Big Data in Healthcare Management: A Review of Literature
American Journal of Theoretical and Applied Business
Volume 4, Issue 2, June 2018, Pages: 57-69
Received: Mar. 4, 2018; Accepted: May 3, 2018; Published: Jul. 3, 2018
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Senthilkumar SA, Department of Management, Pondicherry University, Pondicherry, India
Bharatendara K Rai, Charlton College of Business, University of Massachusetts Dartmouth, North Dartmouth, USA
Amruta A Meshram, Charlton College of Business, University of Massachusetts Dartmouth, North Dartmouth, USA
Angappa Gunasekaran, School of Business and Public Administration, California State University, Bakersfield, USA
Chandrakumarmangalam S, Department of Management Studies, Anna University Regional Campus, Coimbatore, India
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A systematic literature review of papers on big data in healthcare published between 2010 and 2015 was conducted. This paper reviews the definition, process, and use of big data in healthcare management. Unstructured data are growing very faster than semi-structured and structured data. 90 percentages of the big data are in a form of unstructured data, major steps of big data management in healthcare industry are data acquisition, storage of data, managing the data, analysis on data and data visualization. Recent researches targets on big data visualization tools. In this paper the authors analysed the effective tools used for visualization of big data and suggesting new visualization tools to manage the big data in healthcare industry. This article will be helpful to understand the processes and use of big data in healthcare management.
Big Data, Data Acquisition, Data Storage, Data Analytics, Data Visualization, Healthcare Management
To cite this article
Senthilkumar SA, Bharatendara K Rai, Amruta A Meshram, Angappa Gunasekaran, Chandrakumarmangalam S, Big Data in Healthcare Management: A Review of Literature, American Journal of Theoretical and Applied Business. Vol. 4, No. 2, 2018, pp. 57-69. doi: 10.11648/j.ajtab.20180402.14
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This article is an open access article distributed under the Creative Commons Attribution License ( which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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