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Improving readability of shoulder and elbow surgery online patient education material with Chat GPT (Chat Generative
Krishna Chandra1, Umar Ghilzai1, Jad Lawand2
1Department of Orthopaedic Surgery, Baylor College of Medicine, Houston, TX, USA.
Background:
Health literacy is crucial for effective doctor-patient communication, particularly for surgical patients who need to comprehend complex procedures and care protocols. The American Medical Association and National Institutes of Health suggest patient education materials be at a sixth-grade to eighth-grade reading level. Despite this, many online materials for orthopedic surgeries, including shoulder and elbow procedures, are written above this level. Chat Generative Pretrained Transformer (ChatGPT) 4, an artificial intelligence language model, may help simplify these materials and improve readability given poor health literacy in patient populations.
Methods:
Thirty excerpts of patient-facing information on shoulder and elbow surgeries were selected from academic and professional medical sources on a variety of shoulder and elbow orthopedic surgical topics. Original readability was assessed using the Simple Measure of Gobbledygook (SMOG) Index. ChatGPT then analyzed readability and simplified the text to a sixth-grade to eighth-grade level. To simplify the text while maintaining medical accuracy, the following prompt was used: "Rewrite this text at a sixth-grade to eighth-grade level without losing information." ChatGPT achieved this by defining medical terminology, using common language equivalents, and restructuring information for easier readability. Simplified text was re-evaluated for readability by both SMOG Index and ChatGPT and accuracy by study authors.
Results:
Original excerpts had an average SMOG readability score of 10.1, requiring about a 10th-grade reading level. ChatGPT's initial analysis averaged slightly higher at 10.3 (P < .001). Following simplification, both the SMOG readability score and ChatGPT significantly dropped to 8.3 and 7.7, respectively, aligning closer to recommended readability levels (P < .001). ChatGPT also provided targeted feedback on areas for readability improvement.
Conclusions:
ChatGPT-4 demonstrated utility in analyzing and simplifying shoulder and elbow surgery patient education materials, lowering readability to near-recommended levels. By providing specific suggestions for simplification, ChatGPT streamlined the revision process, enhancing potential patient understanding and engagement. However, human review remains necessary to ensure clinical accuracy in artificial intelligence-simplified materials.
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