A fast structured method for diagnosis of single disease based on medical insurance data

Abstract

The invention discloses a fast structuring method of single disease diagnostic information based on medical insurance data, which structurizes the diagnostic information in medical big data and constructs a single disease thesaurus. Includes extracting diagnostic information from medical insurance database; Segmentation of unstructured text into multiple lexical texts; Tagging the part of speech of the lexical text; Training word vector; Positive order sorting, dividision of corresponding word sets; Cosine distance used to find the relevance between words. acquisition of a list of words that are most similar to the standard expression of the disease as a list of standard words; Computer-assisted manual verification is performed by professionals and repeated many times. The method of the invention can be used for realizing the rapid structuring of the personalized single disease diagnosis text data, providing technical support for fully and efficiently utilizing the diagnostic information in the medical insurance data, greatly improving the efficiency of data processing and utilization, and accelerating the popularization and application of the medical big data conversion.

Description

technical field [0001] The invention provides a fast structuring method for diagnostic data / information about a single disease in a medical insurance database, and belongs to the technical field of medical text processing. Background technique [0002] Medical insurance data (Claims data) is the data generated during the medical insurance business process. The data volume is huge, covering a large-scale group of people, and can completely and truly record the medical treatment information and reimbursement records of the group within a certain period of time. [0003] At present, more and more workers in the medical field are beginning to try to use medical big data for processing and application. Unified and standardized processing, so as to realize the completion of drug evaluation through active monitoring. [0004] However, there are a large number of unstructured texts (mainly diagnostic information) in medical big data. For example, there may be many different express...

AI Technical Summary

Problems solved by technology

[0011] The present invention aims at the non-structural problem of disease diagnosis text or coding (such as multiple myeloma) data existing in the current medical insurance database, and adopts a large and comprehensive matching method different from the previous construction of field databases, and uses single-disease centralized strategy, using the broadest extraction field to include all potential target disease patients into the structured range, and then combined with computer-aided screening and matching, all relevant diagnostic texts of a single disease (such as multiple myeloma) in the medical insurance database For fast and personalized structuring

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