Shan Zhang, Shu Ding, Wei Cui, Xiangyu Li, Jun Wei, Ying Wu
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引用次数: 0
摘要
目的：评估人工智能辅助谵妄预防和管理（AI-AntiDelirium）对提高重症监护病房（ICU）护士对谵妄指南的依从性的影响。研究方法/设计：于2022年11月至2023年6月间，进行整群随机对照试验。环境：干预组共招募了38名护士，而对照组招募了42名护士，来自北京两家医院的6个icu，比较了使用AI-AntiDelirium和对照组的护士依从性和认知负荷。主要结局指标：AI-AntiDelirium量身定制谵妄预防或治疗干预措施，以解决患者特定的危险因素。谵妄干预的依从率是主要终点。其他终点是对危险因素评估、ICU谵妄评估和护士认知负荷的依从性。采用重复测量方差分析探讨时间、组、时间×组交互作用对重复测量变量（如依从性、认知负荷）的影响。结果：本研究共分析了1040个护理日。AI-AntiDelirium组护士对谵妄干预的依从性高于对照组（75% vs. 58%）， P结论：本研究支持AI-AntiDelirium在增强护士对循证、个性化谵妄干预的依从性以及减少外来认知负荷方面的有效性。对临床实践的启示：护理管理者应采用护士主导的系统来提高ICU护士对护理干预的依从性。
Evaluating the effectiveness of a clinical decision support system (AI-Antidelirium) to improve Nurses' adherence to delirium guidelines in the intensive care unit.
Objectives: To evaluate the impact of Artificial Intelligence Assisted Prevention and Management for Delirium (AI-AntiDelirium) on improving adherence to delirium guidelines among nurses in the intensive care unit (ICU).
Research methodology/design: Between November 2022 and June 2023, A cluster randomized controlled trial was undertaken.
Setting: A total of 38 nurses were enrolled in the interventional arm, whereas 42 nurses were recruited for the control arm in six ICUs across two hospitals in Beijing, comparing nurses' adherence and cognitive load in units that use AI-AntiDelirium or the control group.
Main outcome measures: The AI-AntiDelirium tailored delirium preventive or treated interventions to address patients' specific risk factors. The adherence rate of delirium interventions was the primary endpoint. The other endpoints were adherence to risk factors assessment, ICU delirium assessment, and nurses' cognitive load. The repeated measures analysis of variance was utilized to explore the influence of time, group, and time × group interaction on the repeated measurement variable (e.g., adherence, cognitive load).
Results: A cumulative total of 1040 nurse days were analyzed for this study. The adherence to delirium intervention of nurses in AI-AntiDelirium groups was higher than control units (75 % vs. 58 %, P < 0.01). When compared to control groups, AI-AntiDelirium was found to be significantly effective in both decreasing extraneous cognitive load (P < 0.01) and improving germane cognitive load (P < 0.01).
Conclusions: This study supports the effectiveness of AI-AntiDelirium in enhancing nurses' adherence to evidence-based, individualized delirium intervention and also reducing extraneous cognitive load.
Implications for clinical practice: A nurse-led systemshould be applied by nursing administrators to improve compliance with nursing interventions among ICU nurses.
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