当沉默信号安全时:在人工智能支持的处方验证中治理和责任
Esteban Zavaleta-Monestel1, Jeaustin Mora-Jiménez2, Sebastián Arguedas-Chacón1
1Health Research Department, Hospital Clinica Biblica, San Jose, CRI.
Cureus
|March 13, 2026
概括
处方验证中的人工智能 (AI) 可以提高效率,但可能会将安全性从临床判断转移到对算法的被动依赖. 持续监测和治理对于管理AI相关的药物安全风险至关重要.
科学领域:
- 医疗信息学 医疗信息学
- 临床药房 临床药房
- 医疗保健中的人工智能
背景情况:
- 人工智能 (AI) 越来越多地用于处方验证,以选药品订单并优先考虑药剂师的审查.
- 人工智能系统可以抑制或降低低风险警报的优先级,从而潜在地提高效率并检测处方风险.
研究的目的:
- 分析人工智能支持的处方验证所带来的挑战和影响,特别是关于安全转换和问责制.
- 倡导强有力的治理框架,以便在药物安全方面负责任地整合人工智能.
主要方法:
- 这篇社论回顾了当前的文献,并讨论了与处方验证中的AI相关的关键问题.
- 它检查了诸如自动化偏差,数据漂移和分布式临床责任等概念.
- 还讨论了传统人工智能验证方法的局限性.
主要成果:
- 人工智能支持的处方验证,特别是警报抑制,可能会将药物安全性从积极的临床判断转移到基于算法输出的被动推断.
- 这种过渡重新分配而不是消除安全风险,需要转向持续监控和治理.
- 传统的验证方法不足以在临床实践中持续评估人工智能系统.
结论:
- 人工智能在药物安全方面的负责任整合需要解决诸如自动化偏差和数据转移等挑战.
- 有效的治理框架对于澄清问责制,维护人类判断和确保持续的AI系统评估至关重要.
- 将处方验证视为社会技术活动是推动医疗保健安全推进人工智能的关键.
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