The internet has introduced many resources frequently accessed by patients prior to orthopaedic visits. Recently, Chat Generative Pre-Trained Transformer, an artificial intelligence-based chat application, has become publicly and freely available. The interface uses deep learning technology to mimic human interaction and provide convincing answers to questions posed by users. With its rapidly expanding usership, it is reasonable to assume that patients will soon use this technology for preoperative education. Therefore, we sought to determine the accuracy of answers to frequently asked questions (FAQs) pertaining to total knee arthroplasty (TKA).

Ten FAQs were posed to the chatbot during a single online interaction with no follow-up questions or repetition. All 10 FAQs were analyzed for accuracy using an evidence-based approach. Answers were then rated as “excellent response not requiring clarification,” “satisfactory requiring minimal clarification,” satisfactory requiring moderate clarification,” or “unsatisfactory requiring substantial clarification.”

Of the 10 answers given by the chatbot, none received an “unsatisfactory” rating with the majority either requiring minimal (5) or moderate (4) clarification. While many answers required nuanced clarification, overall, answers tended to be unbiased and evidence-based, even when presented with controversial subjects.

The chatbot does an excellent job of providing basic, evidence-based answers to patient FAQs prior to TKA. These data were presented in a manner that will be easily comprehendible by most patients and may serve as a useful clinical adjunct in the future.

The study's investigation was performed at Vanderbilt University Medical Center, Nashville, TN.

This study was exempted from the IRB approval process.

Received: 14 December 2023

Accepted: 08 February 2024

Article published online:
05 March 2024

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