一个早期的管道框架,用于评估供应商AI解决方案,以支持投资回报率
Charles E Binkley1,2, David Bouslov3, Ali Zaidi3
1Hackensack Meridian Health, Edison, NJ, USA. Charles.binkley@hmhn.org.
NPJ digital medicine
|June 16, 2025
概括
在卫生系统中实施人工智能 (AI) 早期管道治理对于成功至关重要. 一种四个方面的方法确保了战略调整,执行支持,以及对人工智能解决方案的彻底影响和风险评估.
科学领域:
- 医疗信息学 医疗信息学
- 医疗保健中的人工智能
- 临床治理的管理
背景情况:
- 人工智能 (AI) 融入医疗系统提供了重大机遇,但需要强有力的治理.
- 在整个AI生命周期中,从最初的概念到部署和持续的审计,有效的治理至关重要.
研究的目的:
- 提议一个早期的管道治理框架,专门用于供应商开发的医疗保健环境中的AI解决方案.
- 概述一个可扩展的,四个方面的方法来管理AI解决方案在不同规模的卫生系统.
主要方法:
- 该框架强调了四个关键组成部分:战略调整,高管赞助,影响和价值案例评估和风险评估.
- 这些组件被设计为具有适应性,可以根据组织需求同时或顺序实施.
主要成果:
- 拟议的框架为卫生系统提供了一种结构化的方法来管理AI解决方案.
- 可扩展性允许各种医疗保健组织采用,无论规模如何.
- 评估时间的灵活性 (同时或顺序) 支持实际实施.
结论:
- 实施积极主动,早期管道治理框架对于成功采用和管理医疗保健中人工智能解决方案至关重要.
- 概述的四个方面方法为卫生系统提供了一个实用和可扩展的战略,以应对人工智能集成的复杂性.
- 该框架支持知情决策,风险减轻和从人工智能投资中实现价值.
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