I was at the Boston event and I concur that the packed room full of entrepreneurs, venture capitalists and established vendors were in agreement that something big -- driven by tech -- is happening in healthcare. I was also there at the Internet bubble and the healthcare fervor has some big differences from that era of Pets.com, Webvan and Kozmo. Those Internet bubblers were solving problems that didn't exist. The healthcare upstarts are trying to solve gnarly business/technology problems in a multi-trillion dollar industry.
Bryan Sivak, CTO of the U.S. Department of Health and Human Services (HHS), is at the forefront, trying to change an industry that at times seems cast in concrete. "Can technology-driven innovation be infused within the legendary bureaucracies of government?" I asked Sivak in an interview following his Xconomy keynote presentation. "The funny thing is, I don't think government is that much different from other large industries," Sivak said.
Sivak, who came to the 90,000-employee HHS six months ago, was the founder of knowledge management company InQuira, which was acquired by Oracle in 2011. "Some of the greatest people I've worked with are in government ... [T]hey are people doing these projects for the right reasons, they are smart, they work hard and they are dedicated. But the way the system is structured can be risk adverse, with no tolerance for any sort of failure. What we are trying to do is to allow people to successfully experiment, even if those experiments don't happen to show the hypothesis to be true."
In his keynote, Sivak said "data is changing the healthcare industry right now. Healthcare is an opaque market and you need transparency around cost and quality." He could have the biggest, big data project currently taking place in government. The healthcare industry is awash in data contained in silos, subject to various privacy rules, guarded by companies that want to keep the data to themselves, in an environment where paper and manila folders still rule.
Figuring out how to mesh that data, maintain privacy and make it available in a customer-friendly format is a tech and business problem formidable enough to stump the best and the brightest. You need to take the complex data and present it in a consumer-friendly user interface. That information will most likely be viewed on a mobile device and, while difficult, there are some initiatives that are pointing the way. Sivak points to the Blue Button initiative as an example of a simple way for Veterans Administration patients to access complex data streams.
Solving the healthcare big data dilemma has enormous rewards. Healthcare in the United States is a multi-trillion dollar industry (2007 figures were $2.26 trillion), and it is expected to continue to grow as the population ages. National health reform, changes in Medicare, and changes in the provider, insurer, and patient relationships are all creating a search for efficiency. This requires new methods of care, as well as the application of business analysis to an industry that traditionally operated under extensive medical and legal oversight, but little impetus for a customer-first attitude.
That shifting relationship and the resulting business opportunities filled the room at the Xconomy Forum. Here are four technology trends that will change healthcare over the next five years.
1. Cloud: "Payers are stuck with 25-year-old infrastructures. They are asking: Is there another way?" said Rob Gillette, CEO of HealthEdge. The prospect of a cloud-based architecture to mesh those information silos and provide patients, providers and payers with a consistent view into the healthcare system is one of the big health investment drivers. Rock Health, a venture capital organization, tracks health-related startups and lists seven in the health cloud category.
2. Robots: The idea of a robot scooting around a hospital ward checking on patients might sound farfetched -- until you speak with Yulan Wang, CEO of InTouch Health, based in Santa Barbara, Calif. I interviewed Wang from Boston via the RP-VITA robot, which is a co-project with iRobot. The robot allows full-image, full-audio and (for the doctor or nurse) remote monitoring. The biggest issue holding back the wider use of robotics for telemedicine is not technology but figuring out the provider and payee reimbursement systems.
3. Consumers: Consumer gadgets are expanding from music, video and social sharing to include health monitoring and health improvement. The most interesting one mentioned was Scandu, which is pioneering in allowing patients to do tests using a smartphone app that were once restricted to the doctor's office. Where this will lead is anyone's guess, but patients will increasingly know more details about their personal health than any one office visit can provide.
4. Big Data: No tech conference is complete these days without some mention of big data. But just as Sivak's keynote address stated, big data in health may be our biggest data analysis problem with the greatest benefit. Unlike other industries where data on an individual or process may be sparse, the healthcare industry suffers from an overload of data contained in silos, often incompatible and very often still in analog, rather than digital, form. The cloud may help align some of that data, but it will be the data analysis systems still to be built that may finally turn data overload into just the right data being available at just the right time.
Venture capital funding of healthcare technology companies is 70% ahead of Q3 2011, year over year, with the Boston and San Francisco Bay regions accounting for about half of the funding.
VCs looking for "real" investments, as opposed to yet another social networking app, are betting on those shifts in the multi-trillion dollar healthcare economy to create superstar companies. I'm betting they are right and this bubble is no bubble at all, but the stuff from which great new companies will emerge.
InformationWeek Tech Digest, Nov. 10, 2014Just 30% of respondents to our new survey say their companies are very or extremely effective at identifying critical data and analyzing it to make decisions, down from 42% in 2013. What gives?