基于人工智能的生成护理诊断和文档推使用虚拟患者电子护理记录数据.
Hongshin Ju1,2, Minsul Park1,3, Hyeonsil Jeong1
1DKMediInfo, Hwaseong, Korea.
Healthcare informatics research
|May 19, 2025
概括
生成型人工智能 (AI) 显著减少了护理文档的时间,减少了40%,提高了效率. 虽然人工智能显示出前景,但需要进一步开发以提高准确性以实现无临床整合.
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:
- 护理文档约占护士时间的30%,影响工作流程和患者安全.
- 优化文档效率对于现代医疗保健环境至关重要.
- 传统的电子护理记录 (ENR) 在护理人员的时间管理方面带来了挑战.
研究的目的:
- 将传统护理文档的效率与基于人工智能的生成系统进行比较.
- 评估人工智能对减少文档制作时间和提高准确性的影响.
- 评估人工智能辅助护理文档的整体效率和质量.
主要方法:
- 40名至少有6个月经验的护士参与了这项研究.
- 预评估阶段使用传统的ENR,随后使用生成AI系统 (基于ChatGPT 4.0的SmartENR) 进行后评估阶段.
- 文档质量使用5分级准确度,全面性,可用性,易用性和流利性的评价.
主要成果:
- 人工智能辅助的文档减少了大约40%的时间 (467.18s传统与182.68s人工智能).
- 人工智能生成的文档在易用性 (4.80/5) 和流利性 (4.50/5) 方面获得了高分.
- 精度 (3.62/5) 和可用性 (3.50/5) 的分数表明AI模型需要改进的领域.
结论:
- 生成型人工智能可以大大降低护理文档工作量,提高效率.
- 人工智能系统有可能提高临床实践中的护理文档质量和效率.
- 进一步改进人工智能模型是必要的,以优化准确性,并促进无集成到临床工作流程.
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