Big Data Is BS in Healthcare. When Will It Become Real?

4/15/13Follow @xconomy

Tech entrepreneurs have been raving for a while now about big data changing the world, and it’s mostly bullshit. Venture capitalist Brad Feld made this point, more or less, when he was being purposely provocative at an Xconomy event last fall.

As a biotech journalist, I wanted to cheer “Preach On, Brother Feld!” Doctors are still kicking and screaming about being forced to use electronic medical records, more than 30 years into the PC revolution. We’ve had to pay them all off as a country to get them to quit using old-fashioned pen and paper. Hospitals have dozens of proprietary records systems that don’t talk to each other. While “big data” analysis is sweeping through and changing the way people forecast the weather, predict traffic patterns, and trade stocks, it’s always been hard for me to see how big data will crack into an industry as hidebound as healthcare. How many times have you written down your Social Security number on a patient intake form, when they could have just had it on file?

How are we suddenly going to wake up in an environment where we capture, store, retrieve, and analyze big volumes of medical data to improve wellness and patient care? Will we all end up wearing glucose monitors that stream real-time data to cloud-based supercomputers that use mathematical, predictive models to warn us when we’re headed toward diabetes? The future of personalized medicine sounds enticing, and there are already some great examples of a few drugs and diagnostics that do make healthcare more effective, and precisely targeted to the patient. But no one should underestimate the power of the status quo, and how allergic most healthcare players are, to any of this disruptive change.

But after a recent visit with Colin Hill at Cambridge, MA-based GNS Healthcare, I’m starting to think that big data is now worth at least keeping an eye on in healthcare. The revolution, when it comes, will be driven by financial necessity.

Colin Hill, CEO of GNS Healthcare

GNS has been around for a long-time already, and Hill is a smart guy and regular speaker on the life sciences event circuit. GNS is one of the early movers in this world of what you could call “big data analytics for healthcare” or “data-driven decision-making for healthcare.” The company has had its ups and downs, and probably has been a little too far ahead of the times for its own good. But Hill has been a careful student of the healthcare markets, he’s been patient, and while he sees that big data hasn’t yet arrived in healthcare, he believes it’s only a matter of time.

When I spoke with him a week ago, he had just delivered a sobering message to biotech and pharma CEOs at a private gathering in Boston.

“You guys are not prepared for what you’re about to run into.’” Hill says he told the group of executives. “A lot of CEOs talk a good game about moving ‘beyond the pill,’ but the level of chops and data assets and analytic tools needed to do this are beyond what most pharma companies have. If they don’t get ahead of it, payers will do it for them.”

Big data could mean a lot of things in healthcare, but GNS is now starting to find what looks like a truly useful niche.

Right now, most prescribing of drugs is based on trial and error. A patient comes in, sees a doctor, gets diagnosed with something like multiple sclerosis. The doctor, being the expert, is familiar with the various treatments that are approved by the FDA, and the body of medical evidence that each product has built up in controlled clinical trials. Based on that knowledge, and some information about the patient and the doctor’s own intuition or biases, he or she prescribes a medication and hopes for the best. If it doesn’t work, the doctor and patient move on to another drug or device.

Payers, whether they are at Medicare or UnitedHealth or Aetna or elsewhere see enormous waste in this system.

As Hill puts it, the $2.7 trillion a year U.S. healthcare industry suffers from a massive ‘Wanamaker’ problem. Wanamaker, students of history know, was a 19th and early 20th century retailer who famously observed that half of the money he spent on advertising in traditional media outlets was wasted—the trouble was, he didn’t know which half.

By the end of the 20th century, Google came along and made it possible for advertisers to eliminate much of that waste, and aim their ads precisely where they could be most effective. It was a win for advertisers and a horrible loss for traditional media companies (don’t get me started.)

The “Wanamaker” problem in healthcare is equally big and ripe for disruption. Cancer drugs … Next Page »

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  • http://www.philsimon.com/ Phil Simon

    I was a bit skeptical as well. Then I started doing research for my new book. I’m not skeptical anymore.

  • http://twitter.com/ExMedNav ExMedNav

    On behalf of physicians, nurses & caregivers who care about patients, their outcomes and the cost effectiveness of care, I can say with surety that a good majority of caregivers will gladly embrace the USE of big data. Forcing them to be the primary source of data CREATION (e.g. costly keying it into forms) takes them away from interacting with patients, which is the concern most often expressed.

    Likewise, patients, who often aren’t included as a key stakeholder in these conversations, should also be given incentives for not only healthy behavior but also the consumption and use of big data through tools that empower their ability to look out for themselves. The analogs Luke identifies early on (weather, traffic, stocks) are great examples of big data empowering *consumer* applications.

  • http://www.facebook.com/people/Azana-Baksh/100003026037089 Azana Baksh

    Luke, at LexisNexis Risk Solutions we are actively engaged in using the open source HPCC Systems data intensive compute platform along with the massive LexisNexis Public Data Social Graph to tackle everything from fraud waste and abuse, drug seeking behavior, provider collusion to disease management and community healthcare interventions. We have invested in analytics that help map the social context of events through trusted relationships to create better understanding of the big picture that surrounds each healthcare event, patient, provider, business, assets and more. For an interesting case study visit: http://hpccsystems.com/Why-HPCC/case-studies/health-care-fraud

  • http://www.facebook.com/liz.derr Liz Derr

    Another set of stakeholders that have a financial motivation to use big health care data are the Personal Liability Insurers. Insurers and Patient Safety Organizations have a huge motivation to prevent medical mistakes and reduce the number of malpractice lawsuits. Analysis of big data can help them identify who among their clients is at higher risk of making mistakes, and why.

  • http://www.facebook.com/dominick.hoffler Dominick Hoffler

    Some great thoughts to ponder. I totally agree with this post.
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  • http://www.facebook.com/dominick.hoffler Dominick Hoffler

    Some great thoughts to ponder. I totally agree with this post.
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  • Laurie Meehan

    Excellent article. Nothin’ better than hope from a skeptic!

  • http://twitter.com/chris_biow Christopher Biow

    Statistical analytics over large populations of structured data may be the most common mental image of “Big Data.” But whether or not that particular Volume-oriented example is BS or not, there is a broader spectrum of Big Data technology . Velocity and Variety are equally important dimensions, where, in particular, new NoSQL database technologies are providing fast responses over medical data whose complexity doesn’t fit well in database technologies that are a generation or two out of date.

  • http://twitter.com/EquationBI Equation

    Great post. I think the key is starting in smaller segments. Where the data silos are still large, though targeted with specific niche based questions. It’s true that there are many variables at play, though one aspect we’re tackling is the physician economics. With http://www.datariver.me, we aggregate billing data make it instantly useful for practice managers and others within the health system.