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Big data science: A literature review of nursing research exemplars

机译:大数据科学:护理研究普遍研究的文献综述

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Abstract Background Big data and cutting-edge analytic methods in nursing research challenge nurse scientists to extend the data sources and analytic methods used for discovering and translating knowledge. Purpose The purpose of this study was to identify, analyze, and synthesize exemplars of big data nursing research applied to practice and disseminated in key nursing informatics, general biomedical informatics, and nursing research journals. Methods A literature review of studies published between 2009 and 2015. There were 650 journal articles identified in 17 key nursing informatics, general biomedical informatics, and nursing research journals in the Web of Science database. After screening for inclusion and exclusion criteria, 17 studies published in 18 articles were identified as big data nursing research applied to practice. Discussion Nurses clearly are beginning to conduct big data research applied to practice. These studies represent multiple data sources and settings. Although numerous analytic methods were used, the fundamental issue remains to define the types of analyses consistent with big data analytic methods. Conclusion There are needs to increase the visibility of big data and data science research conducted by nurse scientists, further examine the use of state of the science in data analytics, and continue to expand the availability and use of a variety of scientific, governmental, and industry data resources. A major implication of this literature review is whether nursing faculty and preparation of future scientists (PhD programs) are prepared for big data and data science. Highlights ? Findings from this literature review support that nurse scientists are beginning to engage in data science with big data using a variety of data sources and cutting-edge analytic methods. ? The key challenge is determining how nursing scientists partner with the data science field to transcend human intellectual limitations. ? A major implication of this literature review is whether nursing faculty and preparation of future scientists (PhD programs) are prepared for big data and data science.
机译:抽象背景大数据和尖端分析方法在护理研究挑战护士科学家扩展了用于发现和翻译知识的数据来源和分析方法。目的本研究的目的是识别,分析和综合适用于练习和在关键护理信息学,一般生物医学信息学和护理研究期刊的实践和传播的大数据护理研究的平方例。方法对2009年至2015年期间出版的研究文献综述。在科学数据库网络中有650个关键护理信息学,一般生物医学信息管理和护理研究期刊。在筛选纳入和排除标准后,18条文章发布的17项研究被确定为适用于实践的大数据护理研究。讨论护士显然正在开始进行适用于实践的大数据研究。这些研究代表多个数据源和设置。虽然使用了许多分析方法,但基本问题仍有难以定义与大数据分析方法一致的分析类型。结论需要提高护士科学家大数据和数据科学研究的知名度,进一步审查数据分析中科学状态的使用,并继续扩大各种科学,政府和使用的可用性和使用行业数据资源。本文综述对未来科学家(博士计划)的护理教师(博士计划)的重大含义是为大数据和数据科学做好准备。强调 ?从这种文献审查支持的调查结果,护士科学家正在使用各种数据来源和尖端分析方法开始与大数据进行数据科学。还关键挑战是确定护理科学家如何与数据科学领域合作以超越人类的智力限制。还本文综述对未来科学家(博士计划)的护理教师(博士计划)的重大含义是为大数据和数据科学做好准备。

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