Generative AI-Assisted Nursing Handover: Enhancing Clinical Data Integration and Work Efficiency

Area of Science:

• Healthcare Informatics
• Artificial Intelligence in Medicine
• Nursing Workflow Optimization

Background:

• Nursing handover is critical for patient safety but time-consuming.
• Inefficient documentation contributes to significant nursing workload.
• Current handover processes may lack standardization and efficiency.

Purpose of the Study:

• To evaluate the effectiveness of generative AI in automating nursing handover documentation.
• To assess the impact of AI integration on documentation time and nursing efficiency.
• To determine the practicality and scalability of AI-driven handover solutions.

Main Methods:

• Implementation of a generative AI system integrated with existing nursing information systems.
• Deployment across three hospitals within the TMU Health network.
• Quantitative analysis of documentation time before and after AI implementation.

Main Results:

• Documentation time was reduced by over 99% post-AI integration.
• The AI system demonstrated practicality and scalability in real-world hospital settings.
• Significant improvements in nursing efficiency were observed.

Conclusions:

• Generative AI provides a highly effective solution for automating nursing handover documentation.
• AI integration can substantially alleviate nursing workload and improve operational efficiency.
• The developed system represents a promising advancement for healthcare informatics and nursing practice.