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Authors : Ashish Kaushik, Sachin Kumar, Manjunath C R.

Volume/Issue :-
 Volume 3 Issue 5

Google Scholar :-
 https://goo.gl/DF9R4u

Scribd :- 
https://goo.gl/xytsQovY

Thomson Reuters :- https://goo.gl/3bkzwv

Health care analysis poses a consistent challenge to physicians and is the area of research in which tr illions of amounts are being spent by all countries. The patient health conditions are analyzed and exact disease is diagnosed using Big Data analytics with Evidence Based methodology. Patient analysis report is generated to monitor the recovery and patient feedback of the suggested drug is recorded to witness the success-rate of the diagnosis process. Proposing new idea for the patients on their medicine dosage by applying strictly age limit and providing nearby shops and Medicare Centre by their GPS location on their device. Here a probabilistic data collection mechanism is designed and the correlation analysis of those collected data is performed. A stochastic prediction model is designed to foresee the future health condition of the most correlated patients based on their current health status. A cloud-enabled big data analytic platform is the best way to analyze the structured and unstructured data generated from healthcare management systems. Patient’s medical history and current evidences are considered to diagnose and drug suggestion. The EBM manifesto offered here grew from that awareness. It is an open invitation for others to contribute to and join a movement towards better evidence by providing a roadmap for how to achieve the listed priorities and to share the lessons from achievements already made.
Keywords:- Data analytics; Medicare; GP; EBM.