Big Data in Clinical Sciences-Value, Impact, and Fallacies

Abstract

The ever-burgeoning healthcare enigmata may find their answers in Big Data. When data cannot be collected, curated, managed, and processed by commonly used software tools within a requisite time frame, they are referred to as Big Data. We put forth a narrative review on the evolution and spectrum of the clinical applications of Big Data across medical and surgical sciences, evaluating their impact and cautioning about their potential fallibilities. There is an explosion of health care data generated as a byproduct of clinical care and research in the digital information era. The challenge lies in converting these unstructured datasets into clinical wisdom and practice-defining insights. Big data provides information on the quality of health care, resource utilization, public health deficiencies, research hypothesis creation, and overall holds the potential to revolutionize clinical sciences. Several fallacies of big data like data inaccuracies, privacy, confidentiality, proprietary concerns, and caveats in data analysis algorithms may misdirect the lessons from big data.

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