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数据驱动型伤口护理的未来。

The Future of Data-Driven Wound Care.

作者信息

Woods Jon S, Saxena Mayur, Nagamine Tasha, Howell Raelina S, Criscitelli Theresa, Gorenstein Scott, M Gillette Brian

出版信息

AORN J. 2018 Apr;107(4):455-463. doi: 10.1002/aorn.12102.

Abstract

Care for patients with chronic wounds can be complex, and the chances of poor outcomes are high if wound care is not optimized through evidence-based protocols. Tracking and managing every variable and comorbidity in patients with wounds is difficult despite the increasing use of wound-specific electronic medical records. Harnessing the power of big data analytics to help nurses and physicians provide optimized care based on the care provided to millions of patients can result in better outcomes. Numerous applications of machine learning toward workflow improvements, inpatient monitoring, outpatient communication, and hospital operations can improve overall efficiency and efficacy of care delivery in and out of the hospital, while reducing adverse events and complications. This article provides an overview of the application of big data analytics and machine learning in health care, highlights important recent advances, and discusses how these technologies may revolutionize advanced wound care.

摘要

慢性伤口患者的护理可能很复杂,如果不通过循证方案优化伤口护理,出现不良后果的可能性就很高。尽管伤口专用电子病历的使用日益增加,但跟踪和管理伤口患者的每个变量和合并症仍很困难。利用大数据分析的力量,帮助护士和医生根据为数百万患者提供的护理提供优化护理,可能会带来更好的结果。机器学习在工作流程改进、住院患者监测、门诊沟通和医院运营方面的众多应用,可以提高医院内外护理服务的整体效率和效果,同时减少不良事件和并发症。本文概述了大数据分析和机器学习在医疗保健中的应用,突出了近期的重要进展,并讨论了这些技术如何可能彻底改变高级伤口护理。

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