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Medical insurance fraud detection method based on multiple features

A technology of medical insurance and detection methods, which is applied in the field of fraud detection and identification, and can solve problems such as difficult fraud cases

Active Publication Date: 2015-12-16
CHENGDU SHULIAN YIKANG TECH CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

With the increasing number of health insurance fraud patterns, it is becoming more and more difficult for existing fraud methods to effectively detect variable fraud cases

Method used

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  • Medical insurance fraud detection method based on multiple features
  • Medical insurance fraud detection method based on multiple features
  • Medical insurance fraud detection method based on multiple features

Examples

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Embodiment Construction

[0021] In order to be clearer, in conjunction with the implementation examples, the specific embodiments of the present invention are described below. It should be noted that when the detailed description of known functions and designs may dilute the main content of the present invention, these descriptions are here will be ignored.

[0022] In this embodiment, diabetes, a common disease, is taken as an example, and the data is the medical insurance data of a certain administrative region in Chengdu.

[0023] In this implementation example, the detection method of medical insurance fraud includes the following steps:

[0024](1) All the records of diabetes are selected from the data as the basic data. In the data records, there are many records for each hospitalization of each person, with a total of more than 400,000 records, which will record the consumption of various treatment items (including various medications, inspections, laboratory tests, etc.) for the same patient ...

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Abstract

The invention discloses a medical insurance fraud detection method based on multiple features. The method comprises: aimed at treatment histories of all patients suffered from the same disease in medical insurance declaration data, in combination with medicine classification knowledge, adopting probability statistics, mixture Gaussian modeling, feature fusion and other techniques to extract multiple secondary feature data with higher distinction degree; then, vectorizing the treatment histories of the patients based on the secondary feature data; and then, after carrying out clustering analysis on treatment data marked with 'normal', adopting a non-linear support vector machine classification technique to establish multiple classification hyperplanes for each type of normal treatment data subjected to clustering and treatment data marked with 'fraud', so that the fraud detection can be carried out on non-marked medical insurance data. The method can be used for quickly and effectively detecting the fraud data existent in the medical insurance data, and has relatively high accuracy.

Description

technical field [0001] The invention relates to the field of fraud detection and recognition, in particular to a multi-feature-based detection method and system for medical insurance fraud. Background technique [0002] In the medical security social system, tens of thousands of transaction data of outpatient clinics and hospital medical behaviors occur every day. Transactions mainly include transactions between patients and medical institutions, and transactions between medical institutions and insurance institutions. At present, the existing medical insurance processing system has some disadvantages when processing payment transactions, that is, it cannot identify whether the real needs of patients are true, and it is easy to cause insured persons or medical institutions to seek benefits from it. According to the "Financial Times" report, the U.S. government has used big data methods to identify and distance medical insurance fraud and saved billions of dollars in medical ...

Claims

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Application Information

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IPC IPC(8): G06F17/30G06K9/62
CPCG06F16/285G06F18/23213G06F18/2411
Inventor 不公告发明人
Owner CHENGDU SHULIAN YIKANG TECH CO LTD
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