基于人工智能的临床决策支持系统参与式设计的挑战和促进方法:范围审查议定书
Tabea Rambach1, Patricia Gleim2, Sekina Mandelartz2
1Care & Technology Lab, Furtwangen University, Furtwangen, Germany.
JMIR research protocols
|September 5, 2024
概括
本综述探讨了开发基于人工智能 (AI) 的临床决策支持系统 (CDSS) 的参与式方法. 它确定了涉及临床医生的挑战和方法,以提高人工智能工具在实践中的接受度和相关性.
科学领域:
- 医疗信息学 医疗信息学
- 医疗保健中的人工智能
- 人与计算机的交互
背景情况:
- 对基于人工智能的临床决策支持系统 (CDSS) 的日益增长的兴趣面临实施障碍,特别是用户接受.
- 参与式方法对于设计AI-CDSS至关重要,这些方法是可接受的,可行的,并且与临床实践相关.
- 人工智能开发对传统的用户参与方法提出了独特的挑战.
研究的目的:
- 系统地审查和综合方法,方法,实践和挑战,参与基于AI的CDSS的参与性研究和开发,涉及临床医生.
- 识别知识缺口,并刺激该领域的进一步研究.
- 为决策者和医疗保健从业人员提供AI-CDSS有效的参与策略的信息.
主要方法:
- 根据乔安娜·布里格斯研究所的方法进行范围审查.
- 在MEDLINE,ACM数字图书馆,CINAHL和PsycInfo (2012-2023) 中进行的搜索,包括英语和德语研究.
- 包括关于AI-CDSS开发,试点,实施和评估的研究,其中包括临床工作人员的参与.
主要成果:
- 在开放科学框架 (2023年3月) 上注册的协议.
- 在对3,118项研究的初步选中,确定了31项需要进行全文审查.
- 数据收集,分析和手稿准备计划于2024年,预计将在年底之前提交.
结论:
- 该审查将概述参与式AI-CDSS开发的当前知识格局.
- 它旨在突出需要进一步调查的领域,并为利益相关者提供实际见解.
- 研究结果将通过以用户为中心的设计,支持AI-CDSS在临床环境中的有效整合.
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