Evaluating if ChatGPT Can Answer Common Patient Questions Compared With OrthoInfo Regarding Rotator Cuff Tears

Document Type

Article

Publication Date

3-1-2025

Publication Title

J Am Acad Orthop Surg Glob Res Rev

Abstract

PURPOSE: To evaluate ChatGPT's (OpenAI) ability to provide accurate, appropriate, and readable responses to common patient questions about rotator cuff tears.

METHODS: Eight questions from the OrthoInfo rotator cuff tear web page were input into ChatGPT at two levels: standard and at a sixth-grade reading level. Five orthopaedic surgeons assessed the accuracy and appropriateness of responses using a Likert scale, and the Flesch-Kincaid Grade Level measured readability. Results were analyzed with a paired Student t-test.

RESULTS: Standard ChatGPT responses scored higher in accuracy (4.7 ± 0.47 vs. 3.6 ± 0.76; P < 0.001) and appropriateness (4.5 ± 0.57 vs. 3.7 ± 0.98; P < 0.001) compared with sixth-grade responses. However, standard ChatGPT responses were less accurate (4.7 ± 0.47 vs. 5.0 ± 0.0; P = 0.004) and appropriate (4.5 ± 0.57 vs. 5.0 ± 0.0; P = 0.016) when compared with OrthoInfo responses. OrthoInfo responses were also notably better than sixth-grade responses in both accuracy and appropriateness (P < 0.001). Standard responses had a higher Flesch-Kincaid grade level compared with both OrthoInfo and sixth-grade responses (P < 0.001).

CONCLUSION: Standard ChatGPT responses were less accurate and appropriate, with worse readability compared with OrthoInfo responses. Despite being easier to read, sixth-grade level ChatGPT responses compromised on accuracy and appropriateness. At this time, ChatGPT is not recommended as a standalone source for patient information on rotator cuff tears but may supplement information provided by orthopaedic surgeons.

Medical Subject Headings

Humans; Rotator Cuff Injuries; Surveys and Questionnaires; Patient Education as Topic; Comprehension; Generative Artificial Intelligence

PubMed ID

40080671

Volume

9

Issue

3

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