A smart ward information management method, system, medium and program product

By collecting and analyzing the physiological and behavioral data of patients in real time, combining individual information for behavioral evaluation, and automatically generating a task list, the problems of blind spots in the existing technology and low patrol efficiency are solved, and efficient dynamic monitoring and early warning management of non-cooperating patients are achieved.

CN119400423BActive Publication Date: 2025-03-21BEIJING CAPIPAD COMM EQUIP
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Patent Information

Application Number
CN202411908438.X
Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
Filing Date
2024-12-24
Publication Date
2025-03-21
Estimated Expiration
2044-12-24

AI Technical Summary

Technical Problem

The prior art has blind spots in monitoring the overall status changes of patients in non-cooperation periods, and manual patrol efficiency is low, making it difficult to detect and deal with emergencies in a timely manner, and poses safety hazards.

Method used

By collecting the patient's physiological index data and behavioral characteristic data in real time, constructing a characteristic data sequence, combining the patient's individual information for behavioral evaluation, automatically generating a task execution list, and updating the behavioral risk score based on the warning response results.

Benefits of technology

Dynamic monitoring and early warning management of patient status has been achieved, the patient's safety guarantee level has been improved, potential risks have been identified in a timely manner, monitoring blind spots have been reduced, and patrol efficiency has been improved.

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Abstract

An information management method, system, medium and program product for a smart ward, relating to the field of electronic digital data processing, the method comprising: collecting physiological index data and behavioral characteristic data of a target patient, constructing a characteristic data sequence; parsing each data in the characteristic data sequence, determining the current representative behavior and behavior change sequence of the target patient; obtaining individual information of the patient, inputting the individual information of the patient, the current representative behavior and the behavior change sequence into a behavior assessment model, obtaining risk representative behavior and behavior risk score; determining the warning level and warning response time limit based on the behavior risk score; when the warning level is higher than the preset warning threshold, generating a task execution list according to the warning response time limit and the risk representative behavior, and sending it to a medical terminal; updating the behavior risk score according to the warning response result returned by the medical terminal. The implementation of this application can optimize the patient status monitoring of smart wards and avoid safety hazards to a greater extent.
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