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Research and Application of data mining techniques in the field of health insurance

Author: HeJunHua
Tutor: ZhuYangYong
School: Fudan University
Course: Computer Software and Theory
Keywords: Data Mining Health insurance Fraud detection Consistent behavior Data mining tools
CLC: TP311.13
Type: Master's thesis
Year: 2011
Downloads: 152
Quote: 0
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Abstract


With data mining technology continues to evolve and mature , the research and application of data mining gradually penetrated into various industries . In the field of health insurance , to maintain the balance of payments of the medical insurance fund , effective supervision of the operation of the Fund , in order to ensure the safe operation of the Fund is an important issue . The Medicare information technology to build a relatively complete Medicare data warehousing, data mining technology has laid a good foundation . Data mining is the process of seeking the rule from the large amounts of data . Effective application of potential information in the Medicare data can be found in the field of health insurance , the auxiliary health insurance fund safe operation and risk control is perfect for modern health insurance fund operating system . This article summarizes the first scene in the field of health care possible data mining applications . The implementation of Medicare data data exploration, analyze Medicare data characteristics , data mining technology is applied to Medicare insured subdivision, treatment pattern mining , abstract and health insurance business needs a Medicare fraud detection problem , solve the problem more in-depth research , to make a consistent behavior mining algorithms, the effectiveness of the algorithm in practical applications is verified by experiments . The last article describes the Design and Implementation of the Medicare - oriented data mining tool , the tool has been applied in a city health insurance fund in the prevention and control of risk control platform , with a high degree of visualization to facilitate the operation of the health insurance business targeted . The main results include: 1 ) designed to detect potentially fraudulent behavior consistent algorithm CBM , and MaxCBM , the algorithm based on vertical data format frequent pattern mining, and experimentally verify the effectiveness and efficiency . 2) design a complete health insurance data mining framework , were constructed the insured person segmentation model based on clustering and sequence pattern discovery - based treatment model mining model . 3 ) the development of data mining tools for health insurance , and health insurance business logic and domain knowledge to facilitate the operation and use of the operational staff .

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CLC: > Industrial Technology > Automation technology,computer technology > Computing technology,computer technology > Computer software > Program design,software engineering > Programming > Database theory and systems
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