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.

该项目的目的是利用天体物理学领域的大型数据集的广泛数据归档，搜索和分析技术，并将其应用于医院重症监护室（ICU）设置。 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.这些技术用于基于MSSL的航天器数据集。这与粒子物理世界的类似推动以及STFC资助的研究中的核心专业知识在处理当今我们（天文学）科学研究的大部分基础方面都获得了核心专业知识。一个示例是Hinode航天器数据。在这种情况下，用户可以探索档案，以搜索不同参数的变化，例如强度，速度，湍流，并以多种格式（例如电影格式和灯火车）查看数据。该系统旨在灵活，使用世界上任何人都可以探索的标准格式。我们有技术可以在太阳上寻找大爆炸的触发因素，这涉及导致灾难性结果的逐渐变化。可以使用类似的技术来获取患者数据并在重症监护病房（ICU）设置（例如心率，血压，血压，血液氧合，电解质干扰等）中的患者状况中追踪趋势。目前，大多数数据集都是以不连续的方式拍摄的，在许多情况下，仍以30分钟的间隔手动记录。数据当前尚未存储，也不能用于确定前体。最长的周期数据将保存在监视器中，将在圆形缓冲液中进行24小时，并以30分钟的间隔收集不连续的数据以允许长期研究。这项研究的最终目标是提供一种软件工具，该工具将允许在灾难性变化发生在生理上而不是之后的情况下，就像目前一样。