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Big Data, Health Economics and Pricing & Reimbursement
From fraud protection to online advertising, "big data" plays a large role behind the scenes of all of our day-to-day lives. References to "big data" are omnipresent across a wide spectrum of disciplines. However, the term is relatively new in the healthcare area despite the fact that the pharmaceutical industry is one of the industries most affected by the big data story --particularly in the area of clinical trials and post-approval tracking and, of course, healthcare economics. Here, the pharmaceutical industry has no choice. With growing requirements to support the evidence base of new technologies, the industry is forced to be part of the big data story, or risk not getting their drug to market. And indeed, one of the major themes of ISPOR's ongoing 19th international meeting is the potential of "big data" applications in the fields of healthcare and health economics.
The rise of electronic healthcare data, such as EMRs, combined with technological improvements in computing power has led to an increased interest in the prospective insights to be gained from this valuable resource. The financial and temporal requirements of RCTs inevitably lead to a less than ideal evidence base to support effective decisions in the broader population. Novel techniques, such as machine learning and graph analysis, represent another potential tool to aid healthcare decision makers. While these data and methods will never replace the human element in healthcare decision making, they have the ability to identify heretofore undiscovered relationships and provide insights that can lead to tangible improvements.
This field is still evolving and concerns (such as issues related to missing and noisy data) abound. However, the large number of sessions relating to "big data" at ISPOR is a testament to the level of attention the discipline is currently receiving and the community's excitement at the prospect of the potential findings inherent therein.
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