基于虚拟患者数据的护理诊断/记录生成AI系统的开发
Dongkyun Lee1,2, Mihyeon Seong2, HongShin Ju2,3,4
1Ajou University College of Nursing.
Studies in health technology and informatics
|July 25, 2024
概括
生成型人工智能可以减少护士重复的电子护理记录任务. 这项在5万条记录上训练的技术在减轻医疗保健专业人员的工作负担方面表现有前途.
科学领域:
- 护理信息学 护理信息学
- 医疗保健中的人工智能
- 临床文档 临床文档
背景情况:
- 重复的电子护理记录任务为护士增加了大量的工作量.
- 有效的临床文档对于患者护理和运营效率至关重要.
- 现有的电子护理记录系统可能无法完全应对数据输入的负担.
研究的目的:
- 调查生成AI的应用,以减少重复的电子护理记录任务.
- 评估生成AI在护理记录创建中的有用性,可用性和可用性.
- 评估生成人工智能的潜力,以减轻护士的工作负担.
主要方法:
- 用5万个护理记录数据点来训练生成AI,包括NANDA,FocusDAR,SOAPIE和叙事格式,利用虚拟患者数据.
- 人工智能模型的性能通过微调技术得到了增强.
- 一个API将生成AI连接到实践电子护理记录系统,由40名经验丰富的护士进行测试.
主要成果:
- 该研究展示了生成人工智能的潜力,可以自动化和简化电子护理记录的创建.
- 护士的反表明了该系统在实践中的潜在实用性和可用性.
- 预计生成性AI的整合将减少用于文档的时间.
结论:
- 生成型人工智能为减少与电子护理记录相关的重复任务提供了可行的解决方案.
- 这项技术有可能大大减轻护士的工作量,允许更直接的病人护理.
- 在医疗保健环境中进一步开发和整合生成AI是有必要的.
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