To effectively implement analytic processes, various big data management challenges 3–9 must be overcome. Healthcare data analytics begins with the process of database development: this includes data collection, preparation (extraction, cleansing, discretization, validation, integration, and transformation), modeling, validation, and resulting in the creation of patient knowledge bases. 2 The ability to stratify patients, understand scenarios, and optimize decision-making would consistently improve based on the myriad data obtained during the care-delivery process. Healthcare analytics has the potential to revolutionize the field of medicine by improving the quality and transition of care, improving outcomes by reducing costs, detecting diseases at earlier stages, 1 developing a better understanding of biological mechanisms, and modeling complex biological interactions through integration and analysis of data with holistic approach.
Healthcare data include information about patients’ lifestyles, medical histories, visits to the practices, lab tests, imaging tests, diagnoses, medications, surgical procedures, metabolomics and genomics profiles, consulted providers and claims.
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