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Navigating clinical guidelines can be complex for real-time health care decision making. Our study evaluates the chat generative prerained transformer (ChatGPT)-4 in improving responses to clinical questions by integrating guidelines on Clostridioides difficile infection and colon polyp surveillance. We assessed ChatGPT-4’s responses to questions before and after guideline integration, noting a clear improvement in accuracy. ChatGPT-4 provided guideline-aligned answers consistently. Further analysis showed its ability to summarize information from conflicting guidelines, highlighting its utility in complex clinical scenarios. The findings suggest that large language models such as ChatGPT-4 can enhance clinical decision making and patient education by providing quick, conversational, and accurate responses. This approach opens a path for using artificial intelligence to deliver reliable responses in health care, supporting clinicians in real-time decision making and improving patient care.