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

被引:77
作者
Galetsi, Panagiota [1 ]
Katsaliaki, Korina [1 ]
Kumar, Sameer [2 ]
机构
[1] Int Hellen Univ, Sch Econ Business Adm & Legal Studies, 14th Km Thessaloniki N Moudania, Thessaloniki 57001, Greece
[2] Univ St Thomas, Opus Coll Business, Minneapolis Campus,1000 LaSalle Ave, Minneapolis, MN 55403 USA
关键词
Big data analytics; Health-Medicine; Decision-making; Machine learning; Operations research (OR) techniques; BUSINESS INTELLIGENCE; PREDICTIVE ANALYTICS; DECISION-MAKING; SUPPLY CHAIN; MODEL APPLICATION; MATURITY MODEL; VALUE CREATION; CARE; INFORMATION; MANAGEMENT;
D O I
10.1016/j.ijinfomgt.2019.05.003
中图分类号
G25 [图书馆学、图书馆事业]; G35 [情报学、情报工作];
学科分类号
1205 ; 120501 ;
摘要
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.
引用
收藏
页码:206 / 216
页数:11
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