Recently, the Wall Street Journal has been writing article after article about how Silicon Valley is suddenly as hot again as in 1995. And anyone driving into San Francisco these days will have views of the city obscured with big “we’re hiring” billboards from the Groupons, Zyngas, Rockyous, and whathaveyous of the world.
In the past healthcare innovation and startups/new value creation has proceeded independent of that tech-scene and it has been much slower, dominated by buying behavior from giant incumbents who thought NIH stood for Not In Healthcare. But as my colleague and Health 2.0 co-founder Matthew Holt likes to put it: change starts at the edges. And we have seen Health 2.0 start small at the edges with the growth of patient communities, followed by other models connecting patients, payers, and providers in new ways (e.g. American Well, athenahealth, Castlight).
On May 18 SDForum is organizing a one-day event highlighting the change that is afoot in mainstream healthcare as a result of the innovation from the edges reaching the shores (and more) of mainstream health and wellness industries.
I am introducing the first keynote speaker (Holly Potter from Kaiser Permanente) and moderating a panel on one of my favorite topics: how data and innovation in analytics can make treatment and wellness decisions better, and hence create value, for all involved. While 80% of presenting companies are young (from only a few months in existence to 5 years from initial funding), there are also some pioneering established companies (Kaiser Permanente, Safeway, PAMF) who will touch upon topics like:
how ONC’s push for ‘data Liberacion’ is one of several forces helping to make health decisions more data-driven
how mobile/unplatforms, cloud-computing, and innovative use of analytics create new opportunities to understand patient behavior and introduce new, smart interventions
how chronic disease treatment is starting a transformation (funky billboards in LAX not withstanding, Lisa)
how new entrepreneurial energy is being backed by more and more funding (Healthtap is one of the companies who recently received funding and who will be on the panel that I moderate, Doximity is another company that fits that bill)
Finally, while some companies in general tech or consumer markets seem to pursue growth without a business model, this event shows how companies in healthcare who get it right (e.g. Limeade), can grow fast, do good, and become financially viable businesses. Maybe one day the WSJ will report on the exciting IPO window of healthcare technology innovation companies for a change. In the meantime, come and see what the future will look like by hearing from those who are building it now.
Marco Smit is President of Health 2.0 Advisors, the market intelligence arm of the Health 2.0 family.
The father of a wireless engineer, who made a good living designing mobile devices, contracted a rare and chronic form of athlete’s foot. Over the course of a few months, the father’s condition worsened and eventually he died. Vowing he would make sure that no-one suffered the way his father had during the last few weeks of his life, the engineer set about developing a wireless athlete’s foot detector.
After obtaining the backing of a venture capitalist, he licensed technology from a university spinout that specialised in bio-sensing and embedded it onto a wireless chipset, which he then packaged into a simple mobile device. The athlete’s foot monitor is now on the market and our wireless engineer is talking to a number of healthcare providers, including the NHS.
There are two important things about this story; first it is complete fiction – and second; anyone who has been involved in the wireless and mobile industry, will have come across real life examples of personal quests masquerading as business plans.
It’s the end of the year – an opportune time to forecast how 2011 will unfold in health care. We are likely to see some surprises, such as the sharply rising importance of primary care physicians.
Here are some predictions about the new year:
More consolidation is on its way in healthcare under Obamacare, which heightens the pressure to improve the efficiency of healthcare delivery. As part of this, more and more healthcare provider groups, even the small ones, will feel compelled to go electronic once and for all.
Valuable new, cost-effective medical tools will begin to become widely embraced. One is telemedicine. Just imagine how much more effective doctors can be if they interact with patients remotely via cameras. The technology exists now, has been successfully used in a number of situations, and it is not expensive. Soon insurance reimbursement models will permit and remunerate physicians for telemedicine “visits,” and then this will take off.
The use of genetic testing to segment patient populations and better target therapies will be one of the fastest growing segments of healthcare as a new wave of accurate, clinically actionable tests hits the market.
As health reform increasingly kicks in, there will be heightened emphasis on the importance of primary care physicians – a sharp contrast to the elevated importance of specialists for so many years. They will become the linchpins of health care and make more pivotal care decisions as more than 30 million more people enter the healthcare system and require access to them.
No matter what your opinion of Electronic Health Records (EHR) is, you would probably agree that the concept of computerizing medical records represents an innovation of sorts. The spread of innovation, or its diffusion, has been researched and modeled by Rogers as a bell shaped advancement through populations of Innovators, Early Adopters, Early Majority, Late Majority and Laggards (the blue curve in the figure below). At some point during this spread of an innovative solution a Critical Mass of adopters, or Tipping Point, is reached and the innovation is assured widespread diffusion (Gladwell). Adoption is usually described by an S-shaped curve of adopters vs. time, and the rate of adoption is the slope of the S-shaped curve at any given time (the red curve in the figure).
The Tipping Point occurs right after the rate of adoption assumes its largest value which will be maintained throughout most of the adoption process. It is worth noting that the diffusion of innovation model is not predictive. Many innovations linger and die within the Innovator circle. Another important aspect of the model is that the time variable is not constrained. Depending on the rate of adoption, it may take weeks, months or many years for an Innovation to spread throughout a given population. There is no question that EHR adoption is slowly moving up on the ascending side of a classic diffusion model bell curve, but is it moving fast enough? Is the tipping point visible? Are we there yet?
I’ve been thinking a great deal about the newly formed Center for Medicare and Medicaid Innovation. (CMI). This entity was established as a result of the Affordable Care Act (the new healthcare reform legislation) and its purpose is to “research, develop, test and expand innovative payment and service delivery models that will improve the quality and reduce the costs of care for” patients covered by CMS-related programs. The legislation gives this entity over $10 billion dollars initially and broad authority to figure out new ways of doing things better and differently than before. What is great about CMI is that they have the authority to run their programs much more like a business would without many historical governmental constraints. That’s great news for innovation, which is sorely needed in the U.S. healthcare system.
Among the key objectives that the administration has discussed is how to transition the collective mindset from one of healthcare to one of health. In other words, if a person is healthy, they do not need health CARE. This is a very important distinction; it puts the emphasis on prevention and wellness as opposed to what you do when somebody is already sick. In order to affect such a transition, there must be an emphasis on innovation to change the way we have traditionally looked at the healthcare world.
This is an interesting challenge and one that requires a great deal of thoughtfulness in how to approach the universe of innovation opportunities. As venture capitalists, I and my colleagues vet, select and monitor deals and specifically focus on how we pick winners and avoid losers. It’s a little like being asked to handicap who’s going to win the World Series, but then again, that is pretty much our job as VCs: to act like Billy Beane and pick those most likely to succeed in a capital efficient way based on detailed analysis of trends and meaningful data, not solely based on experience.Continue reading…
“How do you inspire and enable innovation in a large organization?”
That’s the question I grapple with daily as director of Kaiser Permanente’s health care innovation center. I’ve observed that it isn’t sufficient to have a dedicated Innovation Center, an Innovation & Advanced Technology Group, or in-house Innovation Consultancy design group – all of which Kaiser Permanente has. The real question to solve is: “How do you create a culture that enables innovation throughout an organization?”
To explore answers to that, this week I am joining with physicians, nurses and design thinking, quality and innovation experts from the United Kingdom’s National Health Service and Kaiser Permanente for three days in South Devon, England, at the NHS Horizon Centre for Innovation, Education & Research in Healthcare, to share successful failures and best practices in innovation.
One contribution the NHS already has shared with the extended health care innovation community is a guide that helps leaders enhance the conditions for innovation: “Creating a Culture of Innovation.” Given that organizational leaders’ behaviors have a disproportionate influence on creating a culture that either hinders or aids innovation, Lynn Maher and Helen Bevan of the NHS Institute for Innovation and Improvement and Paul Plsek distilled the organizational research on innovation into a helpful “how to” guide outlining the seven dimensions of culture that support innovation. These principles, summarized below, can be applied to any organization.
So how can you begin building your own innovative culture — and how have we used these principles at Kaiser Permanente?
Risk-taking: Establish a climate in which people feel OK trying out new ideas by not shutting down ideas before they’ve been vetted. Leaders should demonstrate they are more interested in learning from failure than punishing people for it.
To foster innovative thinking at Kaiser Permanente, our Information Technology leadership created an Innovation Fund, an internal program that provides seed funding and support to teams of doctors and employees to facilitate the rapid prototyping of novel IT ideas and diffusion of successful innovations. Leadership also created iLabs, an innovation lab that serves as a technology research, advisory and software prototyping group that works with Kaiser Permanente innovators to help develop technology solutions for health care.
Resources: Resources are meant in the broadest sense of the term here. The traditional definition signifies an organizational commitment to innovation, but resources need not always be concrete. Time, permission and autonomy to innovate may be what is needed. For example, Kaiser Permanente’s Innovation Fund not only provides seed funding, but access to mentors and tools to jumpstart innovation.
All eyes are on Toyota’s recall of 8.5 million vehicles due to faulty gas pedals and brakes. The recall has sparked congressional hearings, a probe by the U.S. Department of Transportation, possible criminal charges stemming from a federal grand jury investigation and numerous civil lawsuits, all in the name of driver safety.
This aggressive response to Toyota’s mistakes is appropriate, even though the human toll from its miscues has been, thankfully, relatively modest – 34 alleged deaths and a few hundred injuries. Not to downplay this misery, but in stunning contrast, consider this: More than 100,000 Americans die annually in U.S. hospitals because of avoidable medical errors, according to the Institute of Medicine (IOM), which also says that medical errors rank as America’s eighth leading cause of death. This is higher than auto accidents (about 45,000) and breast cancer (about 43,000). And the problems don’t end here. Studies show that approximately 19% of medications administered in hospitals are done so in error, injuring about 1.3 million each year, according to the FDA.
Our healthcare system is now facing a problem that has plagued business leaders for years: how do you balance consistency and innovation?
The drive for consistency in healthcare is based upon the fundamental observation that physicians across the country treat similar medical conditions in dramatically different fashions. Sometimes, these different approaches are costly, such as using a more expensive treatment when a less expensive approach might be as effective. In other cases, these practice variations are dangerous – failing to provide patients with treatment the evidence suggests is best.
Standardizing the delivery of care — identifying “best practices,” and then insisting physicians follow these guidelines – could, in theory, save money while improving quality, and is the basis of Obama’s healthcare proposal.Continue reading…
Most biomedical research is framed by an outdated view of disease, a linear mind-set that focuses on simple causes rather than complex relationships within dynamic systems. If we are to achieve President Obama’s audacious goal of “a cure for cancer in our time,” we must radically alter the way we think about biology and disease.
Physicians and medical researchers are traditionally taught to consider disease in terms of simple causes and isolated linear pathways. This one-gene-one-disease approach also informs the way most animal models of disease are developed. Technology readily enables researchers to engineer mice with specific molecular defects in one or a small number of genes as an experimental proxy for human disease. While some of these models are informative and reasonably predictive, most are not.
The limitations of animal models are highlighted by results emerging from powerful genomic studies of human diseases ranging from Type 2 diabetes to pancreatic cancer. For these and many other conditions, the cause is not a single defect, or even a handful of defects, but rather, combinations of hundreds of possible defects, each contributing slightly to the overall risk of disease.