Guest Post by Dr. Jody Ranck
As we contemplate the fallout from the Supreme Court’s decision in NFIB v. Sebelius on the Obama Administration’s Affordable Care Act, it is useful to think beyond the din of the punditry on what the decision means in an electoral cycle and consider seriously the looming crisis in healthcare.
Our health system—or better, anti-system—consumes nearly $2 trillion annually and does not deliver the value that it should. Those who think we have the best system in the world come up against the cold hard facts (if they matter in political debate anymore) of health outcomes, which indicate that we’re ranked 37th in the world and trending downward, not improving. Despite one of the most robust ecosystems for innovation in biotechnology and information technology that the world has ever seen, converting this into tangible health outcomes is an “innovation space” that we’ve yet to get a handle on.
There is hope and promising signs that these tools can be mobilized to make a dent in some of the major challenges we face such as obesity, diabetes, environmental health, and a host of other areas if we can bring politics, technology, and both the public and private sectors into the right relationship in the coming years. Technology can’t do it alone. Nor will antiquated political hubris of “death panels” and market fundamentalism fix health care. In my new book, “Connected Health: How Mobiles, Cloud and Big Data Will Reinvent Healthcare”, I explore how this might happen if we can think more strategically and engage in more grassroots efforts to engage with the “Algorithmic Revolution” in healthcare.
Mobile Health (mHealth)
Today we find mainstream publications almost daily reporting on new mobile health, or mHealth, apps to help you manage your fitness, diet or health condition. There are over 10,000 health apps in the iTunes store, making them one of the fastest-growing categories, and it is estimated that 2012 will reach at least 247 million people who have downloaded at least one app, up from 124 million in 2011, according to the analyst firm Research2Guidance. The firm estimates that the world market for mHealth apps will reach over $1.2 billion this year. These apps run the gamut from diabetes, exercise and fitness apps (Runkeeper, Fitbit), dieting (Lose It; the wireless weight scales designed by Withings), heart rate monitors (Azumio), sleep trackers (Zeo), mood trackers (Mood Tracker) and a host of peripherals that attach to your phone to provide everything from diagnostics for diseases to EKGs, eye exams (EyeNetra), and even microscopes.
Some mHealth apps use game dynamics to motivate collective action as in the case of the University of California-based CITRIS’ Pwning Asthma Triggers app that helps residents of high-risk neighborhoods identify the sources of industrial pollution that trigger asthma. One of the most interesting startups coming out of MIT is Ginger.io, a platform that enables you to combine patient data with passive data collected on one’s cellphone. Passive data provides insights on how individuals are using the device and can help one better understand social and psychological factors that can determine outcomes. There are many who are looking to mobiles to help improve one of the sticky problems of healthcare: behavioral change that is often required to manage multiple chronic diseases. Successful mHealth apps will have to demonstrate the ability to move the dial on behavioral change to warrant investment in coming years.
The Internet of Things, Health 2.0 and Mobiles as Health Hubs
Beyond mobile devices, there is the rapidly growing use of sensors that are connected to the Internet. The Internet of Things, as it is commonly known, can also play an important role in future health systems. From real-time air pollution sensors (the focus of a recent EPA Challenge, MyAir, MyHealth) and radiation sensors (Cosm (formerly Pachube)) to the growing market for wearables (Misfit Wearables, Zephyr Technology), we’re increasingly entering the early years of the Health Internet of Things. That is, sensors connected to the Internet that can transmit data related to health. When you combine this with the use of social networks for health, including platforms such as PatientsLikeMe.com, CureTogether, and general use of Twitter and Facebook for exchanging health information or organizing campaigns for health, the amount of health data and networks related to health and healthcare is exploding.
There is also the increasing number of individuals who use a variety of devices and social media platforms to track data about their health and fitness, experiment, and exchange insights. Widely known as the Quantified Self, this movement is rapidly moving beyond early adopters in Silicon Valley and beginning to have an influence in even how consumer device manufacturers think about future health and fitness devices. Qualcomm Life, perhaps anticipating the mainstreaming of aspects of the Quantified Self movement, has focused on creating the technology to integrate the range of devices in a simple, easy-to-use hub, the 2net Hub, that can make it easier for consumers to connect devices and data in their homes.
A Tipping Point: Democratizing Health Through Participatory Medicine
The exciting part of this ecosystem is not just the range of devices and impressive range of indicia we can monitor, measure, and analyze with the devices in our pockets, many of which did not exist with this level of functionality even 4-5 years ago. Increasingly the Health 2.0 movement, or those interested in the use of social media and connected health to radically change the traditional top-down orientation of healthcare, view these technologies as a way to democratize health and medicine. Calls for participatory medicine, or more patient-physician and even health system collaboration, are frequent, and there is even a Society for Participatory Medicine to debate and share information on the movement. “ePatients” are challenging the traditional medical encounter armed with data they’ve tracked on a mobile or iPhone app and with the latest research or information gleaned from platforms that provide access to clinical trials and data. Sometimes referred to as “cyberchondriacs”, the message is becoming clearer that we are reaching a tipping point where the practice of medicine and public health are going to change for good. Information and data flows are no longer a one-way street.
Government and the Need for Public-Private Cooperation
In contrast to many in the field of health technology, I do not necessarily see a single trajectory for where this is heading. There are many major technological, social, and political roadblocks and obstacle courses to navigate in the coming years. First, the most difficult challenge is the political rhetoric in the United States concerning healthcare. The recent Supreme Court decision on the Affordable Care Act and the popular politics leading up to the decision and for the indefinite future actually have little or nothing to do with existing healthcare that actually exists. There are no death panels; universal coverage is not socialism; and no country outside of places like Somalia and the Eastern Congo believe that the government should not have a place in healthcare.
We live in a time when we’ll soon be spending one (1) out of every five (5) dollars of our GDP on healthcare. Our employer-sponsored healthcare system makes no business sense and, as stated at the beginning of this article, fails so many who die and suffer needlessly. Fragmentation and an ad hoc employer-based anti-system is expensive and leaves too many people without insurance, which ends up being a driver for even inflationary healthcare expenditures.
While conservatives bemoan the Supreme Court’s decision to uphold the Affordable Care Act under Congress’s taxing power, they ought to look at how dysfunction in the system is far more taxing to the average person’s wallet. Too often the call for “consumer-driven healthcare” becomes a euphemism for cost-shifting to consumers rather than improved quality and cost-effective care. Even in systems with universal coverage, there are vibrant private sector health care businesses. From a technological perspective, the government has a vital role in areas such as standards, core infrastructure development, and regulatory frameworks to protect everything from privacy to the security of your health data. The right mix of regulatory standards and frameworks can actually help businesses flourish. We need a great deal of policy innovation in healthcare to keep pace with technological change. Innovation is not just about simplistic calls for cutting “big government”.
In support of this last point we are have already seen how creative government can support the growth of innovative companies in healthcare and also create jobs. Health and Human Services (HHS) launched its Health Data Initiative two years ago to open up government health data to entrepreneurs and citizens. This is health data our tax dollars pay for, but which was left in formats that rendered it not very user-friendly until the Initiative was launched. An event, the Health Datapalooza, was launched to bring entrepreneurs, venture capitalists, and governments together. The 2010 event had 48 participants. In early June 2012, the most recent Datapalooza had over 240 companies and 1,500 attendees and was a dramatic demonstration of how government open data initiatives armed with an entrepreneurial focus can create jobs and new products and services that can have a big impact on health. Polarized ideological posturing won’t solve the health crisis.
We also have significant technological challenges around the issue of interoperability. Having the ability to choose different devices and technologies to collect and store our data and to be able to move that data from one health plan to another or across healthcare providers is no easy feat. Most large healthcare IT programs in the 1990s–early 2000s were very capital intensive, lengthy technology implementations that are expensive to replace. This has made many healthcare providers wary of new technologies. One of the issues that both Republicans and Democrats agreed on was the incentive for electronic medical record (EMR) adoption in the stimulus package. In theory this serves as the foundation for creating data liquidity in the future. In reality, the practice of interoperability is challenging and is as much a human and organizational challenge as a technological one. The right approach to interoperability is urgently needed and can help reduce uncertainty and risk for medical device manufacturers and even for those working down stream in the area of analytics. At the Open mHealth Project (where I’m an advisory board member), we are working on filling in some of these gaps that challenge our ability to create personalized and optimized data ecosystems through an open source architecture. We believe this will reduce the amount of effort and resources to develop devices and data analytics for evaluating and inferring the impact of interventions.
Data privacy, ethics, and ownership are emerging issues that we need to address as well. The emergence of Big Data allows us to mine and analyze massive amounts of data—both structured (e.g., traditional health services research) and unstructured (e.g., data from Twitter, Facebook, or much of the data in an EMR)—and has brought the issue of privacy to the fore. It is now possible to de-anonymize data from a large national anonymized survey, for example. The World Economic Forum recently issued a paper that argues that personal data has now become a new asset class. Jerry Michalski, in addition, recounts some of the emerging ethical issues that Big Data raises – from the ways data can be used against us (a big issue in healthcare) to making us over-confident in projections and forecasts (as the financial crisis and numerous banking fiascos in recent months, e.g., J.P.Morgan, have demonstrated). Yet there is much to be gained here from early outbreak detection to creating new efficiencies in health systems and better clinical decision-making with personalized health data.
Much work needs to be done in this area to make sure that the circle of beneficiaries of Big Data is wide and includes the marginalized. I’ve been advocating the creation of a Global Data Alliance, a public-private partnership that can bring the best minds on data together to create the policy and ethical frameworks that build trust and value across the stakeholder value chain. A key feature of the Alliance would be to foster public-private partnerships to address market failures in the data value chain, from food systems to healthcare systems and insurance. Of the utmost importance are innovations that focus on products and services for low-income populations to mitigate their risk. Risk mitigation, particularly in healthcare, should not be the preserve of the top one percent. We need to build on Robert Kirkpatrick’s notion of “data philanthropy” for tangible social businesses in the healthcare space that are capable of improving health outcomes and changing risk equations for the most needy.
Last week’s Supreme Court decision is only the beginning of a long road to forge a healthier nation. We have the technological tools to create efficiencies and build transformative health systems. Now we need the human interoperability and creativity to realize the visions the technologists. That will require political leadership and imagination that has become a scarce resource at a time when we need it most.
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Dr. Jody Ranck has worked on health policy and health technology for over 20 years as a researcher and strategist. Much of his work has been in global health working on programs in Africa and South Asia. He has worked extensively with both private sector and government agencies in the area of technology forecasting and innovation strategy. He recently served on a committee at the Institute of Medicine on the use of information technologies and is an analyst for GigaOM, which recently published his book, “Connected Health: How Mobiles, Cloud and Big Data Will Reinvent Healthcare”.
