Abstract
Global healthcare industry is under significant pressure to reduce costs and more efficiently manage resources while improving patient care. Rising costs, chronic illness, an aging population and a shortage of professionals are forcing massive changes in the healthcare industry. To gain insight into how they can improve service while reducing costs, healthcare payers and providers are turning to data and analytics. Today Big data in healthcare is a hot issue. Therefore, in this communication, it is attempted to briefly present definitions, sources of big data, characteristics of Big Data, the architectural framework of big data analytics required in healthcare application. Big data analytics in healthcare reported in various literature are highlighted particularly on clinical data, Pharmaceutical data, Patient behavior, sentiment data, viral and Global Infectious Disease Surveillance. Lastly, the challenges are identified followed by future directions and advantages of big data analytics in healthcare.
Highlights
A day’s Hospital captures daily large amounts of data about their customers or patients, suppliers, and operations
We provide examples of big data analytics in healthcare reported in the literature
This chapter aimed to Healthcare analysts and practitioners to the advancements in the computing field to effectively handle and make inferences from voluminous and heterogeneous healthcare data
Summary
Global healthcare industry is under significant pressure to reduce costs and more efficiently manage resources while improving patient care. To gain insight into how they can improve service while reducing costs, healthcare payers and providers are turning to data and analytics. Today Big data in healthcare is a hot issue. In this communication, it is attempted to briefly present definitions, sources of big data, characteristics of Big Data, the architectural framework of big data analytics required in healthcare application. Big data analytics in healthcare reported in various literature are highlighted on clinical data, Pharmaceutical data, Patient behavior, sentiment data, viral and Global Infectious Disease Surveillance. The challenges are identified followed by future directions and advantages of big data analytics in healthcare
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