Hidden big data analytics issues in the healthcare industry

• Published in: Health informatics journal Vol. 26; no. 2; pp. 981 - 998
• Main Authors: Strang, Kenneth David, Sun, Zhaohao
• Format: Journal Article
• Language: English
• Published: London, England SAGE Publications 01.06.2020; SAGE PUBLICATIONS, INC
• Subjects: Big Data; Data analysis; Health care industry; Research methodology; big data body of knowledge; big data privacy; exponential Weibull trend; big data security; kappa interrater agreement; big data paradigm; literature review
• ISSN: 1460-4582; 1741-2811; 1741-2811
• DOI: 10.1177/1460458219854603

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.