Turning ‘Big Data’ into ‘Big Med’: 3 Perspectives

babelIn a recent audio report for iHealthBeat, 3 healthcare advocates for Big Data chimed in on specific ways it is helping now (current applications) and its future potential.

iHealthBeat posed the questions: “How do we make sense of Big Data, and can we change and improve the way care is delivered?” A cardiologist and two healthcare-related VPs answered.

‘Tower of Babel’ and a revolution

Eric Topol, a cardiologist at Scripps Health, delved into the potential of what could be a revolution in medicine. He envisioned a future in which you could map one patient’s tumor with another’s exact same tumor, individual demographics, DNA, treatment and outcomes. This kind of rich data access allows for highly custom and appropriate treatment.

Topol also emphasized how Big Data has mostly benefited individual healthcare systems up to this point in time. The main reason for this is interoperability, or what he calls the electronic health record (EHR) “Tower of Babel.” In other words, the lack of a standard EHR platform prevents the easy application of system-wide healthcare improvements across the nation. His vision of integration amounts to Big Data becoming “Big Med,” a powerful, common information system that includes easy access to genetic sequencing, lab tests, and other medical data.

Better health answers

Lydon Neumann, vice president of Impact Advisors, talked about using data to identify patterns and trends for better “health answers” for patients: “We have a huge amount of captured data that we now can look at and start looking for patterns and trends. In essence, using Big Data as the way to mine what is the best evidence-based medicine, what is the best approach to managing conditions, how do we want to manage a large population, how do we come up with the best answer for our patients.”

He cited the 2004 example of Kaiser Permanente effectively killing Vioxx after analyzing data from 1.4 million patients and discovering the increased risks of heart attacks among those taking that particular painkiller.

For reasons like the study above, mining Big Data is “not just practical, but highly desirable,” he argues. And the high adoption rate of automation of medical records is making the improved outcomes possible.

Elective deliveries: Improving care and lowering costs

Lee Pierce, vice president of business intelligence and analytics at Intermountain Healthcare, discussed how his company’s directors looked to data when they needed to improve care and lower costs. The network of 22 hospitals in Utah and Southern Idaho ultimately reduced its 30% rate of elective deliveries prior to 39 weeks. After applying insights from Big Data, the network’s elective deliveries prior to 39 weeks plummeted to 5%.

These Big Data illustrations reveal much about its promise—and current importance—in healthcare.


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Photo courtesy of rpi virtuell via Flickr.

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