生成型人工智能总结以促进ED转让
Nicholas Genes1, Gregory Simon1, Christian Koziatek1
1Ronald O. Perelman Department of Emergency Medicine, NYU Grossman School of Medicine, New York, United States.
Applied clinical informatics
|August 12, 2025
概括
生成型人工智能在总结紧急情况部门 (ED) 向住院团队的交付方面表现有前途. 虽然AI总结通常是准确和有用的,但需要改进以解决遗漏并确保患者安全.
科学领域:
- 医疗信息学 医疗信息学
- 医疗保健中的人工智能
- 临床交流 临床沟通
背景情况:
- 紧急部门 (ED) 到住院患者的交接非常重要,但容易出现错误.
- 生成型人工智能 (AI) 为简洁的临床数据总结提供了潜力.
- 人工智能可以提高ED交付的准确性和效率.
研究的目的:
- 评估人工智能生成的ED交付摘要的准确性,临床实用性和安全性.
- 确定影响AI总结有效性的患者和访问因素.
- 描述AI错误模式以指导实施.
主要方法:
- 在一个城市学术ED的探索性研究 (2024年2月至4月).
- 符合HIPAA标准的GPT-4模型使用IPASS框架生成了ED-to-inpatient摘要.
- ED提供者通过轮班调查评估了总结的准确性,有用性和安全性.
主要成果:
- 在50个案例中,质量和实用性的中位数为4/5 .
- 安全问题 (遗漏,错误描述) 发生在6%的案例中.
- 咨询状态影响了实用性;临床医生注意到关于患者稳定性的遗漏和分歧.
结论:
- 人工智能提供者在循环中的模型证明了临床可接受性.
- 需要改进的领域包括解决数据遗漏和表征准确性的问题.
- 未来的研究应该包括接受者反和AI优化临床结果.
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