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Optimizing Nursing Records: Exploring the Impact of AI-Enhanced Documentation
Ryoma Seto1, Susumu Wakabayashi1,2, Yuko Takeyama3
1Health Informatics, Faculty of Healthcare, Tokyo Healthcare University, Japan.
Structured templates in nursing records significantly reduce missing information and redundancy, improving patient care quality and safety. AI tools can further enhance adherence and data completeness for consistent clinical practices.
Area of Science:
- Health Informatics
- Nursing Documentation
- Clinical Data Management
Background:
- Standardized medical records are crucial for enhancing patient care quality and safety.
- Free-form nursing documentation often results in inefficiencies, ambiguities, and data gaps.
- Evaluating adherence to structured templates is key to optimizing clinical record-keeping.
Purpose of the Study:
- To assess adherence to predefined documentation templates in nursing records.
- To identify rates of missing information, redundant entries, and medication mention specificity.
- To evaluate the impact of structured templates on documentation quality and patient safety.
Main Methods:
- Analysis of 90,432 anonymized nursing records using text mining techniques.
- Evaluation of adherence across five key topics: mild fever, pain, fever, bowel control, and fever reduction.
- Quantification of missing items, redundant entries, and medication classification specificity.
Main Results:
- Missing information rates ranged from 40.0% (fever reduction) to 43.9% (pain).
- Redundant entries varied from 11.7% (mild fever) to 20.0% (fever).
- Structured templates improved specificity in medication mentions compared to general classifications, enhancing patient safety.
Conclusions:
- Structured templates are essential for reducing variability and improving the completeness of nursing records.
- User-friendly templates and integration of AI technologies can optimize adherence and data accuracy.
- Further research into user experience and organizational factors is needed for successful implementation.
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