The Future of Data-Driven Wound Care

被引：10

作者：

Woods, Jon S. ^{[1
]}

Saxena, Mayur ^{[2
]}

Nagamine, Tasha ^{[2
]}

Howell, Raelina S. ^{[1
]}

Criscitelli, Theresa ^{[3
]}

Gorenstein, Scott ^{[4
]}

Gillette, Brian M. ^{[5
]}

机构：

[1] NYU Winthrop Hosp, Dept Surg, Mineola, NY 11501 USA

[2] Droice Labs Res, New York, NY USA

[3] NYU Winthrop Hosp, Dept Surg, Adm Perioperat & Procedural Serv, Mineola, NY USA

[4] NYU Winthrop Hosp, Dept Surg, Wound Care & Hyperbar Med, Mineola, NY USA

[5] NYU Winthrop Hosp, Dept Surg, Div Wound Healing & Regenerat Med, Mineola, NY USA

来源：

AORN JOURNAL | 2018年 / 107卷 / 04期

关键词：

big data; machine learning; dataset; neural networks; wound care; BIG DATA; KNOWLEDGE; COST; US;

D O I：

10.1002/aorn.12102

中图分类号：

R47 [护理学];

学科分类号：

101102 [成人与老年护理学];

摘要：

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.

引用

页码：455 / 463

页数：9

共 35 条

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