Health insurance anomaly detection method and system based on hin mining dynamic multi-mode
An anomaly detection and multi-mode technology, applied in relational databases, database models, structured data retrieval, etc., can solve problems such as lack of immunity, complex and changeable medical insurance fraud, and achieve the effect of comprehensively improving identification and reducing complexity
Active Publication Date: 2020-08-07
SHANDONG UNIV
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[0004] However, with the development of the medical insurance system, medical insurance fraud is complex, changeable and hidden. What is more noteworthy is that new fraud patterns are constantly emerging, and the anomaly detection algorithm for fixed patterns lacks immunity to new fraud patterns. Therefore, the method of detecting fraudulent behavior based on a fixed pattern is difficult to meet the current needs, and considering the development of the medical system, the medical insurance attribute data is constantly changing, which leads to changes in attribute associations. Therefore, it is necessary to analyze the overall medical insurance data and individual medical insurance data. Abnormal data is detected, so as to continuously dynamically and adaptively optimize the abnormal detection model
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[0033] It should be noted that the following detailed description is exemplary and intended to provide further explanation of the present disclosure. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this disclosure belongs.
[0034] It should be noted that the terminology used herein is only for describing specific embodiments, and is not intended to limit the exemplary embodiments according to the present disclosure. As used herein, unless the context clearly dictates otherwise, the singular is intended to include the plural, and it should also be understood that when the terms "comprising" and / or "comprising" are used in this specification, they mean There are features, steps, operations, means, components and / or combinations thereof.
[0035] Implementation example one
[0036] This embodiment discloses a medical insurance anomaly detection method based on HIN...
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The invention provides an HIN mining dynamic multi-mode-based medical insurance anomaly detection method and system. The method comprises the steps of obtaining historical medical insurance record instance data; extracting strong association attributes related to medical insurance fraud to form a medical insurance feature data set; constructing a medical insurance heterogeneous information network; acquiring a heterogeneous information network and a meta-graph thereof based on construction of a medical insurance heterogeneous information network; randomly selecting an initial node based on themeta-graph of the medical insurance heterogeneous information network, and generating a single-layer mode and a composite mode through incremental addition of associated nodes and edges; and based ona single-layer mode in which the mode is NP>2, identifying outliers for different instances in the same instance set by adopting transverse comparison, and identifying outliers for medical records ofthe same instance in different time periods by adopting longitudinal comparison, thereby completing medical insurance record anomaly detection. The association of each node in the medical insurance records appearing at a plurality of time intervals in the same time period is reserved, so that the complexity of exception identification is reduced, and the exceptional medical insurance records canbe identified more comprehensively and perfectly.
Description
technical field [0001] The present disclosure relates to the technical field of medical insurance information processing, in particular to a method and system for detecting anomalies in medical insurance based on HIN mining dynamic multi-mode. Background technique [0002] With the development of medical insurance, its coverage is getting bigger and bigger, and related businesses are becoming more and more complicated. The problem of medical insurance fraud is becoming more and more serious. A lot of medical insurance funds have been defrauded. At the same time, with the development of medical insurance informatization, a large amount of medical insurance-related data has been accumulated in the process of medical insurance business, and detecting potential abnormal data from it is an important means to control the phenomenon of medical insurance fraud. [0003] The inventor found in the research that outlier detection is a common method for anomaly detection in medical ins...
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IPC IPC(8): G06Q40/08G06F16/2458G06F16/28
CPCG06F16/2465G06F16/288G06Q40/08
Inventor 史玉良赵备张坤王新军
Owner SHANDONG UNIV