In his new book, #SOCIALQI: Simple Solutions for Improving Your Healthcare,
We spoke recently with McGowan to learn more about the ideas he outlines in the book, and about the role of continuing medical education providers in the new SocialQI system he envisions will improve healthcare quality by re-engineering the information flow using social technology.
MM: How did you come to the ideas you talk about in the book?
McGowan: For years reports on the healthcare system in the U.S. have been describing a system that is broken and fragmented. The U.S. ranks 16th among developed countries in the quality of care that is provided, but year after year the U.S. ranks first in cost of healthcare. What has always struck me is that our quality problems are not as much about the level of care as they are about the variations in care. In some U.S. regions and in some U.S. healthcare systems, we are able to provide and have access to some of the best care in the world—this is why the ultra-rich and nobility from around the world come here for care. But in other regions and in other healthcare systems, the care that is provided is downright bad.
This variation in care has worsened over the past decade to the point where your zip code is now considered one of the most important risk factors that must be considered when determining your life expectancy or predicting healthcare outcomes for you and your loved ones.
To me this is pretty clearly a problem of information flow. Clinical best practices are not being shared, and when shared, they are not being implemented. In a very real way, what we have here is a failure to communicate.
MM: What are some of the main themes you explore in the book?
McGowan: My themes are pretty simple:
- To ensure optimal healthcare outcomes and to flatten the variability across the systems, patients need other patients, physicians need other physicians, scientists need other scientists.
- To maximize wellness and healthcare quality, we must have a system architecture that simplifies social engagement, information flow, and collaboration.
- As the system architecture is built, we must support the end users (patients, physicians, and scientists) such that they can effectively leverage the system.
- As new collaborative healthcare models emerge, they cannot be left to chance. We need broad, intelligent engineering to accelerate change.
MM: What makes you confident that people in all three of the current silos will be willing and able to do the work involved in building and working the SocialQI system?
McGowan: Confident is not a word I would choose to use—as much time as I have spent exploring these problems and sifting through the potential solutions, it is tough to find enough evidence to support any degree of confidence. On the other hand, we do not have any other choice.
#SOCIALQI: Simple Solutions for Improving Your Healthcare offers what some have called “a Goldilocks solution” for healthcare. For years the solutions for the emerging healthcare crises have been focused on two fronts: broad policy or individual empowerment. But the truth is, policy debates will not be resolved in short order—they can’t be. Democracies are not built for revolutions like the one we need in healthcare; this approach is too big. On the other hand, individual empowerment will never have the impact that is needed. It can’t, as we all know behavior change is difficult and it is inconceivable that 300 million Americans can be separately empowered to sustainably make better choices; this approach is too small.
Instead, I provide a road map to overcoming our healthcare-quality crisis by leveraging communities and collective intelligence. This book is not about technology, though technology plays an important role. This is a story about the way information flows, the forces that restrict information flow (either intentionally or unintentionally), the systems that can be built to optimize information flow, and the skills we would all need in order to make use of this new data stream.
I am quite frank—of the many solutions presented within the book, some are new, some are borrowed, and some have evolved through collaboration. Some of the solutions are proven, some are being piloted, and some are too disruptive to currently find a home, but they each offer a new perspective for the inextricably siloed networks of patients, of physicians, and even of the broader fields of biomedical research and innovation. Throughout the book, we spend some time coming to learn how these various silos are currently structured, how they got where they are today, and how we can fix this.
MM: What we currently seem to have is a mishmash of all sorts of systems, public and private. Do you see one system ultimately becoming the dominant one? If not, how efficient can the system be when not everyone is on the same page?
McGowan: This is a great question. The reality is that it is too early to tell how this will all play out, but what we must begin to define and better understand is what systems are showing signs of success, what elements of these early systems must be scaled up, and what elements of these systems must be jettisoned. My belief is that we are a long way from having the perfect system, and for that reason we must become more diligent in ensuring rigor in the study of what is already available.
Here is what we do know: Whether one system prevails or a dozen systems become federated such that they become interoperable, there are critical engineering elements that must be leveraged. Real change can only come from engineering new collaborative models of information flow, learning, and healthcare improvement. To do this we need to build systems for social learning and these systems must be integrated, open and connected, social, controlled, incentivized, and able to leverage a culture of improvement.
But once this system or these systems are engineered, their impact will ultimately depend on the ability of end users (patients, clinicians, and research scientists) to leverage the systems to drive quality improvement. And there are critical lessons we are already learning here too. Stakeholders must be able to establish credibility and reputation; filter, curate, and search within these new knowledge streams; provide and receive feedback and criticism; accurately assess their own “topic” literacy; and critically think through their high-stakes decisions.
It is these system needs and these individual end-user needs that I explore in great detail within the book.
MM: What role does continuing medical education play in SocialQI?
McGowan: The CME system was designed to support lifelong learning and to standardize the competence of healthcare professionals—this we can pretty much agree on. But beyond this, it seems that CME has become a vehicle for regulatory bodies to exert control over the healthcare profession. As a result, the acronym CME has collected a lot of baggage over the years.
As it relates to SocialQI, what we need is a better system for continuing professional development. Study after study has demonstrated a negative association between knowledge and experience such that physicians with more experience are less likely to adhere to standards of practice for diagnostic and screening tests, as well as preventive healthcare. For example, in one study cardiac surgeons who had been in practice longer had higher operative mortality rates, and patients with recent heart attack had a 1 percent increase in mortality for every two years their treating physician had been in practice. In another study, physicians with more years in practice had longer hospital stays, higher risk of in-hospital mortality, and higher risk of 30-day mortality than patients treated by physicians who had been in practice five years or less. So clearly a system offering lifelong support and practice improvement is necessary.
Within the framework of SocialQI, I suggest that building a collaborative system for information flow, learning, and healthcare improvement is the first step, and then over time we could integrate a variety of broader content types into the system. In other words, our need is for a better system to connect the clinician learners, and then we can revisit whether the types of content and activities that we have come to produce as “CME” add value. I continue to be haunted by the consistent finding that CME as we know it “may be effective” in support of short-term learning. But instead of giving up hope, I believe we need to address the underlying system for information flow and learning first.
MM: If SocialQI takes off, would we still have traditional CME as we now know it?
McGowan: It may be too early to answer this question effectively, but if I had to speculate, I would say that the SocialQI system would offer a system for distribution and engagement that far surpasses anything we rely on currently. Once the healthcare community is connected and once the system supports a culture for learning, then the content that is being produced by the CME community may have new life. Once learners are able to connect their learning to that of their peers and once a rapid-learning model is actualized, then didactic lectures, small-group workshops, and even asynchronous online learning may be found by the right learners at the right times (a major problem with the existing system). With a better system learners will find a more supportive architecture for learning, and the CME community may very well find a new environment in which their programs blossom.
MM: How does the AMA PRA credit system fit into SocialQI (or does it)? If not credit, what incentives will there be to drive healthcare provider participation?
McGowan: Not to be difficult, but I would never think of the AMA PRA credit system as an incentive to participate in anything, though I would accept that that is why it was initially designed.
Within the book I tackle the idea of incentives in great depth. I dedicate an entire chapter to the exploration of behavioral science and one of the critical “system needs” that I lay out in Chapter 7 is effectively engineering incentives. In brief, I think we have enough evidence to suggest that extrinsic incentives like CME credit play a minimal role in who participates and who benefits from CME. Instead we need to revisit why physicians learn, why they seek out new information, and why they change behavior. The SocialQI model relies on the science of behavior change and the science of social networks to refocus the incentives discussion. AMA PRA credits as an element of credentialing will likely always be on the table, but the sooner we move beyond thinking of this as an incentive or as a metric of engagement then the sooner the CME community can refocus on what really matters: engagement, learning, and practice change.
You May Also Want to Read: