Device and method for automatically generating quality control circle association diagram in hospital adverse event management

By using machine learning models to process and analyze text data in hospital adverse event management, the quality control circle correlation diagram is automatically generated, which solves the problems of low efficiency and poor accuracy of manually generating correlation diagrams in the existing technology, and realizes intelligent analysis and automatic analysis Pushing improves the accuracy and efficiency of adverse event management.

CN113934859BActive Publication Date: 2025-02-21JIANGSU UNIV
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Patent Information

Application Number
CN202111134653.5
Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
Filing Date
2021-09-27
Publication Date
2025-02-21
Estimated Expiration
2041-09-27

AI Technical Summary

Technical Problem

In the prior art, the quality control circle correlation chart of hospital adverse events mainly relies on manual generation, resulting in large statistical workloads and easy errors.

Method used

By collecting text descriptive data of hospital adverse events, using machine learning models for data processing and module learning, the quality control circle correlation diagram in adverse event management is automatically generated.

Benefits of technology

Achieve intelligence and correlation analysis of the causes of adverse events, reduce human errors, improve the accuracy of the analysis, and automatically push the correlation diagram to remind medical personnel of the main causes and inherent correlations of adverse events to avoid medical adverse events The recurrence happened.

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Abstract

The present invention provides a device and method for automatically generating a quality control circle association diagram in hospital adverse event management, which belongs to the field of medical information management technology. The data acquisition module collects text descriptive data of adverse events in the hospital adverse event system, the machine learning module trains and tests the text data set, performs entity recognition on the main factors that cause adverse events, and realizes the adverse event entity extraction function. The association graph generation module is used to automatically generate the title, theme factors, arrows and number of arrow directions of the association graph through the entity extraction results through keyword weight descending analysis, so as to realize the visualization of the adverse event analysis results. The association graph push module is used to automatically push the association graph through the hospital public account, so as to facilitate the medical and nursing management personnel of each department to view the latest association graph in time. The present invention automatically generates a quality control circle association graph in adverse event management, and realizes the intelligent and correlation analysis of the causes of the entire adverse event.
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Citation Information

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