Big data architecture for pervasive healthcare: a literature reviewTan, C., Sun, L. and Liu, K. (2015) Big data architecture for pervasive healthcare: a literature review. In: ECIS 2015 Completed Research Papers. ECIS, Paper 117. ISBN 9783000502842
It is advisable to refer to the publisher's version if you intend to cite from this work. See Guidance on citing. Official URL: http://aisel.aisnet.org/ecis2015_cr/177/ Abstract/SummaryPervasive healthcare aims to deliver deinstitutionalised healthcare services to patients anytime and anywhere. Pervasive healthcare involves remote data collection through mobile devices and sensor network which the data is usually in large volume, varied formats and high frequency. The nature of big data such as volume, variety, velocity and veracity, together with its analytical capabilities com-plements the delivery of pervasive healthcare. However, there is limited research in intertwining these two domains. Most research focus mainly on the technical context of big data application in the healthcare sector. Little attention has been paid to a strategic role of big data which impacts the quality of healthcare services provision at the organisational level. Therefore, this paper delivers a conceptual view of big data architecture for pervasive healthcare via an intensive literature review to address the aforementioned research problems. This paper provides three major contributions: 1) identifies the research themes of big data and pervasive healthcare, 2) establishes the relationship between research themes, which later composes the big data architecture for pervasive healthcare, and 3) sheds a light on future research, such as semiosis and sense-making, and enables practitioners to implement big data in the pervasive healthcare through the proposed architecture.
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