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

JOSPT methods Pub Date : 2025-06-01 Epub Date: 2025-04-28 DOI:10.2519/josptmethods.2025.0151

Mark Vorensky, Daniel Peredo, Richard Ferraro, Emily Paris, Asma Mohammadi, Paul Spano, Smita Rao

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Abstract

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.

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提高ChatGPT在骨科中的表现：使用CRISPE框架的机会。

ChatGPT已越来越多地应用于临床实践、教育和研究。在骨科研究中，ChatGPT在临床决策中的准确性一直是主要关注的问题，其结果的准确率从33%到80%不等。ChatGPT的不准确性可能对临床医生、受训人员或患者有害，因为他们的回答似乎是可信的，被信任的，并采取了行动。骨科研究的一个关键限制是缺乏结构化提示工程，这严重影响了ChatGPT的性能。CRISPE（能力/角色、洞察力、陈述、个性、实验）框架提供了一种系统的方法来精炼提示和提高反应的准确性。本观点将CRISPE框架应用于最近的骨科研究，并强调了在ChatGPT中优化提示的机会。虽然需要研究来验证和完善骨科中的快速工程工具，但这些方法有可能提高ChatGPT响应的准确性和可靠性，并在骨科实践、教育和研究中成为有价值的工具。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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JOSPT methods

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