VTE intelligent monitoring system supporting multi-role requirements
By constructing an evidence hypergraph and a guideline version dictionary tree, the VTE intelligent monitoring system realizes a closed loop of risk assessment and intervention execution among multiple roles, solves the problem of the disconnect between assessment results and the patient's condition in existing technologies, and enables the dynamic adjustment of prevention and control recommendations and nursing measures that are traceable and replayable.
Patent Information
- Application Number
- CN202610036749.4
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2026-01-13
- Publication Date
- 2026-02-10
- Estimated Expiration
- 2046-01-13
AI Technical Summary
Existing technologies in hospital-based VTE risk monitoring lack continuous tracking of patients' dynamic risks and cannot achieve real-time collaboration between different roles. This leads to a disconnect between assessment results and actual changes in the patient's condition. Doctors' prevention and control recommendations lack traceable evidence, and the nursing execution process suffers from problems such as frequent assessment triggers but low effective intervention rates, redundant reminders, and incomplete closed loops. These issues make it difficult to meet the needs for accurate identification and dynamic prevention and control under multi-role collaboration.
Design a VTE intelligent monitoring system that supports the needs of multiple roles. On the physician side, a traceable chain of evidence is generated by constructing an evidence hypergraph and a guideline version dictionary. On the nursing side, the traceability chain is received and parsed, and nursing execution instructions are generated by combining real-time monitoring data. The system is dynamically adjusted and feedback is provided to achieve closed-loop collaboration among multiple roles in risk assessment, intervention execution, and result verification.
It achieves a collaborative closed loop between risk assessment by doctors and intervention execution by nurses, dynamically generates prevention and control recommendations and maintains consistency with the guideline version, ensures that the assessment results are traceable and replayable, and enables the nursing staff to screen instructions and provide real-time feedback based on the traceability chain, so that prevention and control measures can be adaptively adjusted according to changes in the patient's condition.