Nursing and precision predictive analytics monitoring in the acute and intensive care setting: An emerging role for responding to COVID-19 and beyond.
Nursing and precision predictive analytics monitoring in the acute and intensive care setting: An emerging role for responding to COVID-19 and beyond.
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DOI：
10.1016/j.ijnsa.2021.100019
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发表时间：
2021-11
影响因子：
--
通讯作者：
Moorman LP
中科院分区：
文献类型：
--
作者：
Keim-Malpass J;Moorman LP
随着全球对COVID-19的持续应对，护士的任务将是适当地分流患者，应对临床恶化事件，并在超出能力的医疗系统内制定以家庭为中心的护理计划。预测分析监测是一种基于人工智能（AI）的工具，可将流式临床数据转换为患者风险的实时视觉估计，允许在患者处于症状前状态时进行不断发展的敏锐度评估和临床恶化检测。虽然护士处于COVID-19大流行的前线，但使用基于人工智能的预测分析监测可能有助于认知复杂的临床决策任务，并为早期发现有失代偿风险的患者铺平道路。我们必须制定策略和技术，以研究基于人工智能的技术对患者护理结果和临床工作流程的影响。本文概述了护理和精确预测分析监测交叉的关键概念。
As the global response to COVID-19 continues, nurses will be tasked with appropriately triaging patients, responding to events of clinical deterioration, and developing family-centered plans of care within a healthcare system exceeding capacity. Predictive analytics monitoring, an artificial intelligence (AI)-based tool that translates streaming clinical data into a real-time visual estimation of patient risks, allows for evolving acuity assessments and detection of clinical deterioration while the patient is in pre-symptomatic states. While nurses are on the frontline for the COVID-19 pandemic, the use of AI-based predictive analytics monitoring may help cognitively complex clinical decision-making tasks and pave a pathway for early detection of patients at risk for decompensation. We must develop strategies and techniques to study the impact of AI-based technologies on patient care outcomes and the clinical workflow. This paper outlines key concepts for the intersection of nursing and precision predictive analytics monitoring.
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DOI：
10.1186/s13054-015-0950-5
发表时间：
2015-05-20
期刊：
Critical care (London, England)
影响因子：
--
作者：
Douw G;Schoonhoven L;Holwerda T;Huisman-de Waal G;van Zanten AR;van Achterberg T;van der Hoeven JG
通讯作者：
van der Hoeven JG
影响因子：
3.8
作者：
Blackburn, Holly N.;Clark, Matthew T.;Calland, J. Forrest
通讯作者：
Calland, J. Forrest
影响因子：
6.5
作者：
Green, Malcolm;Lander, Harvey;Edelson, Dana
通讯作者：
Edelson, Dana
影响因子：
3.6
作者：
Griffin, M. Pamela;Lake, Douglas E.;Moorman, J. Randall
通讯作者：
Moorman, J. Randall
影响因子：
4.5
作者：
Aboukhalil, Anton;Nielsen, Larry;Clifford, Gari D.
通讯作者：
Clifford, Gari D.