让多学科的临床用户参与设计一个人工智能驱动的图形用户界面,用于重症监护室的不稳定性决策支持
Stephanie Helman1, Martha Ann Terry2, Tiffany Pellathy3
1Department of Acute and Tertiary Care Nursing, University of Pittsburgh, Pittsburgh, Pennsylvania, United States.
Applied clinical informatics
|October 4, 2023
概括
人工智能 (AI) 临床决策支持需要以用户为中心的设计,以获得最佳的临床护理. 多学科的投入对于开发透明,可解释的AI图形用户界面 (GUIs) 至关重要,这些界面支持,而不是取代临床判断.
科学领域:
- 临床信息学 临床信息学
- 医疗保健中的人工智能
- 人与计算机的交互
背景情况:
- 人工智能 (AI) 可以通过临床决策支持来提高关键不稳定性预测和治疗.
- 人工智能产出的面向用户的显示必须为所有临床护理学科的临床思维和工作流程提供便利.
研究的目的:
- 让包括医生,护士从业人员和医生助理在内的多学科用户参与开发图形用户界面 (GUI).
- 优化AI衍生风险得分在用户友好的GUI中呈现的呈现.
主要方法:
- 与23名重症监护室 (ICU) 临床医生 (护士和医疗服务提供者) 组成的焦点组分为两轮.
- 收集了对原型AI风险评分GUI的输入,在轮次之间实施了设计更改.
- 转录被编码,以识别有关GUI设计和可用性的新兴主题.
主要成果:
- 六个主要主题出现了:分析透明度,图形解释性,对实践的影响,趋势综合,决策权重和显示位置.
- 护士优先考虑客观信息和GUI位置,而提供者则专注于可解释性和避免损害学员的批判性思维.
- 所有临床医生都重视综合数据,但对人工智能的决定权持怀疑态度,直到可信度得到确立.
结论:
- 为了在医疗保健中设计有效的AI衍生的GUI,多学科的用户输入至关重要.
- 人工智能决策支持系统必须是透明的,可解释的,最小的破坏性,并作为人类决策的辅助.
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