Hospital operation monitoring analysis method and platform based on artificial intelligence

By adopting artificial intelligence-based data integration and analysis methods in hospital operation and management, the problem of low efficiency of data integration and resource scheduling under the traditional management model is solved, real-time and intelligent operation management is achieved, and resource utilization and medical service quality are improved.

CN119673411AInactive Publication Date: 2025-03-21HUNAN CHANGXIN CHANGZHONG TECH SHARES CO LTD
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Patent Information

Application Number
CN202510194571.1
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-02-21
Publication Date
2025-03-21
Estimated Expiration
Not applicable · inactive patent

AI Technical Summary

Technical Problem

It is difficult for traditional hospital operation and management models to integrate multi-source heterogeneous data, process complex nonlinear relationships and high-dimensional data, and lack real-time and intelligent support, resulting in low resource scheduling efficiency, improper drug inventory management, and lag in medical quality monitoring.

Method used

Adopting the hospital operation monitoring and analysis method based on artificial intelligence, a unified data platform and an intelligent operation management system are built through steps such as data collection and integration, data preprocessing, AI model construction and training, real-time monitoring and analysis, visualization and report generation.

Benefits of technology

Real-time analysis and dynamic optimization of hospital resource usage are achieved, resource utilization and scheduling efficiency are improved, drug shortage and oversupply are avoided, real-time and accuracy of medical quality monitoring are enhanced, and operating costs are reduced.

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Abstract

The invention provides a hospital operation monitoring analysis method and platform based on artificial intelligence, and the method comprises the steps: collecting data from a plurality of data sources of a hospital, and integrating the multi-source heterogeneous data into a unified data platform through a data access gateway; performing cleaning, standardization and feature extraction on the acquired data, and extracting key features by using automatic feature engineering; constructing an AI model according to a hospital operation scene, and training and verifying the model by using historical data; inputting the real-time data into an AI model for analysis, generating a prediction result or a classification label, and performing real-time early warning on an abnormal condition; key indexes and analysis results are displayed through a visual instrument panel, and an operation report is automatically generated. Through the artificial intelligence technology platform, hospital resource use conditions can be analyzed in real time, resource allocation can be dynamically optimized, medical staff scheduling and equipment use plans can be automatically adjusted, waiting time of patients is shortened, and scheduling efficiency and response speed are remarkably improved.
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