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Natural Language Processing Improves Postoperative Discharge Instructions
Carrie N Reaver1, Rohit Siddabattula1, Daniel E Pereira1
1Department of Orthopedic Surgery, Washington University in St. Louis, St. Louis, Missouri, U.S.A.
Summary
Generative artificial intelligence (AI) significantly enhanced orthopaedic discharge instructions, improving readability, understandability, and actionability. This AI intervention offers a scalable solution for better patient recovery and reduced healthcare burden.
Area of Science:
- Orthopaedic Surgery
- Medical Education
- Health Informatics
Background:
- Current orthopaedic discharge instructions often present challenges in readability, understandability, and actionability for patients.
- Effective patient education is crucial for successful postoperative recovery and management.
Purpose of the Study:
- To evaluate the readability, understandability, and actionability of orthopaedic discharge instructions.
- To assess the effectiveness of generative artificial intelligence (AI) in improving these instructions.
Main Methods:
- Discharge instructions from an academic hospital were analyzed for key subcategories.
- ChatGPT-4 was employed to rewrite instructions using structured prompts.
- Readability, understandability (PEMAT), and actionability were quantitatively assessed and compared.
Main Results:
- Generative AI significantly reduced the average reading grade level from 9.8 to 7.5 (P < .001).
- Understandability scores increased from 63.6% to 87.9% (P < .001), and actionability scores improved from 44.4% to 73.6% (P < .001).
- Specific subcategories like narcotics, medications, and physical therapy required further targeted improvements.
Conclusions:
- Generative AI offers a cost-effective and scalable method to enhance orthopaedic discharge instructions.
- While AI improves key metrics, not all documents reached the target sixth-grade reading level.
- Targeted interventions for specific topics are recommended to optimize patient education and postoperative recovery.
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