Normalization method and device for diagnosis words

Abstract

The invention discloses a normalization method and device for diagnosis words. The method comprises the following steps: acquiring a main diagnosis word and an attribute word of an original diagnosisword by structurally separating the original diagnosis word; determining whether the main diagnosis word and the attribute word of the original diagnosis word are the same as each main diagnosis wordand each attribute word of each standard diagnosis word in a standard word list or not; and normalizing the original diagnosis word to a standard diagnosis word when determining that the main diagnosis word and the attribute word of the original diagnosis word are both same as a main diagnosis word and an attribute word of the standard diagnosis word. With the normalization method and device for diagnosis words, input amount of manual labor is reduced and labor cost is reduced. The normalization efficiency of diagnosis words is enhanced. Meanwhile, the normalization accuracy of the original diagnosis word is improved.

Description

technical field [0001] The present disclosure relates to the technical field of data normalization, and in particular, to a diagnostic word normalization method and a diagnostic word normalization device. Background technique [0002] Medical data is the data generated by doctors in the process of diagnosing and treating patients, including basic patient data, electronic medical records, diagnostic words, medical imaging data, medical management, economic data, medical equipment and instrument data, etc. primary source of information. Effectively counting, aggregating, and analyzing healthcare data has significant benefits for healthcare organizations. [0003] When normalizing medical data, the normalization of diagnostic words is the most important part. At present, the diagnostic words are mainly obtained through manual input by doctors. Due to the different writing habits of doctors, there may be multiple descriptions for the same diagnosis. Therefore, when normalizing...

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Problems solved by technology

[0004] Obviously, in the above method, on the one hand, it is necessary to manually normalize the diagnostic words of different descriptions, resulting in a large amount of manpower input, high labor costs, and low efficiency; on the other hand, when manually normalizing the diagnostic words, Since different people may have different understandings of the same diagnostic result, when normalizing the same diagnostic word, different people may make different normalization results, which reduces the accuracy of diagnostic word normalization

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