基于医院的预测风险工具的图形用户界面开发:共同设计研究协议
Nicholas Marlow1, Marion Eckert1, Greg Sharplin1
1University of South Australia, Adelaide, Australia.
JMIR research protocols
|August 31, 2023
概括
这项研究使用了共同设计来制定人工智能 (AI) 支持的风险预测工具的图形用户界面 (GUI) 的建议. 吸引卫生专业人员确保人工智能工具可用,并与临床工作流程保持一致,以便更好地采用.
科学领域:
- 医疗信息学 医疗信息学
- 人与计算机的交互
- 医疗保健中的人工智能
背景情况:
- 共同设计研究对于开发以用户为中心的健康技术至关重要.
- 让最终用户参与人工智能工具的设计过程,有助于推广采用和有效使用.
- 卫生干预措施的美学和功能设计选择最好由预期的用户决定.
研究的目的:
- 确定卫生专业人员对支持人工智能的风险预测工具图形用户界面 (GUI) 的建议.
- 收集医疗保健专业人员的设计和采用建议,用于AI风险预测工具的GUI.
主要方法:
- 一个三阶段的共同设计研究方法,涉及36名卫生专业人员.
- 六个代研讨会活动 (使用上下文,通知者,格式,AI调查-Likert,原型,AI调查-书面) 在研讨会中重复.
- 以NASSSS框架为指导的定性 (主题分析,互动性框架) 和定量 (描述性统计) 数据分析.
主要成果:
- 在澳大利亚和新西兰临床试验注册处申请项目注册 (#384098).
- 获得了南澳大利亚卫生与福利部和南澳大利亚大学的人类研究伦理审批.
- 最终设计建议预计将在2024年初到中期完成;手稿提交计划于2024年中期.
结论:
- 为用户采用和整合到现有工作实践中设计干预措施对于他们的成功至关重要.
- 共设计确保人工智能工具满足最终用户对美学和功能的需求,与临床工作流程保持一致.
- 如果不能将干预措施与用户实践保持一致,可能会导致不喜欢甚至危险的结果.
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