The paper from the New England Journal of Medicine that reports azithromycin might cause cardiovascular death is not new to electrophysiologists tasked with deciding antibiotic choices in patients with Long QT syndrome or in those who take other antiarrhythmic drugs. Heck, even the useful Arizona CERT QTDrugs.org website could have told us that.
What was far scarier to me, though, was how the authors of this week’s paper reached their estimates of the magnitude of azithromycin’s cardiovascular risk.
Welcome to the underworld of Big Data Medicine.
Careful review of the Methods section of this paper reveals that “persons enrolled in the Tennessee Medicaid program” were the subjects, and that the data collected were “Computerized Medicaid data, which were linked to death certificates and to a state-wide hospital discharge database” and “Medicaid pharmacy files.” Anyone with azithromycin prescribed from 1992-2006 who had “not had a diagnosis of drug abuse or resided in a nursing home in the preceding year and had not been hospitalized in the prior 30 days.” Also, they had to be “Medicaid enrollees for at least 365 days and have regular use of medical care.”
Hey, no selection bias introduced with those criteria, right? But the authors didn’t stop there.
[youtube width=”520″ height=”270″]http://www.youtube.com/watch?v=dtNMA46YgX4[/youtube]
Supporters of the Big Data movement argue that data will change everything, but only once we break down the institutional and technological barriers that prevent us from getting at it. In his talk at TEDMED 2012 at the Kennedy Center, Stanford’s Atul Butte argues that the we already have more than enough to do real science, if only we know where to look.
I was chatting with a friend the other day about how to get people’s attention in this information-overload age, and we decided that the use of buzz words was a critical component of success. So I decided to test this catchy title and see if it leads to any more reader traffic than I usually get.
Really, I’m not messing with you. There is something to the idea of buzz word use in our search engine optimized world, but as I reflected on these three technology trends, I thought it worth pausing for a moment to reflect on just how game-changing each is for those of us in the connected health space.
Of all the top-of-the-hype-cycle buzz words in health care right now, mobile tops the list. And while we probably can’t cure cancer, reverse aging and find the true meaning of life with mobile technology, it really has revolutionized the world of healthcare.
In just about a month, the third Annual Health Datapalooza will take place in Washington, DC – a celebration of data-driven healthcare innovation (tax-payer funded data, by the way). The part of the program that I’m personally looking forward to is the Apps Expo of about a hundred or so health apps that will be showcased throughout the event. While there will be center stage presentations by a cavalcade of inspiring leaders (including Thomas Geotz and Bob Kocher), what is noteworthy is that there will be the opportunity to participate in roundtable discussions and deep dive sessions on top-of-mind areas of development such as big data, ACOs, and consumer data liberation. (liberacion!)
But what is the value in attendance? Better question, why has the event attracted more and more new attendees recently?
I’ve spent the last few years supporting private-sector healthcare innovation – especially around health IT. What I’ve come to appreciate from those dedicated to the space – whether a two person startup or a carve-out within a large technology prime – is that success at every stage of innovative development is predicated on how quickly one can create value based on the expectations of the relevant stakeholders at that stage.
This weekend, the famous Health 2.0 Code-A-Thon is coming to Boston! Hosted in conjunction with Health 2.0’s Spring Fling: Matchpoint Boston, this one-day event taking place on May 11 – 12 aims to bring the best and most talented developers together to come up with new and creative applications to improve healthcare.
And that’s not all, a total of $10K in cash prize money will be distributed among three winning teams and four runner-ups (provided by the Office of the National Coordinator). The first place team will get free passes to Spring Fling: Matchpoint Boston, the industry’s preeminent deal-making and partnership forum, and sessions on growth and commercialization strategies for today’s dynamic healthcare market. First place winners will also receive an all-expense paid trip to athenahealth’s More Disruption Please conference—a conference for entrepreneurs, innovators, and investors to come together to share innovative and disruptive ideas in the HC/HIT space in Maine this September.
We live in an age of “big data.” Data has become the raw material of production, a new source of immense economic and social value. Advances in data mining and analytics and the massive increase in computing power and data storage capacity have expanded, by orders of magnitude, the scope of information available to businesses, government, and individuals. In addition, the increasing number of people, devices, and sensors that are now connected by digital networks has revolutionized the ability to generate, communicate, share, and access data. Data create enormous value for the global economy, driving innovation, productivity, efficiency, and growth. At the same time, the “data deluge” presents privacy concerns that could stir a regulatory backlash, dampening the data economy and stifling innovation. In order to craft a balance between beneficial uses of data and the protection of individual privacy, policymakers must address some of the most fundamental concepts of privacy law, including the definition of “personally identifiable information,” the role of consent, and the principles of purpose limitation and data minimization.
Big Data: Big Benefits
The uses of big data can be transformative, and the possible uses of the data can be difficult to anticipate at the time of initial collection. For example, the discovery of Vioxx’s adverse effects, which led to its withdrawal from the market, was made possible by the analysis of clinical and cost data collected by Kaiser Permanente, a California-based managed-care consortium. Had Kaiser Permanente not connected these clinical and cost data, researchers might not have been able to attribute 27,000 cardiac arrest deaths occurring between 1999 and 2003 to use of Vioxx. Another oft-cited example is Google Flu Trends, a service that predicts and locates outbreaks of the flu by making use of information—aggregate search queries—not originally collected with this innovative application in mind. Of course, early detection of disease, when followed by rapid response, can reduce the impact of both seasonal and pandemic influenza.
The world is awash in data. It is estimated that the amount of digital information increases ten-fold every few years, with data growing at a compound annual rate of 60 percent. The big technology company Cisco has forecast that by 2013, the amount of traffic flowing over the internet annually will reach 667 exabytes. Just to put that in perspective, one exabyte of data is the equivalent of more than 4,000 times the information stored in the US Library of Congress.
This data explosion – now rather imprecisely dubbed “big data” – is both an opportunity and a curse. Having all of that information makes it possible to do things that were previously never even imaginable. Last year, the McKinsey Global Institute (MGI) conducted a major research study on big data, calling it “the next frontier for innovation, competition, and productivity.” The MGI study noted that big data is becoming even more valuable as our analytical and computing abilities continue to expand.
On the “curse” side of the big data phenomenon, the growing mountains of information also pose massive challenges to those who need to manage it. Having ever greater volumes of data to sift through to find critical insights (the proverbial needle in the digital haystack), is a growing problem for companies, organizations, and governments the world over. Sometimes, there really is such a thing as too much information.
The data deluge is especially urgent for hospitals, which are factories of data. In the typical hospital, data flows from every department and function – from emergency department admission records and HR systems, to purchasing and billing information. But, hospitals are not exactly known for effectively managing data. The healthcare provider sector is probably 20 years behind other major industry domains in terms of how its uses data. Many hospitals fail to realize the value of the data they do have – or they are overly focused on EMRs.
I’ve had the luck to attend medical school in the city of San Francisco during what will be looked back on as the start of transformational change in our health care system. My growing interest in technology and new business models as the disruptive forces behind this change, as well as marriage to a technology entrepreneur, has me frequently rubbing elbows with movers and shakers in the digital health space. One question I constantly receive (other than how I feel about being replaced by a computer) is how to get ideas and products in front of practicing physicians for product feedback or to test the market. Even more commonly, I’m asked why we are so resistant to technology and change in the way we practice. My reply usually takes some form of the following.
1. Show us the data.
The robust system medicine has developed for testing innovations in clinical care, disseminating these ideas, and transforming practice standards is being entirely overlooked (or alternatively scoffed at for being too cautious and slow) by most entrepreneurs. We insist on data to show that the newest pharmaceutical drug, procedure, or implantable device is safe and at least as efficacious as placebo, (and due to comparative effectiveness, this may soon become as compared to the standard of care). It should not be any different for an EKG iPhone app I use to rule out a myocardial infarction in your mother, or a motivational weight loss app the patient invests days of their time into with no results. These are not restaurant recommendations where a failure means bad sushi. These are people’s lives and well being, and we feel it’s unethical to start recommending unproven products.Continue reading…
Health care is in the process of getting itself computerized. Fashionably late to the party, health care is making a big entrance into the information age, because health care is well positioned to become a big player in the ongoing Big Data game. In case you haven’t noticed computerized health care, which used to be the realm of obscure and mostly small companies, is now attracting interest from household names such as IBM, Google, AT&T, Verizon and Microsoft, just to name a few. The amount and quality of Big Data that health care can bring to the table is tremendous and it complements the business activities of many large technology players. We all know about paper charts currently being transformed via electronic medical records to computerized data, but what exactly is Big Data? Is it lots and lots of data? Yes, but that’s not all it is.Continue reading…