Improving intensive care unit effectiveness and efficiency through improved data processing and analysis techniques.

通过改进的数据处理和分析技术提高重症监护室的有效性和效率。

• 批准号: ST/I003231/1
• 负责人: Louise Harra
• 金额: $ 16.37万
• 依托单位: University College London
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2012
• 资助国家: 英国
• 起止时间: 2012 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=ST%2FI003231%2F1
• 关键词: Improving; intensive; care; unit; effectiveness

The purpose of this project is to make use of the extensive data archiving, searching and analysis techniques for large datasets in the field of astrophysics and apply them to the hospital Intensive Care Unit (ICU) setting. Over the past 10 years in particular there has been a big push to ensure that complex, multi-wavelength, multi-source astrophysics datasets are in a compatible formats to enable astronomers to explore and resources from around the world, find data, store and share files, query databases, plot and manipulate tables, cross-match catalogues, and build and run scripts to automate sequences of tasks. These techniques are used for spacecraft datasets based at MSSL. This alongside with a similar push from the particle physics world has lead to a core expertise within STFC funded research in dealing with large and complex datasets that is the foundation of much of our (astronomy) scientific research today. One example is the Hinode spacecraft data. In this case a user can probe the archive searching for changes in different parameters such as intensity, velocity, turbulence, and view the data in multiple formats such as movie format and lightcurves. The system was designed to be flexible, using standard formats that can be probed by anyone in the world. We have techniques to look for triggers to large explosions on the Sun, which involve gradual changes that lead to a catastrophic outcome. Similar techniques could be used to acquire patient data and track trends in a patient's condition in an intensive care unit (ICU) setting (e.g. heart rate, blood pressure, blood oxygenation, electrolyte disturbances etc.). Currently most of the datasets are taken in a discontinuous way and in many cases are still recorded by hand at 30 minute intervals. The data is not currently stored and cannot be used to determine precursors. The longest period data will be kept in monitors will be on circular buffers for 24 hours with discontinuous data being collected on 30 min intervals to allow longer term study. The ultimate goal of this study is to provide a software tool that will allow a response BEFORE a catastrophic change happens physiologically rather than after, as is currently the case.

本项目的目的是利用天体物理学领域的大量数据归档、搜索和分析技术，并将其应用于医院重症监护病房(ICU)环境。特别是在过去10年里，人们大力推动确保复杂、多波长、多源的天体物理数据集具有兼容的格式，使天文学家能够探索和利用来自世界各地的数据和资源、查找数据、存储和共享文件、查询数据库、绘制和操纵表格、交叉匹配星表以及构建和运行脚本以自动执行一系列任务。这些技术用于基于MSL的航天器数据集。这一点，再加上粒子物理界的类似推动，导致了STFC资助的处理大型和复杂数据集的研究的核心专业知识，这是我们今天许多(天文学)科学研究的基础。Hinode航天器的数据就是一个例子。在这种情况下，用户可以探测档案，搜索不同参数(如强度、速度、湍流)的变化，并以多种格式(如电影格式和光照曲线)查看数据。该系统设计灵活，使用世界上任何人都可以探测的标准格式。我们有技术来寻找太阳大爆炸的诱因，这涉及到导致灾难性后果的渐进变化。类似的技术可用于获取患者数据并跟踪重症监护病房(ICU)环境中患者病情的趋势(例如心率、血压、血氧、电解质紊乱等)。目前，大多数数据集是以不连续的方式获取的，在许多情况下，仍是每隔30分钟手工记录一次。数据目前没有存储，不能用来确定前兆。将在监视器中保存最长时间的数据将在循环缓冲区上保存24小时，每隔30分钟收集不连续的数据，以便进行更长期的研究。这项研究的最终目标是提供一种软件工具，允许在灾难性的变化发生之前做出反应，而不是像目前的情况那样发生在之后。