试验将护理记录转换为简化和结构化的信息,使用聊天GPT-3.5
Ryoma Seto1, Masatoshi Ishikawa1, Hirona Okudaira2
1Healthcare Research Institute, Tokyo Healthcare University, Tokyo, Japan.
Studies in health technology and informatics
|July 25, 2024
概括
这项研究探讨了使用ChatGPT-3.5将冗长的护理记录转换为简洁的"子弹"格式. 人工智能展示了关键词提取的潜力,有助于制定标准化的护理文档.
科学领域:
- 医疗信息学 医疗信息学
- 护理信息学 护理信息学
- 医疗保健中的人工智能
背景情况:
- 在日本,过长的护理记录是一个社会挑战.
- 需要简洁的护理文档,以实现语音识别和国际合作.
- 当前的描述性记录阻碍了有效的信息检索和工作流程.
研究的目的:
- 评估将描述性的护理记录转换为简洁的"标签"格式的可行性,使用ChatGPT-3.5.5.
- 识别用于转换的护理记录中的典型信息来源和情况.
- 评估人工智能在简化护理文档方面的潜力.
主要方法:
- 分析了96,000个匿名的,描述性地写的护理记录.
- 使用ChatGPT-3.5将已识别的记录部分转换为"标记"摘要.
- 专注于常见的护理场景,如术后状态,生命体征和患者监测.
主要成果:
- 聊天GPT-3.5显示了可用的功能,用于提取关键字的"子弹"护理记录.
- 转换过程强调了人工智能在简化复杂临床信息方面的实用性.
- 该研究确定了创建标准化护理笔记的关键元素.
结论:
- 聊天GPT-3.5可以作为一个有价值的工具,用于生成简洁的护理记录关键字.
- 过渡到"子弹"护理记录是通过人工智能辅助转换促进的.
- 这种方法支持采用标准化术语,例如"护理观察和行动标准术语 (STerNOA)".
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