Hidden big data analytics issues in the healthcare industry

被引:17
|
作者
Strang, Kenneth David [1 ]
Sun, Zhaohao [2 ]
机构
[1] SUNY Coll Plattsburgh, Queensbury, NY USA
[2] PNG Univ Technol, Lae, Papua N Guinea
关键词
big data body of knowledge; big data paradigm; big data privacy; big data security; exponential Weibull trend; kappa interrater agreement; literature review; PRIVACY ISSUES; PUBLIC-HEALTH; SECURITY; CHALLENGES; NETWORKS; ERA;
D O I
10.1177/1460458219854603
中图分类号
R19 [保健组织与事业(卫生事业管理)];
学科分类号
摘要
The goal of the study was to identify big data analysis issues that can impact empirical research in the healthcare industry. To accomplish that the author analyzed big data related keywords from a literature review of peer reviewed journal articles published since 2011. Topics, methods and techniques were summarized along with strengths and weaknesses. A panel of subject matter experts was interviewed to validate the intermediate results and synthesize the key problems that would likely impact researchers conducting quantitative big data analysis in healthcare studies. The systems thinking action research method was applied to identify and describe the hidden issues. The findings were similar to the extant literature but three hidden fatal issues were detected. Methodical and statistical control solutions were proposed to overcome the three fatal healthcare big data analysis issues.
引用
收藏
页码:981 / 998
页数:18
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