背景:在过去的几年中,人们对基于人工智能(AI)的临床决策支持系统(CDSS)的开发越来越感兴趣。然而,在实践中成功实施此类系统存在障碍,包括缺乏接受这些系统。参与式方法旨在让未来的用户参与设计更容易接受的应用程序,如CDSS,可行,从根本上与实践更相关。基于人工智能技术的发展,然而,挑战用户参与的过程和相关方法。
目的:这篇综述的目的是总结和介绍主要方法,方法,实践,以及涉及临床医生的基于AI的决策支持系统的参与性研究和开发的具体挑战。
方法:此范围审查将遵循JoannaBriggsInstitute的范围审查方法。通过PubMed在MEDLINE数据库中搜索合格研究;ACM数字图书馆;护理和相关健康累积指数;和PsycInfo。以下搜索筛选器,适应每个数据库,使用:2012年1月1日至2023年10月31日期间,仅英语和德语研究,抽象可用。范围审查将包括涉及开发的研究,驾驶,实施,以及基于人工智能的CDSS(混合和数据驱动的人工智能方法)的评估。临床工作人员必须以参与的方式参与。数据检索将伴随着手动灰色文献检索。然后将潜在出版物导出到参考管理软件中,和重复将被删除。之后,获得的一组论文将被转移到系统的审查管理工具中。所有出版物将被筛选,提取,并分析:标题和摘要筛选将由两名独立审稿人进行。分歧将通过让第三名审稿人参与来解决。将使用为研究准备的数据提取工具提取数据。
结果:该范围审查方案于2023年3月11日在开放科学框架上注册。当时已经开始了全文筛选。在按标题和摘要筛选的3118项研究中,31个被包括在全文筛选中。计划在2024年第二和第三季度进行数据收集和分析以及手稿准备。手稿应在2024年底提交。
结论:这篇综述将描述基于AI的决策支持系统的参与式开发的知识现状。目的是确定知识差距并提供研究动力。它还旨在为决策者和从业人员提供相关信息。
■DERR1-10.2196/58185。
BACKGROUND: In the last few years, there has been an increasing interest in the development of artificial intelligence (AI)-based clinical decision support systems (CDSS). However, there are barriers to the successful implementation of such systems in practice, including the lack of acceptance of these systems. Participatory approaches aim to involve future users in designing applications such as CDSS to be more acceptable, feasible, and fundamentally more relevant for practice. The development of technologies based on AI, however, challenges the process of user involvement and related methods.
OBJECTIVE: The aim of this review is to summarize and present the main approaches, methods, practices, and specific challenges for participatory research and development of AI-based decision support systems involving clinicians.
METHODS: This scoping review will follow the Joanna Briggs Institute approach to scoping reviews. The search for eligible studies was conducted in the databases MEDLINE via PubMed; ACM Digital Library; Cumulative Index to Nursing and Allied Health; and PsycInfo. The following search filters, adapted to each database, were used: Period January 01, 2012, to October 31, 2023, English and German studies only, abstract available. The scoping review will include studies that involve the development, piloting, implementation, and evaluation of AI-based CDSS (hybrid and data-driven AI approaches). Clinical staff must be involved in a participatory manner. Data retrieval will be accompanied by a manual gray literature search. Potential publications will then be exported into reference management software, and duplicates will be removed. Afterward, the obtained set of papers will be transferred into a systematic review management tool. All publications will be screened, extracted, and analyzed: title and abstract screening will be carried out by 2 independent reviewers. Disagreements will be resolved by involving a third reviewer. Data will be extracted using a data extraction tool prepared for the study.
RESULTS: This scoping review protocol was registered on March 11, 2023, at the Open Science Framework. The full-text screening had already started at that time. Of the 3,118 studies screened by title and abstract, 31 were included in the full-text screening. Data collection and analysis as well as manuscript preparation are planned for the second and third quarter of 2024. The manuscript should be submitted towards the end of 2024.
CONCLUSIONS: This review will describe the current state of knowledge on participatory development of AI-based decision support systems. The aim is to identify knowledge gaps and provide research impetus. It also aims to provide relevant information for policy makers and practitioners.
UNASSIGNED: DERR1-10.2196/58185.