IntroductionThe purpose of this study was to explore nurses' perspectives on Machine Learning Clinical Decision Support (ML CDS) design, development, implementation, and adoption.DesignQualitative descriptive study.MethodsNurses (n = 17) participated in semi‐structured interviews. Data were transcribed, coded, and analyzed using Thematic analysis methods as described by Braun and Clarke.ResultsFour major themes and 14 sub‐themes highlight nurses' perspectives on autonomy in decision‐making, the influence of prior experience in shaping their preferences for use of novel CDS tools, the need for clarity in why ML CDS is useful in improving practice/outcomes, and their desire to have nursing integrated in design and implementation of these tools.ConclusionThis study provided insights into nurse perceptions regarding the utility and usability of ML CDS as well as the influence of previous experiences with technology and CDS, change management strategies needed at the time of implementation of ML CDS, the importance of nurse‐perceived engagement in the development process, nurse information needs at the time of ML CDS deployment, and the perceived impact of ML CDS on nurse decision making autonomy.Clinical RelevanceThis study contributes to the body of knowledge about the use of AI and machine learning (ML) in nursing practice. Through generation of insights drawn from nurses' perspectives, these findings can inform successful design and adoption of ML Clinical Decision Support.

中文翻译：

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护士对机器学习临床决策支持的设计、实施和采用的看法：描述性定性研究


简介本研究的目的是探讨护士对机器学习临床决策支持 (ML CDS) 设计、开发、实施和采用的看法。设计定性描述性研究。方法护士 ( n = 17) 参加了半结构化访谈。使用 Braun 和 Clarke 描述的主题分析方法对数据进行转录、编码和分析。 结果 四个主要主题和 14 个子主题突出了护士对决策自主权的看法，以及先前经验对形成他们使用护士的偏好的影响。新颖的 CDS 工具，需要澄清为什么 ML CDS 对于改善实践/结果有用，以及他们希望将护理纳入这些工具的设计和实施中。结论这项研究深入了解了护士对 ML CDS 的实用性和可用性的看法以及以前的技术和 CDS 经验的影响、实施 ML CDS 时所需的变更管理策略、护士感知参与开发过程的重要性、ML CDS 部署时的护士信息需求，以及ML CDS 对护士决策自主权的感知影响。临床相关性本研究有助于丰富有关在护理实践中使用 AI 和机器学习 (ML) 的知识体系。通过从护士的角度得出见解，这些发现可以为 ML 临床决策支持的成功设计和采用提供信息。