ICD-based data-encoded medical record error recognition system and recognition method thereof

Abstract

The invention discloses an ICD-based data-encoded medical record error recognition system and a recognition method thereof. The system comprises a server which is connected to a rule database and a data memory. The server (1) is internally provided with at least a user registration login unit and a data checking unit. The rule database is used for storing Y medical record error rules. The data memory is used for storing X data-encoded medical records to be identified. After any user is registered through the user registration login unit, the X data-encoded medical records to be identified areuploaded into the data memory, the data checking unit misidentifies the data-encoded medical records in the data memory and the Y medical record error rules one by one, and the information of existingdata-encoded medical records is obtained. The system and the method have the advantages that the intelligent identification is achieved without human intervention, and modification instructions of errors are given.

Description

technical field [0001] The invention relates to the technical field of medical disease data statistics, in particular to an ICD-based data coded medical record error identification system and an identification method thereof. Background technique [0002] The International Classification of Diseases (ICD) is a system that classifies diseases according to certain characteristics according to the rules and expresses them by coding methods. ICD is an internationally unified disease classification method formulated by WHO. It classifies diseases into categories according to their etiology, pathology, clinical manifestations, and anatomical location, making them an orderly combination and expressed by coding methods. The 10th revision of the "International Statistical Classification of Diseases and Related Health Problems" is commonly used all over the world, and the abbreviation of ICD is still retained, and it is collectively referred to as ICD-10. The system has collected abo...

AI Technical Summary

Problems solved by technology

However, at the current stage, there is a serious shortage of professional coders, and there are often many errors in the obtained coded data, which cannot meet the quality standards of DRGs technology for ICD coded data

Therefore, the existing technology hinders the promotion of DRGs technology

[0006] Second, the medical records are complex and changeable, and often one disease can cause multiple complications. However, when a doctor creates a medical record, he will record all the symptoms of the patient in detail, resulting in a complex and changeable medical record. For the record entry personnel, it is often difficult All diseases will be entered one by one, but for the final classification, mistakes or missing are prone to occur

[0007] Third, due to the complexity of the patient's illness, tens of thousands of illness codes are involved. When converting the medical records into data, it is very easy for the code to not correspond to the illness.

[0008] Fourth, in the existing technology, when people convert paper medical records into digital medical records, they still need to manually review the errors in the digital medical records, which is equivalent to requiring at least two or even more people to convert a medical record to digital To enter, time-consuming and labor-intensive

Even though a lot of labor was spent, there are still many errors in the final input results, which makes the medical record data conversion technology at the bottleneck stage, seriously affecting the development of medical information intelligent data

[0009] Based on the above statement, the accuracy of the digital medical record data obtained after the existing medical records are digitized is not guaranteed, resulting in low reliability of the digital medical record information and delaying the development of medical informatization

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