Many challenges stand in the way of achieving the full potential of using patient data in research, according to a paper by Yale researcher Harlan Krumholz in the July 8 edition of Health Affairs, a theme issue on “Big Data.”
Krumholz said these challenges include the need to ensure the privacy and security of sensitive patient information, as well as to ensure data used in research are valid, reliable, and standardized. But even in the face of these challenges, the effort is essential, writes Krumholz.
“Until medicine develops a robust clinical research community that embraces these contemporary opportunities and fully realizes the promise of big data, the large gap between the available evidence, what is needed, and what could be generated will persist,” said Krumholz, the Harold H. Hines, Jr. Professor of Medicine at Yale and director of the Yale Center for Outcomes Research and Evaluation.
Big data in medicine — massive quantities of health care data accumulated from patients and populations and the advanced analytics that can give those data meaning — hold the prospect of becoming an engine for the knowledge generation that is necessary to address the extensive unmet information needs of patients, clinicians, administrators, researchers, and health policy makers.
Read the full article here.
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