Leonard Kish talks to Douglas Fridsma, President and CEO at American Medical Informatics Association, about his work in the Office of the National Coordinator for Health Information Technology, or ONC, and the barriers to implementing MIPS in the most useful and transparent way. In order to communicate the data, of course, we’ll need informatics; but how will that work? And which comes first, policy or technology?
Leonard Kish: When you first began your studies in medical informatics, was there a sense that the field was a science?
Doug Fridsma: After working on the Standards of Interoperability Framework for the National Cancer Institute – which was essentially crowdsourced, I engaged government, research and other pharmaceutical companies and standards organizations to basically come up with what that standard should be – I had an opportunity to go out to the University of Arizona and ASU. Ted Shortliffe, who had been my mentor at Stanford, had just been appointed to be the Dean of the new medical school at the University of Arizona.
No, there is no Uber of healthcare, even as everyone claims to be or wants to be the Uber of healthcare. Others rail against it.
Part of it is that an Uber for healthcare sounds great! The sharing economy! But what is it? What would it even look like? Everyone has their own interpretation: is it house calls? appointment scheduling like ZocDoc? telehealth? PatientsLikeMe?
The movement Uber, AirBnB and the like embody is often referred to as “the sharing economy.” No matter what you call it: sharing, borrowing or buying, it’s a platform for effective exchange, enabled by the peer to peer connections over the internet, but it’s not new, just more mobile, more convenient with more specific use cases around surplus capacity of some sort.
The model was pioneered by companies like craigslist and eBay, who first offered free or low-cost methods of buying and selling everything from toys to automobiles; and sharing information to everything from lost dogs to love connections. Using these early internet tools to find a job, a book group, or a place to unload your old IKEA furniture led the way to today as the sharing takes place with mobile assets (cars) enabled by smart phones.
Leonard Kish, Principal at VivaPhi, sat down with Ed Park, COO of athenaHealth, to discuss how interoperability is defined, and how it might be accelerating faster than we think.
LK: Ed, how do you define interoperability?
EP: Interoperability is the ability for different systems to exchange information and then use that information in a way that is helpful to the users. It’s not simply just the movement of data, it’s the useful movement of it to achieve some sort of goal that the end user can use and understand and digest.
LK: So do you have measures of interoperability you use?
EP: The way we think about interoperability is in three major tiers. The first strata (1) for interoperability can be defined by the standard HL7 definitions that have been around for the better part of three decades at this point. Those are the standard pipes that are being built all the time. So lab interoperability, prescription interoperability, hospital discharge summary interoperability. Those sort of basic sort of notes that are encapsulated in HL7. The second tier (2) of interoperability we are thinking about is the semantic interoperability that has been enabled by meaningful use. The most useful thing that meaningful use did from an interop standpoint was to standardize all the data dictionaries. And by that I mean that they standardized the medication data dictionary, the immunizations, allergies and problems.
Grahame Grieve is a long-time leader within HL7 and one of the key drivers behind FHIR. He chats with Leonard Kish about what’s been happening and what’s ahead for interoperability.
LK: First tell me how you got into standards… it’s kind of an odd business to get into. Why have you chosen this and why are you excited about it? G: It happened by accident. I was working for a vendor and we were tasked with getting some exchanges and I wanted them to be right the first time. That was the philosophy of the vendor. If we did it right the first time, then we wouldn’t have to keep revisiting and that meant that using the standards correctly. The more I got involved, the more I discovered that it wasn’t obvious how to do that…and that the standards themselves weren’t good. I felt personally that we need really good standards in healthcare. So it became a personal mission and I got more involved through the company I was working for and eventually I left so I could continue doing what I wanted doing with the standards – I enjoy the community aspect of the standards and feel very strongly that it’s worth investing time in and I had the opportunity to build a business out of it, which not many people do. So now I freelance in standards development and standards implementation. LK: There’s a lot of talk in Congress about the lack of interoperability and everyone probably has their own definition. Do you have a working definition of interoperability or is there a good definition you like for interoperability? G: The IEEE definition to get data from one place to another and use it correctly is pretty widely used. I guess when you’re living and breathing interoperability you’re kind of beyond asking about definitions. LK: Are there ways to measure it then? Some people talk about different levels; data interoperability, functional interoperability, semantic interoperability. Are there different levels and are there different ways to measure interoperability? G: We don’t have really have enough metrics. It’s actually relatively easy to move data around. What you’ve got to do is consider the costs of moving it, the fragility of the solution, and whether the solution meets the user’s needs around appropriateness, availability, security, and consent. Given the complexity of healthcare and business policy, it’s pretty hard to get a handle on those things. One thing that is key is that interoperability of data is neither here nor there in the end because if providers continue with their current work practices, the availability of data is basically irrelevant, because they treat themselves as an island. They don’t know how depend on each other. So I think the big open area is clinical interoperability. LK: Interoperability in other verticals mostly works. We hear talk about Silicon Valley and open APIs. There’s perhaps less commotion about standards, maybe because there are less conflicting business interests than in healthcare. Why is healthcare different? G: First of all – from an international perspective, I don’t think other countries are by and large better off or different (where incentives are different). They all have the same issues and even though they don’t have the business competition or the funding insanity that you do in the US, they still have the same fundamental problems. So I hear a lot of stuff from the US media about that and I think it’s overblown. The problem is more around micro level transactions and motivations for them and fundamentally the same problem around getting people to provide integrated clinical care when the system works against them doing that. LK: So can you give me an example of how things are maybe the same with NHS or another country vs. the US in terms of people not wanting to exchange clinical data? G: In Australia, there’s a properly funded medical health care system where the system is overwhelmed by the volume of work to be provided. No one get’s any business benefit from not sharing content with other people. Still, because you have to invest time up ahead to exchange data and other people get the benefits later, there’s very low participation rates for any kind of voluntary data sharing schemes that you set up. There’s scandalously low adoption rates. And that’s not because it’s not a good business idea to get involved but it’s because the incentives are misaligned at the individual level (and the costs are up front). LK: Right, so it’s maybe it’s also a lack of consumer drive? It’s there data and you’d expect the incentives to align behind them, but they don’t ask and don’t get, maybe because we (or our providers) only access your record when we really need them. It’s not like banking or email or other things we use on a daily basis? G: Probably that’s part of it, but from a consumer’s point of view, what does it do for them getting access to their data? Continue reading…
Leonard Kish sits down with Julia Hutchins, CEO of the Colorado HealthOP, to talk about the recent surprise when Co-ops were informed the federal government would pay just 12.6 percent of the money they’d requested …
LK: Julia, tell me a little about the history of CO-OPs in general and the Colorado Health-OP in particular. When were they formed? Why were they formed?
JH: The CO-OP program was an important part of healthcare reform. The CO-OPs were part of a bipartisan compromise to ensure that there was competition in the individual and small group insurance markets and to ensure that there was competition on behalf of consumers. CO-Ops have enabled lower costs and more responsiveness to consumers as the market moves from one that was previously medically underwritten to one where anybody can buy health insurance regardless of their health status.
Adam Wright of Partners and colleague Dean Sittig asked themselves, with all the talk about information blocking and interoperability happening in congressional hearings this year, “How should we actually define interoperability?”
Leonard Kish, Principal at VivaPhi, sits down with Wright to talk about the EXTREME (EXtract, TRansmit, Exchange, Move, Embed) use-case based definition and more.
LK: So let’s just start from the beginning. Introduce yourself, how’d you get into interoperability and what are you working on.
AW: I’m an associate professor of medicine at Harvard and I work at one of the Harvard affiliated teaching hospitals – Brigham and Women’s Hospital in the general medicine division there although my background is in biomedical informatics…I have a PHD in biomedical informatics. Before that I studied math and computer science. I got into health IT and interoperability because it just seemed like a ripe and interesting place to be applying things that have worked in other industries and asking “How can we apply some of this thinking to problems in healthcare?” Continue reading…
At the end of March the Amercian College of Cardiology (ACC) and the American Heart Association (AHA) issued a joint statement saying they “will begin to include value assessments when developing guidelines and performance measures (for pharmaceuticals), in recognition of accelerating health care costs and the need for care to be of value to patients.”
You may have heard of value-based medicine, but are we entering a new era of value-based medications or value-driven pharma?
Price transparency is great, but it has be combined with efficacy to get to value (price for the amount of benefit). Medical groups are catching on to how important value assessments are, because if patients can’t afford their medication, they won’t take their medication, and that obviously can turn into poor outcomes.
Twenty-seven percent of American patients didn’t fill a prescription last year according to a Kaiser Family Foundation Survey. This trend seems likely to continue as we move toward higher-deductible plans, where those with insurance can have great difficulty affording medications.
Included in the ACC/AMA statement was a quote from Paul Heidenreich, MD, FACC, writing committee co-chair and vice-chair for Quality, Clinical Affairs and Analytics in the Department of Medicine at Stanford University School of Medicine.
“There is growing recognition that a more explicit, transparent, and consistent evaluation of health care value is needed…These value assessments will provide a more complete examination of cardiovascular care, helping to generate the best possible outcomes within the context of finite resources.”
Spreading risk and payment to different members of the health care value chain is beginning to make it apparent to more people and organizations that resources are finite. Patients and their physicians are starting to ask which treatments are worth the cost and have best likelihood of adherence.
An outgrowth of the move toward digital health and accountable care is that we’re entering every patient into a potential personal clinical trial with their data followed as a longitudinal study, and we can look much more closely at efficacy and adherence and reasons why it happens and why it doesn’t.
It won’t be long before we start to see comparative effectiveness across a variety of treatments and across a variety of populations. When we can connect outcomes data, interventions and costs all in the same picture we begin to see where the value (price against results) is and where it isn’t.