Real-time analysis for intensive care: development and deployment of the artemis analytic system.

Marion Blount, Maria R Ebling, J Mikael Eklund, Andrew G James, Carolyn McGregor, Nathan Percival, Kathleen P Smith, Daby Sow
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引用次数: 136

Abstract

The lives of many thousands of children born premature or ill at term around the world have been saved by those who work within neonatal intensive care units (NICUs). Modern-day neonatologists, together with nursing staff and other specialists within this domain, enjoy modern technologies for activities such as financial transactions, online purchasing, music, and video on demand. Yet, when they move into their workspace, in many cases, they are supported by nearly the same technology they used 20 years ago. Medical devices provide visual displays of vital signs through physiological streams such as electrocardiogram (ECG), heart rate, blood oxygen saturation (SpO(2)), and respiratory rate. Electronic health record initiatives around the world provide an environment for the electronic management of medical records, but they fail to support the high-frequency interpretation of streaming physiological data. We have taken a collaborative research approach to address this need to provide a flexible platform for the real-time online analysis of patients' data streams to detect medically significant conditions that precede the onset of medical complications. The platform supports automated or clinician-driven knowledge discovery to discover new relationships between physiological data stream events and latent medical conditions as well as to refine existing analytics. Patients benefit from the system because earlier detection of signs of the medical conditions may lead to earlier intervention that may potentially lead to improved patient outcomes and reduced length of stays. The clinician benefits from a decision support tool that provides insight into multiple streams of data that are too voluminous to assess with traditional methods. The remainder of this article summarizes the strengths of our research collaboration and the resulting environment known as Artemis, which is currently being piloted within the NICU of The Hospital for Sick Children (SickKids) in Toronto, Ontario, Canada. Although the discussion in this article focuses on a NICU, the technologies can be applied to any intensive care environment.

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重症监护的实时分析:artemis分析系统的开发和部署。
世界各地新生儿重症监护病房(NICUs)的工作人员挽救了成千上万早产或足月患病儿童的生命。现代新生儿学家,以及护理人员和该领域的其他专家,享受现代技术的活动,如金融交易,在线购物,音乐和视频点播。然而,当他们进入自己的工作空间时,在许多情况下,他们使用的是与20年前几乎相同的技术。医疗设备通过诸如心电图(ECG)、心率、血氧饱和度(SpO(2))和呼吸速率等生理流提供生命体征的视觉显示。世界各地的电子健康记录倡议为医疗记录的电子管理提供了一个环境,但它们无法支持流式生理数据的高频解释。我们采取了一种合作研究的方法来解决这一需求,为实时在线分析患者数据流提供一个灵活的平台,以在医疗并发症发生之前检测医学上的重要情况。该平台支持自动化或临床驱动的知识发现,以发现生理数据流事件与潜在医疗状况之间的新关系,并改进现有的分析。患者受益于该系统,因为早期发现医疗状况的迹象可能导致早期干预,这可能会改善患者的治疗效果并缩短住院时间。临床医生受益于决策支持工具,该工具提供了对多种数据流的洞察力,这些数据流过于庞大,无法用传统方法进行评估。本文的其余部分总结了我们研究合作的优势和由此产生的被称为Artemis的环境,该环境目前正在加拿大安大略省多伦多病童医院(SickKids)的新生儿重症监护室进行试点。虽然本文的讨论主要集中在新生儿重症监护室,但这些技术可以应用于任何重症监护环境。
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来源期刊
IEEE Engineering in Medicine and Biology Magazine
IEEE Engineering in Medicine and Biology Magazine 工程技术-工程:生物医学
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>12 weeks
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