Objective To develop an AI agent-based training system for nursing assistants and evaluate its effectiveness in clinical practice.

Methods A standardized knowledge base and AI assistant were established by integrating professional knowledge graphs and industry consensus to develop an intelligent nursing training system. Multiple evaluation indicators were compared before and after system implementation to comprehensively assess nursing assistants' learning performance and clinical practical competencies.

Results A total of 50 medical nursing assistants were included. After system implementation, nursing assistants' core competencies improved significantly. Scores for theoretical knowledge (67.42 ± 7.77 vs. 63.98 ± 7.29), practical skills (76.98 ± 8.21 vs. 67.68 ± 7.48), and professional literacy (66.32 ± 6.56 vs. 59.48 ± 7.15) were all significantly higher than before implementation (P < 0.05). The total score for self-directed learning increased from (30.94 ± 2.94) to (47.18 ± 6.48) (P < 0.001). Compliance with basic life care specifications increased from 80.0% to 96.0%, and the implementation rate of nursing risk prevention measures increased from 72.0% to 94.0% (P < 0.05). In addition, the satisfaction levels of medical staff and patients were significantly improved (P < 0.001).

Conclusion The AI agent-based training system significantly enhances the training quality and clinical care safety of nursing assistants, and improve multi-party satisfaction of doctors and patients. It is an effective strategy for optimizing geriatric health care services.

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