Package type medicine purchasing anomaly detection method based on FP-growth and graph network

A technology of anomaly detection and package, which is applied in the direction of drugs or prescriptions, neural learning methods, biological neural network models, etc., can solve problems such as arbitrage of medical insurance funds, and achieve the effects of accelerating mining speed, reducing time and space overhead, and fast efficiency

Pending Publication Date: 2021-06-18
SHANDONG IND TECH RES INST OF ZHEJIANG UNIV
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  • Abstract
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  • Claims
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Problems solved by technology

[0011] The technical problem to be solved by the present invention is to provide an abnormal detection method based on FP-growth and graph network to solve the problem of institutional package drug purchase and medical insurance fund

Method used

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  • Package type medicine purchasing anomaly detection method based on FP-growth and graph network

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Embodiment

[0039] An embodiment, a method for abnormal detection of package medicine purchase based on FP-growth and graph network, comprising the following steps:

[0040] S1. Data preprocessing, processing multiple prescription data of a single person in a specific area into a single record for a single person.

[0041] Specifically, multiple pieces of prescription data of a single person in a single visit of all institutions in a certain area are processed into a single record for a single person. The fields contained in the record include institution code, institution name, visit serial number, and insured person information , Purchase drug code, purchase drug name, diagnosis disease code, diagnosis disease name, etc.

[0042]S2. Establishing a drug relationship diagram, and establishing a drug relationship diagram for a specific area according to the data obtained in step S1.

[0043] Specifically, according to the data obtained in step S1, the drug relationship graph of the region...

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Abstract

The invention belongs to the technical field of medical data mining, and particularly relates to a package type medicine purchasing anomaly detection method based on an FP-growth and graph network. The invention discloses a package type medicine purchasing anomaly detection method based on an FP-growth and graph network. The method comprises the following steps: S1, data preprocessing; S2, establishing a drug relation graph; S3, training the network; S4, drug combination mining; S5, establishing a drug relation graph of a single mechanism; s6, predicting a result; and S7, obtaining a final result, and repeatedly iterating the steps S4 to S6 to obtain all abnormal detail results of the specific region. The invention provides an FP-growth and graph network-based package type medicine purchasing anomaly detection method for solving the problem of institution package type medicine purchasing for extracting medical insurance funds. The FP-growth and graph network-based package type medicine purchasing anomaly detection method provided by the invention is used for solving the problem of institution package type medicine purchasing.

Description

technical field [0001] The invention belongs to the technical field of medical data mining, and in particular relates to an abnormal detection method for package medicine purchase based on FP-growth and graph network. Background technique [0002] The current situation of defrauding medical insurance funds by fraud is relatively severe. [0003] The use of automated technology to detect fraudulent insurance institutions / crowds is the main method other than manual spot checks. At the same time, the use of rule-based detection methods is the mainstream method. Its advantages lie in simple logic and a high degree of compliance with the detected objects, but it also has the ability to migrate algorithms. Poor, high space-time overhead, complex data preprocessing and weak ability to detect masquerade behavior. [0004] In order to solve the shortcomings of the above rule-based algorithms, a package-based drug purchase anomaly detection method based on FP-growth and graph network...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q40/08G16H20/10G06N3/04G06N3/08G06N5/02
CPCG06Q40/08G16H20/10G06N3/04G06N3/08G06N5/025
Inventor 吴健姜晓红应豪超何振烽
Owner SHANDONG IND TECH RES INST OF ZHEJIANG UNIV
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