Improving ChatGPT's Performance in Orthopedics: Opportunities Using the CRISPE Framework

ChatGPT has been increasingly used in clinical practice, education, and research. In orthopedic research, ChatGPT's accuracy in clinical decision-making has been a major concern, with results ranging from 33% to 80% accuracy. Inaccuracies from ChatGPT can be harmful to clinicians, trainees, or patients when responses appear plausible, are trusted, and acted upon. A critical limitation in orthopedic research is the lack of structured prompt engineering, which significantly impacts ChatGPT's performance. The CRISPE (Capacity/Role, Insight, Statement, Personality, Experiment) framework offers a systematic approach to refining prompts and improving response accuracy. This Viewpoint applies the CRISPE framework to recent orthopedic research and highlights opportunities to optimize prompts in ChatGPT. While research is needed to validate and refine prompt engineering tools in orthopedics, these methods have the potential to enhance the accuracy and reliability of ChatGPT's responses and serve as valuable tools in orthopedic practice, education, and research.