Abstract—Increase in storing the Electronic Health Records (EHR) of patients has developed a large scale datasets. Visual analytics plays an important role in decision making process because humans have ability to quickly gain insight through visual analysis. Existing visual analysis tools and techniques do not properly fit the big data. There is a need to design an efficient data visualization tools. These tools should consider the quality of data and presentation to facilitate navigation. Visualization can assist in descriptive, predictive and prescriptive type of analytics. Users like to visualize data processed in clouds have the same experience and feel as though data were processed locally. The batch-job model provided by most cloud environments would now include MapReduce as a backend to features provided in interfaces with which users are familiar. In order to improve the healthcare for patients health care organizations should provide accurate data to the right patient and at the right time. Big data analytics will benefit most of the components of health care system. In this paper we first study the big data impact on healthcare and then analyze how data analytics can improve patient care and reduce costs. Data analytics of Electronic Health Records on cloud can reduce much more costs to the Healthcare organization.
Index Terms—datasets, visual analysis, MapReduce, EHR, cloud, big data
Cite: Sreekanth Rallapalli and Augustin Minalkar, and R. R. Gondkar, "Improving Healthcare-Big Data Analytics for Electronic Health Records on Cloud," Vol. 7, No. 1, pp. 65-68, February, 2016. doi: 10.12720/jait.7.1.65-68
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