评估医疗保健专业人员对临床工作流程中的新系统的看法:基于患者安全的共识定性研究的系统工程倡议
Ye-Eun Park1, Minsu Ock2, Jae-Ho Lee1,3
1Department of Information Medicine, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea.
前线专业人士预计人工智能临床决策支持系统 (CDSS) 可以改善手术输血订单,但也引起了对工作流集成和验证负担的担忧. 成功的采用需要用户的信任和组织的支持,以确保安全实施.
科学领域:
- 医疗保健信息学 医疗保健信息学
- 人工智能在医学中的应用
- 患者安全 患者安全
背景情况:
- 支持人工智能的临床决策支持系统 (CDSS) 越来越多地集成到电子健康记录 (EHR) 中.
- 引入CDSS可以破坏工作流程并引发安全问题,特别是在手术输血等关键领域.
- 关于前线专业人员在部署之前对这些系统的预期,存在有限的定性数据.
研究的目的:
- 质量检查预期的临床,组织和工作流的影响,实施一个特定的AI-enabledCDSS (pMSBOS-TS) 进行手术血液订购.
- 在大规模部署个性化最大手术血顺序计划-胸部手术 (pMSBOS-TS) 之前收集见解.
主要方法:
- 一致的定性研究涉及14个多学科的医疗保健专业人员.
- 在试点会议后,两个半结构化的焦点小组进行了试点会议.
- 使用系统工程倡议患者安全 (SEIPS) 框架进行分析,重点是人,环境,工具和任务.
- 对输血过程的基于任务和工作流程的分析以及对成员的有效性检查.
主要成果:
- 参与者预计,如果AI CDSS可靠,并集成到EHR工作流程中,血液订购的变化将减少.
- 担忧包括增加验证负担,在不寻常情况下的系统限制,以及单位与血液银行之间的通信问题.
- 组织文化,治理和物流对于确定系统是否减少或增加工作量和浪费至关重要.
结论:
- 成功采用人工智能支持的输血CDSS取决于社会技术准备,包括用户信任,工作流适应和组织支持,而不仅仅是预测性能.
- 结果为分阶段实施,培训和治理提供了基于实践的见解,以安全地将预测性输血CDSS集成到外科工作流程中.
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