在精神卫生保健中使用AI驱动的报告生成工具:商业工具的回顾
Ayoub Bouguettaya1, Victoria Team2, Elizabeth M Stuart3
1Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, CA, United States; School of Nursing and Midwifery, Monash University, Melbourne, Victoria, Australia.
General hospital psychiatry
|March 15, 2025
概括
在心理健康 (EHR) 中,人工智能驱动的笔记写作提供了好处,但缺乏透明度. 对于伦理和可靠的临床实施大型语言模型 (LLM) 需要进一步的标准化.
科学领域:
- 临床信息学 临床信息学
- 健康 人工智能 伦理学
- 心理健康技术 技术 心理健康技术
背景情况:
- 人工智能 (AI) 系统,特别是大型语言模型 (LLM),在临床环境中越来越多地用于电子健康记录 (EHR) 笔记写作等任务.
- 人工智能在心理健康电子健康记录中的整合旨在减少临床医生的文档负担.
研究的目的:
- 开发和应用心理健康电子健康专业人员的评估尺度,使用LLM进行笔记写作.
- 评估这些人工智能驱动系统的功能,安全性和伦理考虑.
主要方法:
- 分析在公司网站上提供的供应商产品信息.
- 直接向供应商询问,收集有关LLM功能,安全和道德实践的详细信息.
主要成果:
- 大多数供应商提供了关于数据保护,隐私,多平台可用性,患者访问,更新和有意义使用合规性的良好信息.
- 关于法学士培训,使用的具体模型,偏见纠正和证据基础评估的信息经常缺失.
- 供应商通常披露了针对定制报告和副驾驶功能的LLM功能.
结论:
- 虽然LLM增强的EHR显示出心理健康文档的潜力,但关于LLM的具体情况和偏见缓解存在显著的透明度不足.
- 在报告LLM信息方面,提高透明度和标准化对于道德实施和可靠性至关重要.
- 为未来的发展提出了建议,以确保人工智能驱动的临床工具的安全性,伦理性和质量.
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