Medicine project name contrast translation method for heterogeneous system

Abstract

The invention discloses a medicine project name contrast translation method for a heterogeneous system, and the method comprises six steps: data extraction and preprocessing, name cascading search, preliminary statistics of divided words, regression of all corpuses, repeated dividing of words, the determining of reasonability of all divided words, and the quantification of combined divided words. According to the invention, the method finds the difference of three catalogs of all regions through big data mining analysis. Taking the difference as the starting point, the method builds a three-catalog difference feature library of the heterogeneous systems of all places, builds a reliable medicine project name matching algorithm, effectively replaces a conventional manual contrast three-catalog matching method, solves a problem that the three-catalog contrast mapping period among the heterogeneous systems is longer, gives full play to the value of big data, and improves the medical data circulation efficiency. Meanwhile, the method does not need a professional grammatical word dividing tool to carry out the semantic analysis of each medical project mane, and reduces the complexity of the whole algorithm process.

Description

technical field [0001] The invention relates to the medical and health field, in particular to a drug item name translation method used in heterogeneous systems. Background technique [0002] In 2012, the State Council issued the "Notice on Printing and Distributing the Plan and Implementation Plan for Deepening the Reform of the Medical and Health System during the "Twelfth Five-Year Plan" Period", requiring active exploration and establishment of a protection mechanism for major and serious diseases, while increasing the maximum payment limit of basic medical insurance and the payment of high medical expenses On the basis of the proportion, coordinate basic medical insurance and commercial health insurance policies, and actively explore ways to use basic medical insurance funds to purchase commercial critical illness insurance or establish supplementary insurance to effectively improve the level of protection for major and serious diseases. In the same year, the National D...

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Problems solved by technology

[0003] However, with more and more institutional participants in medical insurance, how to correctly carry out data exchange and analysis, and at the same time analyze the differences in different regions, and how to avoid the three catalogs (drugs, items, materials) Problems such as false positives and differences in analysis results caused by inconsistencies in coding and names need to be resolved urgently

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