优化数据系统：临床预测与决策支持的未来
Optimal data systems: the future of clinical predictions and decision support.
作者信息
Celi Leo A, Csete Marie, Stone David
机构信息
aMassachusetts Institute of Technology, Cambridge, Massachusetts bHuntington Medical Research Institutes, Pasadena, California cUniversity of Virginia School of Medicine, Charlottesville, Virginia, USA *Dr Leo A. Celi, Dr Marie Csete, and Dr David Stone contributed equally to this manuscript.
出版信息
Curr Opin Crit Care. 2014 Oct;20(5):573-80. doi: 10.1097/MCC.0000000000000137.
PURPOSE OF REVIEW
The purpose of the review is to describe the evolving concept and role of data as it relates to clinical predictions and decision-making.
RECENT FINDINGS
Critical care medicine is, as an especially data-rich specialty, becoming acutely cognizant not only of its historic deficits in data utilization but also of its enormous potential for capturing, mining, and leveraging such data into well-designed decision support modalities as well as the formulation of robust best practices.
SUMMARY
Modern electronic medical records create an opportunity to design complete and functional data systems that can support clinical care to a degree never seen before. Such systems are often referred to as 'data-driven,' but a better term is 'optimal data systems' (ODS). Here we discuss basic features of an ODS and its benefits, including the potential to transform clinical prediction and decision support.
综述目的
本综述旨在描述数据在临床预测和决策制定方面不断演变的概念及作用。
最新发现
重症医学作为一个数据特别丰富的专业领域，不仅日益敏锐地意识到其在数据利用方面长期存在的不足，还认识到它在收集、挖掘和利用这些数据以构建精心设计的决策支持模式以及制定强有力的最佳实践方面具有巨大潜力。
总结
现代电子病历为设计完整且实用的数据系统创造了机会，这些系统能够以前所未有的程度支持临床护理。此类系统常被称为“数据驱动型”，但一个更好的术语是“最优数据系统”（ODS）。在此，我们讨论最优数据系统的基本特征及其益处，包括其在改变临床预测和决策支持方面的潜力。
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