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在败血症中基于人工智能的临床决策支持系统的用户导向要求:多方法研究项目协议
Pascal Raszke1, Godwin Denk Giebel1, Carina Abels1
1Institute for Health Care Management and Research, University of Duisburg-Essen, Essen, Germany.
JMIR research protocols
|January 30, 2025
概括
本研究确定了人工智能临床决策支持系统 (CDSS) 采用的障碍和解决方案. 它开发了一个以用户为中心的败血症CDSS要求配置文件,以改善医疗保健整合.
科学领域:
- 医疗信息学 医疗信息学
- 医疗保健中的人工智能
- 临床决策支持系统 临床决策支持系统
背景情况:
- 基于人工智能 (AI) 的临床决策支持系统 (CDSS) 有望改善患者护理,但在标准临床实践中采用率较低.
- 实现AI-CDSS的障碍往往来自于非用户导向的开发和集成挑战,导致用户接受度降低.
研究的目的:
- 确定影响开发和实施基于AI的CDSS的挑战和解决方案.
- 通过创建面向用户的需求配置文件,以败血症管理为例,增强用户对AI-CDSS的接受度.
主要方法:
- 一种多方法方法,结合范围审查,与临床医生聚焦小组和利益相关者访谈.
- 开发一个调查与离散选择实验 (DCE) 针对有败血症专业知识的医生.
- 创建基于AI的CDSS的需求配置文件,然后在专家圆桌会议上评估的政策建议.
主要成果:
- 该研究概述了AI-CDSS开发和实施的障碍和解决方案.
- 已经开发了一个面向用户的AI-CDSS针对败血症的需求配置文件.
- 范围审查结束;定性模块分析;调查和DCE启动.
结论:
- 这项研究提出了一个新的,全面的以用户为导向的毒症AI-CDSS.
- 由此产生的建议旨在减少AI-CDSS开发和实施的障碍.
- 这些发现有可能促进AI-CDSS的长期整合到常规医疗保健中.
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