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.
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.
Keywords
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Article info
Publication history
Published online: December 07, 2016
Accepted:
November 21,
2016
Received in revised form:
November 3,
2016
Received:
June 4,
2016
Identification
Copyright
© 2016 Elsevier Inc. All rights reserved.
