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Generative AI-Based Nursing Diagnosis and Documentation Recommendation Using Virtual Patient Electronic Nursing
Hongshin Ju1,2, Minsul Park1,3, Hyeonsil Jeong1
1DKMediInfo, Hwaseong, Korea.
Healthcare Informatics Research
|May 19, 2025
Summary
Generative artificial intelligence (AI) significantly cut nursing documentation time by 40%, improving efficiency. While AI shows promise, further development is needed to enhance accuracy for seamless clinical integration.
Area of Science:
- Nursing Informatics
- Artificial Intelligence in Healthcare
- Clinical Documentation
Background:
- Nursing documentation accounts for approximately 30% of nurses' time, impacting workflow and patient safety.
- Optimizing documentation efficiency is crucial for modern healthcare settings.
- Traditional electronic nursing records (ENRs) present challenges in time management for nursing staff.
Purpose of the Study:
- To compare the efficiency of traditional nursing documentation with a generative AI-based system.
- To evaluate the impact of AI on reducing documentation time and improving accuracy.
- To assess the overall efficiency and quality of AI-assisted nursing documentation.
Main Methods:
- Forty nurses with at least 6 months of experience participated in the study.
- A pre-assessment phase used traditional ENRs, followed by a post-assessment phase using a generative AI system (SmartENR, based on ChatGPT 4.0).
- Documentation quality was assessed using a 5-point scale for accuracy, comprehensiveness, usability, ease of use, and fluency.
Main Results:
- AI-assisted documentation reduced time by approximately 40% (467.18s traditional vs. 182.68s AI).
- AI-generated documentation received high scores for ease of use (4.80/5) and fluency (4.50/5).
- Scores for accuracy (3.62/5) and usability (3.50/5) indicate areas for AI model refinement.
Conclusions:
- Generative AI substantially decreases nursing documentation workload and enhances efficiency.
- AI systems have the potential to improve nursing documentation quality and efficiency in clinical practice.
- Further AI model refinement is necessary to optimize accuracy and facilitate seamless integration into clinical workflows.
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