Abnormality detection method and device for medical data, equipment and storage medium

Abstract

The invention relates to the field of artificial intelligence and digital medical treatment, is applied to the field of intelligent medical treatment, and discloses a medical data anomaly detection method, device and equipment and a storage medium. The method comprises the following steps: receiving hospitalization medical data, and inputting the hospitalization medical data into a preset judgment engine for verification; if the check of the judgment engine is not passed, determining that the hospitalization medical data is abnormal data; if verification of the judgment engine is passed, taking the hospitalization medical data passing verification of the judgment engine as to-be-processed data, and performing disease name extraction on the to-be-processed data by utilizing a disease theme extraction model; according to the disease name, obtaining an identification model, inputting the to-be-processed data into the identification model for abnormality judgment, and determining whether the to-be-processed data is abnormal data; and when the to-be-processed data is abnormal data, outputting the corresponding to-be-processed data. The invention further relates to a block chain technology, and hospitalization medical data is stored in blockchain. The abnormal data in the hospitalized medical data can be accurately screened out.

Description

technical field [0001] The present application relates to the fields of artificial intelligence and digital medical care, and in particular to a medical data anomaly detection method, device, equipment and storage medium. Background technique [0002] In hospital charges, under the project-based payment method, the hospital lowers the hospitalization standard and admits patients or even non-patients to obtain medical insurance funds. With the payment of DRG and DIP, this violation will not be corrected but may exist for a long time in a more subtle way. In the prior art, it is often judged whether the inpatient medical records are abnormal data by judging the ratio of drug expenses, inspection and inspection expenses, and treatment expenses in the inpatient medical records. Judgment accuracy is low. Therefore, how to accurately judge whether the inpatient medical records are abnormal data has become an urgent problem to be solved. Contents of the invention [0003] The ...

AI Technical Summary

Problems solved by technology

[0003] This application provides a medical data abnormality detection method, device, equipment and storage medium to solve the problem in the prior art of how to review inpatient medical records to determine whether they meet the inpatient qualifications

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