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Signal processing, human factors, and modelling to support bedside care in the intensive care unit.

机译:信号处理,人为因素和模型支持重症监护室中的床边护理。

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摘要

Medical error causes preventable death in nearly 100,000 patients per year in the US alone. Common sources for error include medication related problems, technical equipment failure, interruptions, complicated and error-prone devices, information overload (providing too much patient data for one person to process effectively), and environmental problems like inadequate lighting or distracting ambient noise.;Intensive care units are one of the riskiest locations in a hospital, with up to 9 reported events per 100 patient days. This risk is in large contrast to anesthesia in the operating rooms. Here much advancement in the area of patient safety has been made in the past, dropping the average risk for anesthesia related death to less than 1 in 200,000 anesthetics---an improvement by a factor of 20 in the past 30 years. Improvements in technology and other innovations contributing to this success now need to be adapted for and implemented in the intensive care unit setting.;Nurses are increasingly regarded as key decision makers within the healthcare team, as they outnumber physicians 4:1. Reducing nurses' workload and improving medical decision making by providing decision support tools can have a significant impact in reducing the chances of medical errors.;This dissertation consists of four manuscripts: (1) a review of previous medical display evaluations, providing insight into solutions that have worked in the past; (2) a study on reducing false alarms and increasing the usefulness of the remaining alarms by introducing alarm delays and detecting alarm context, such as suctioning automatically silencing ventilator alarms; (3) a study of simplifying the frequent but complicated task of titrating vasoactive medications by providing a titration support tool that predicts blood pressure changes 5 minutes into the future; and (4) a study on supporting the triage of unfamiliar patients by introducing a far-view display that incorporates information from previously disparate devices and presents trend and alarm information at one easy to scan and interpret location.
机译:仅在美国,医疗错误每年就可导致近100,000名患者可预防的死亡。常见的错误来源包括与药物有关的问题,技术设备故障,中断,复杂且容易出错的设备,信息过载(为一个人提供过多的患者数据以进行有效处理)以及诸如照明不足或干扰环境噪声的环境问题。重症监护病房是医院中风险最高的场所之一,每100个患者日最多报告9起事件。这种风险与手术室中的麻醉形成鲜明对比。在过去,患者安全领域取得了很大进步,将与麻醉相关的死亡的平均风险降低到不到20万种麻醉药中的1种-在过去30年中提高了20倍。现在,需要针对重症监护病房进行技术改造和其他创新,以实现这一成功。护士越来越多地被护士视为重要的决策者,因为护士的比例超过了医生4:1。通过提供决策支持工具来减少护士的工作量并改善医疗决策,可以对减少医疗错误的机会产生重大影响。;本论文包括四篇论文:(1)回顾以前的医疗展示评估,提供对解决方案的洞察力过去有效的; (2)通过引入警报延迟和检测警报环境(例如抽吸自动使呼吸机警报消音)来减少虚假警报并提高剩余警报的有效性的研究; (3)通过提供可预测未来5分钟血压变化的滴定支持工具,简化了血管活性药物滴定的频繁但复杂的任务的研究; (4)通过引入远视显示器来支持对陌生患者进行分类的研究,该显示器结合了先前不同设备的信息,并在易于扫描和解释的位置显示趋势和警报信息。

著录项

  • 作者

    Gorges, Matthias.;

  • 作者单位

    The University of Utah.;

  • 授予单位 The University of Utah.;
  • 学科 Engineering Biomedical.;Health Sciences Medicine and Surgery.;Health Sciences Nursing.
  • 学位 Ph.D.
  • 年度 2010
  • 页码 151 p.
  • 总页数 151
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

  • 入库时间 2022-08-17 11:37:17

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