评估由人工智能模型生成的以患者为中心的出院药物指令的安全性
Michael Tang1, Kristina Markova1, Kristian Stanceski1
1School of Medical Sciences, Faculty of Medicine and Health, The University of Sydney, Australia.
International journal of medical informatics
|January 15, 2026
概括
人工智能生成的药物说明显示了以患者为中心的沟通的潜力,但也引发了公平问题. 安全问题在老年,复杂的患者和具有特定保险的患者中更为普遍,突出了需要仔细审核的需要.
科学领域:
- 医疗保健中的人工智能
- 医疗信息学 医疗信息学
- 患者安全 患者安全
背景情况:
- 人工智能 (AI) 有望在医疗保健中加强以患者为中心的沟通.
- 然而,人工智能工具在不同患者群体中的公平性仍未得到充分探索.
- 这项研究调查了AI生成的医院出院药物信息的公平性和准确性.
研究的目的:
- 评估人工智能生成的药物说明的完整性和准确性.
- 评估不同患者人口统计学 (年龄,复杂性,保险) 的AI工具性能潜在差异.
- 识别与人工智能生成的患者药物信息相关的安全问题.
主要方法:
- 利用GPT-4o从140份医院出院摘要 (MIMIC数据库) 中生成以患者为中心的药物说明.
- 临床专家评估了药物完整性,遵守通用药物表 (UMS) 格式,并确定了安全问题.
- 统计分析检查了不同年龄组,患者复杂性和保险类型的结果差异.
主要成果:
- 人工智能成功地包含了大多数药物 (95%),很少添加外来药物.
- 很大一部分药物没有以通用药物表 (UMS) 格式呈现 (中位数为22.5%).
- 在69.3%的病例中发现了潜在的安全问题,老年,更复杂的患者和具有特定保险类型的患者的患病率更高.
结论:
- 人工智能生成的药物说明在不同患者群体的安全性上表现出差异.
- 较老,更复杂的患者和某些保险类型的患者遇到更多的安全问题.
- 进一步的研究,本地化试验和持续的审计对于在患者沟通中公平安全地实施人工智能至关重要.
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