Each month, What’s Next Health talks with leading thinkers with big ideas about the future of health and health care. Recently, we talked with Daniel Kraft to explore the potential of exponential technologies. Daniel chairs the Medicine Track for Singularity University and is executive director for FutureMed, a program that explores how fast moving technologies can re-invent health & medicine. The next FutureMed will be held Nov. 3-6 at the Hotel Del Coronado in San Diego, CA.

By Daniel Kraft

"Any sufficiently advanced technology is indistinguishable from magic.”

— Arthur C. Clark

We live in an exciting, and seemingly ever faster, exponential age, where many technologies, from Artificial Intelligence, social networks, and mobile, to personal genomics, robotics and nanomaterials, when converging together do indeed approach magical qualities as they become faster, smaller, smarter and more powerful at often dramatically decreasing price points.

I recently stepped out of my largely virtual, long distance relationship with the Khan Academy and went behind the wizard’s curtain to see how it’s actually done.  Certainly, we here at RWJF have met many Khan personalities in real life, including Sal, himself, as well as Dr. Rishi Desai, who leads the Khan Healthcare and Medicine Initiative. However, it's one thing to meet individuals outside of their natural habitat—and quite another to track them back to their offices in Mountain View, California, and see what gives. 

From SFO, I carefully followed my Droid Navigator’s directions off Highway 101 into a warren of non-descript low-slung office buildings—non-descript except for the telltale proliferation of Google signs and young adults riding colorful Google bikes.  I drove around to the back of several of those complexes and finally found the correct numbered grouping.  It really could have been any office or doctors’ office complex in the U.S.  The Khan suite is on the second floor. 

The big data hype cycle is playing out in predictable ways. Perhaps it’s inevitable that, after all the talk about how big data is going to save the world, we’re starting to see a similar rash of stories about how the promise of big data has been oversold. Microsoft Research’s Kate Crawford has been particularly outspoken as of late, with Quentin Hardy recounting her “six myths of big data” in The New York Times last weekend and Kate’s own Foreign Policy piece in May, which pointed out that big data put our privacy at risk, in addition to being susceptible to bias, misunderstanding, limitations and discriminatory outcomes.

I’m all for a little healthy skepticism. In fact, Pioneer seeks out those who are asking questions that others are not. But the potential of big data to take on some of health and health care’s most intractable problems is something we’re excited about here at RWJF. Too many Americans are unhealthy, our health care system isn’t working and I’m confident that effective analysis and use of big data has (at the very least a small) role to play in turning things around. I don’t want this backlash to stifle explorations into what that role could be.

From: Thomas Goetz

To: Christine Nieves, Paul Tarini and Beth Toner

Date: June 2, 2013

Like you, Paul, this will be my third Datapalooza (I’m tempted to go all Woodstock and say I was there for the first, but… I wasn’t that cool).

I remember the second Datapalooza quite vividly. First, because I’d taken a red-eye from San Francisco and was fairly bleary, and second because I was completely unprepared for the passion and sense of potential that was on tap that day at the NIH auditorium. Frankly, I didn’t expect much; I figured a D.C. conference about data organized by the federal government wasn’t exactly going to be a hub of innovative ideas.

But my Bay Area provincialism was quickly scrubbed as Todd Park et al stunned me in the best possible way. In short, I remember that Datapalooza because it’s where I got a vibe that something was going on in D.C. around health care that was, if anything, more powerful and exciting than what was brewing in Silicon Valley.

Think about it for a moment. When you consider what you "know" about health, where does that knowledge come from? While we all have our sources—doctors, friends, news articles—our knowledge at its core is derived from research. And that research is built on a foundation of data.

Data about health typically come from several types of sources: clinical data, gleaned from electronic health records or chart pulls, and billing and claims data, which are byproducts of the health care process; and public health surveillance data, which are specialized collections about particular topics or populations. All of these sources can then be supplemented, at a considerable cost, by original data collection efforts specific to a particular study.

These different types of data are like pieces of a jigsaw puzzle; when assembled, they create a more complete picture of health.

But a piece of the puzzle is missing.  Or it has been up till now.