Big data analytics in health sector: Theoretical framework, techniques and prospects

Panagiota Galetsi, Korina Katsaliaki and Sameer Kumar

International Journal of Information Management, 2020, vol. 50, issue C, 206-216

Abstract: Clinicians, healthcare providers-suppliers, policy makers and patients are experiencing exciting opportunities in light of new information deriving from the analysis of big data sets, a capability that has emerged in the last decades. Due to the rapid increase of publications in the healthcare industry, we have conducted a structured review regarding healthcare big data analytics. With reference to the resource-based view theory we focus on how big data resources are utilised to create organization values/capabilities, and through content analysis of the selected publications we discuss: the classification of big data types related to healthcare, the associate analysis techniques, the created value for stakeholders, the platforms and tools for handling big health data and future aspects in the field. We present a number of pragmatic examples to show how the advances in healthcare were made possible. We believe that the findings of this review are stimulating and provide valuable information to practitioners, policy makers and researchers while presenting them with certain paths for future research.

Keywords: Big data analytics; Health-Medicine; Decision-making; Machine learning; Operations research (OR) techniques (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (9)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:ininma:v:50:y:2020:i:c:p:206-216

DOI: 10.1016/j.ijinfomgt.2019.05.003

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