Doing Big Data In Healthcare

Inside Edge Consulting, Princeton

November 13, 2014

We know that big data will transform healthcare delivery, enable clinical efficiencies and promote greater accountability, or so that theory can be argued. Better yet, as a McKinsey report estimated in 2011, leveraging patient and clinical data could allow us to create more than $300 billion in value every year and reduce U.S. healthcare expenditure by roughly 8 percent.

But recently the industry has focused more on asking whether or not we should even use big data to create a 360-degree view of the patient and our business, as opposed to seeking the answer to a more prudent question: why other industries have been successful in obtaining value from their data sources and leveraging data to improve efficiencies and make more informed decisions—albeit also make more money. If we did, we would quickly recognize two points (among many more): first, what these other industries have figured out is that data is only transformative when disparate systems and data repositories can be linked together to form unified records at an individual level; and second, the industry as a whole is unprepared to address this challenge and thus capture the full potential and influence big data can have on healthcare because much of our data is siloed and fragmented.

We would also better understand data, how innovative its use could be and how it could enable us to reduce costs, identify and improve gaps in care delivery, improve quality, proactively identify at-risk patient populations and make care more accessible. To get to this point, though, we need to create a solid infrastructure—one that leverages data management, analysis, processing, optimization and storage—to empower us with the foundation to make more informed, evidence-based business and clinical decisions.

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Data, Digital, Health economics, Healthcare outlook