Method and system for detecting medical insurance fraud and storage medium

Abstract

The invention provides a method and system for detecting medical insurance fraud and a storage medium, and the method comprises the steps of obtaining the doctor-seeing record of a patient, extractingthe corresponding patient features according to the obtained doctor-seeing record, and building a doctor-patient relation neural network according to the extracted patient features and the corresponding relation between the patient and a doctor; inputting a pre-marked fraud sample into the established doctor-patient relationship neural network, training a fraud prediction model, and outputting aprediction value that each patient node has a fraud behavior from the trained fraud prediction model; and judging whether the patient of the corresponding node has a fraudulent behavior or not according to the output prediction value. Whether a patient has fraudulent behaviors or not is predicted through a machine learning method, the difficulty of predicting the fraudulent behaviors is reduced, the medical insurance fraudulent behaviors can be effectively detected, and health popularization of a medical insurance system is facilitated.

Description

technical field [0001] The present invention relates to the field of medical technology, in particular to a method, system and storage medium for detecting medical insurance fraud. Background technique [0002] Medical insurance is a social security project in my country. It is a social security system established to compensate citizens or workers for economic losses caused by disease risks. However, with the popularization of medical insurance, the phenomenon of criminals taking advantage of the opportunity of universal medical insurance to commit medical insurance fraud emerges in an endless stream, resulting in an additional increase in national fiscal medical and health expenditures. [0003] Therefore, effective detection of medical insurance fraud activities is required. Existing detection methods include unsupervised learning and supervised learning. Among them, unsupervised learning relies on outlier analysis to find potential anomalies in unlabeled data, but the me...

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Problems solved by technology

[0006] The technical problem to be solved by the present invention is to provide a method, system and storage medium for detecting medical insurance fraud in view of the above-mentioned defects of the prior art, aiming to solve the problem that the medical insurance fraud detection method in the prior art cannot be effectively detected, The Problem With Not Preventing Medicare Fraud

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