SearchHealthIT met with outgoing ONC Chief Scientist Doug Fridsma, M.D., the top U.S. official for health data standards and interoperability and informatics specialist, as well as a former practicing physician, at the annual American Health Information Management Association (AHIMA) 2014 convention in San Diego. We asked him about the most pressing health IT issues, health data interoperability, as well as his new job at AMIA, the American Medical Informatics Association, which he will start in November.
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How can interoperability initiatives move forward considering the tense political environment on Capitol Hill? How can national health IT coordinator Karen DeSalvo, M.D. and the ONC operate effectively with so much opposition?
Doug Fridsma: [Health data] interoperability is certainly in the plan that Karen has articulated, certainly in the federal health IT strategy, as well as the roadmap that's being constructed. She [has] made it very clear that success in interoperability in the country is going to require more than just meaningful use and more than just a single program. It's going to require engagement across all the federal partners that we have that deal with or touch on health data. It's going to require the private sector and organizations and associations that have skill in informatics to be able to solve these problems.
So our job at ONC isn't to do the building of all of the technology. In fact, we're not the 'Office of the National Build All the Technology,' we're the Office of the National Coordinator. Our job is to create a vision for what success looks like. You have to remember too that the Office of the National Coordinator was created under the Bush administration and continued under the Obama administration. There has been, I think, broad bipartisan support for the use of information technology to solve many of the pressing problems that we have in this country.
Describe "the learning health system" in layman's terms, and why you think it can improve patient care in both short and long runs?
Fridsma: My personal definition: A learning health system is one in which every interaction that occurs in that system, whether it's a patient, whether it's a practice, whether it's an HIE or a population, or whether it's just the general population out there at large, every interaction with that system is an opportunity to learn how to do what you're doing better.
It means for an individual patient that they have tools and resources that allow them to do better self-management of their diabetes, to be able to measure their exercise, their sleep-wake cycle and number of calories they are consuming, and to be able to learn with all those interactions how they can do better at taking care of their health. Similarly, I think at the level of a practice, doctors need to have the tools and resources so they can learn how to take better care of their patients, figure out what their quality scores are, see which are outliers in their practice that they need to spend more time on, and which are the ones they can start to engage.
The other thing I think that's important is not only the collection of data, but the dissemination of knowledge. A learning healthcare system should have both the collection of information, so you can learn from it, but also once that learning occurs, disseminating that out.
You spoke of individuals and practices. What about the big complex systems?
Fridsma: I think the whole system learns, but it does because individuals do. There are lots of definitions of what the learning healthcare system is, but in some sense, my vision is less about a learning health system and more about a system of health learners, because it's not the system that's going to learn, it's the individuals and all the other people who are part of that system.
So a learning health system takes research information and allows practices to apply that in clinical decision support rules, or for patients to apply that in a very specific way around precision medicine or personalized medicine, where their particular genetic makeup and the results of this test or drug can be applied to them specifically.
What is the role of the patient in a learning health system now, and what will it be in the future?
Fridsma: Right now there is some discontinuity. Patients oftentimes have phones that collect their steps and Fitbits that check their how they're sleeping, and scales that measure their weight, and a lot of different apps that enrich their lifestyle. But that's a separate thing from what doctors do in managing their patients and their practices. There's clinical decision support and things like that. Even at the research side of things, there's the patient-centered outcomes initiative.
But again, that's separated from all those other systems. I think our job certainly at ONC and when we think about the learning healthcare system, is not to think about stovepipes of where patients can learn and practices can learn to do better with quality assessments. We have population analytics and we have clinical research, but we need to think horizontally to say how a patient -- and their experience with their personalized data feed -- [can] contribute to how a doctor takes care of them, how the research that's coming out of a clinical enterprise can actually be applied to what they have inside their Fitbit and their data sources.
This is the first part of a three-part interview. Continue on to part two.
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