Call distribution method and system based on nursing needs
By monitoring bedside vital signs, constructing multidimensional abnormal trigger identifiers and performing Boolean logic analysis, emergency codes for bedside calls are generated. Combined with task execution time and load capacity assessment, nursing resource allocation is optimized, solving the problems of lagging clinical risk identification and uneven resource allocation in traditional nursing call distribution methods, and improving the accuracy and real-time response of automated collaboration in nursing services.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- 中国人民解放军海军青岛特勤疗养中心
- Filing Date
- 2026-04-30
- Publication Date
- 2026-07-21
AI Technical Summary
Traditional nursing call distribution methods rely on mechanical pressure to trigger a single call signal, which leads to a lag in the perception of patients' vital signs, makes it impossible to capture potential clinical risk indicators in real time, and makes it difficult to prioritize urgent critical care requests in multi-bed concurrent call scenarios. The uneven allocation of manual resources results in low response efficiency in the ward.
By monitoring bedside vital signs, constructing multidimensional abnormal trigger identifiers, generating emergency call codes for hospital beds through Boolean logic analysis, dynamically optimizing nursing resource allocation by combining task execution time and load capacity assessment, and generating path response paths using spatial mapping nodes, the global optimal distribution of nursing resources is achieved.
It has achieved automated identification of clinical risk characteristics, solved the problems of strong subjectivity and ambiguous response priorities in manual assessment, effectively shortened the waiting time for critical care calls, reduced the workload of staff, and improved the accuracy and real-time response of automated collaboration in ward nursing service processes.
Smart Images

Figure CN122157447B_ABST