文档
术语
范围(计算机科学)
平面图(考古学)
护理计划
护理部
医学
护理诊断
肺癌
质量(理念)
护理
计算机科学
历史
病理
考古
语言学
哲学
认识论
医学诊断
程序设计语言
作者
Fabiana Cristina Dos Santos,Lisa G. Johnson,Olatunde O Madandola,K. Priola,Yingwei Yao,Tamara Gonçalves Rezende Macieira,Gail M. Keenan
标识
DOI:10.1093/jamia/ocae116
摘要
Abstract Objective Our article demonstrates the effectiveness of using a validated framework to create a ChatGPT prompt that generates valid nursing care plan suggestions for one hypothetical older patient with lung cancer. Method This study describes the methodology for creating ChatGPT prompts that generate consistent care plan suggestions and its application for a lung cancer case scenario. After entering a nursing assessment of the patient's condition into ChatGPT, we asked it to generate care plan suggestions. Subsequently, we assessed the quality of the care plans produced by ChatGPT. Results While not all the suggested care plan terms (11 out of 16) utilized standardized nursing terminology, the ChatGPT-generated care plan closely matched the gold standard in scope and nature, correctly prioritizing oxygenation and ventilation needs. Conclusion Using a validated framework prompt to generate nursing care plan suggestions with ChatGPT demonstrates its potential value as a decision support tool for optimizing cancer care documentation.
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