medical institutions which is 23.43%. Residents basic overall compensation ratio and individual pay scale presents the opposite trend, the highest in the community health service station, at 87.75%, then decreasing and the lowest in the three-level medical institutions which is 58.27%. The serious illness insurance compensation ratio trend similar to individual pay scale, the highest in tertiary hospital is 17.31%, the lowest in the community health service stations is 6.23%.The situation of residents in malignant tumor distribution and compensation:Breast cancer, lung cancer, leukemia and cervical cancer is the most caused malignant tumors of serious illness insurance in Liuzhou. Malignant tumor hospital of compensation is generally higher than the average amount of a serious illness individual out-of-pocket expenses.The situation of residents of serious illness in hospital, medical expenses and compensation:There are 7284 cases inpatient in tertiary hospital, with an average of 18.86 days, main disease is:the Mediterranean anemia and chronic ischemic, malignant tumor, cerebral infarction, etc.201 cases of different ground are in hospital and the major diseases are nasopharyngeal carcinoma, liver cancer, leukemia, cervical cancer and stomach cancer.The results by the decision tree model are that medical category is a major factor affecting medical expenses, followed by classification of diseases, length of hospital stay, age and level of medical institutions, and gender has little impact.According to the grades of medical institution, it has generated three serious illness insurance’s outliers identification table and has analyzed the reasons of the generation. It puts forward that the outliers identification table should be applied to screen the medical induced consumption and fraud in hospital by serious illness insurance regulator.