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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.


flying cadeucii The electronic health record (EHR) is now used by the majority of physicians during every patient encounter. The EHR has become the most important tool in our “black bag” and precisely for that reason, the EHR must be highly accurate and free of bias. As our most heavily utilized tool, the EHR must also be flexible and highly optimized so as to ensure it does not adversely impact the delivery of healthcare. Unfortunately, numerous surveys have found widespread physician dissatisfaction with EHR design.

The fact that EHR programming code is shielded from objective scrutiny by independent evaluators increases the risk that the EHR will contain errors and bias which could adversely impact our patient’s health, hinder our ability to deliver healthcare, “warp” the design of the healthcare system and drain financial resources from our patients and society.

EHR “errors” are well documented in the literature and are referred to as “e-iatrogenesis” or “technology induced” errors. “Bias” in EHR programming code is not discussed in the literature.


flying cadeuciiThe SEC has finally finalized its crowdfunding rule (presser) under the JOBS Act. The health innovation crowdfunding crowd has been waiting for these rules for quite some time, as has the rest of the crowdfunding fan club. (It’s only taken three and a half years.)

So, was it worth the wait?

The crowdfunding rule (full text) sets the stage for broader participation in early-stage investing and may empower crowdfunding platforms (“intermediaries,” in SEC-speak) to compete with angel funding platforms servicing “accredited investors” (SEC-speak for high net worth folks who can afford to lose their entire investment in a startup). It is a democratizing move consistent with the ethos of the internet and digital innovation.

Let’s look at some of the particulars and then think about whether this is a good thing for startup companies (“issuers”) that might want to sell securities rather than their products or promotional T-shirts, and for intermediaries — such as Kickstartr etc. — that might want to have a role in matchmaking individual investors with issuers. (Kickstartr itself has reportedly said it’s not interested in going down this path; IndieGoGo is interested, though.)


LudditeWe all know Luddites.  They proudly pronounce their rejection of Facebook and feign disgust about how they finally “broke down” and bought that awesome Motorola Razor they still carry. Maybe you are a Luddite or pretend to be because you can’t make Gmail work on your phone. So who was this Ludd and why is he the timeless symbol of rage against the machine?

My guess was that the original Ludd was probably some horse breeder that bet the farm against the future of the automobile. As it turns out, the Ludd story is not at all what you’d expect.

Legend has it that in 1779, a fed up British factory worker named Ned Ludd took his aggression out against the knitting machines he was employed to operate, smashing two of them to pieces with a hammer. In this one brazen act of defiance, he became the symbol of man’s rebellion against automation, technological displacement, the death of artisanship, and the worsening conditions of the working class.

Not long after, as the Industrial Revolution gained steam (terrible, I know) young Ned became the poster boy, quite literally, for factory worker uprisings each of which was punctuated with the destruction of machines.

The Luddites met in secret and their operations ranged from sabotage to all out warfare, including a battle with the British Army. They became so fearsome that industrialists had secret chambers constructed in their factories in which they could hide should the Luddites come knocking. Fearing that the name “Ned” lacked gravitas, his PR team apparently took to branding him King Ludd or General Ludd.


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I am an IT geek physician. I have my an EHR which I created and control.

Today, I wanted to understand my diabetic practice a little more, so I dumped all my HbA1c data out of my EHR and into a spreadsheet where I was able to manipulate the data and learn a few things about my practice.

I learned that:

If my patient had a HbA1c ≥ 8, the likelihood that the HbA1c would be < 8 at the next visit is 68%.

If my patient had a HbA1c ≥ 8, the likelihood the HbA1c would be even higher at the subsequent visit is 29%.

If my patient had a HbA1c ≥ 8, the average change in the HbA1c at the next visit was -0.7.

If my patient had a HbA1c < 8, the likelihood that HbA1c at the subsequent visit would exceed 8% would be 15%.


flying cadeuciiWhen it comes to health information technology in the United States, are you an optimist or pessimist?

Do you think it’s likely people who want health information will soon have routine, seamless digital access to it?

Most physicians and hospitals have at least some sort of electronic health record, yet big adoption gaps remain among physicians as just over half now have electronic health records. We can declare success and move on, right?


Most of us still cannot get health information when we want or need it. Health professionals and care systems trying to implement value-based payment and delivery reforms struggle to get the information they need to do that transformation. Communities trying to improve the health of their citizens have trouble getting the data they need and turning it into useful information.


flying cadeuciiTo understand how a landmark new report on diagnostic error breaks the mold, go past the carefully crafted soundbite ­(“Most people will experience at least one diagnostic error in their lifetime, sometimes with devastating consequences”) and rummage around the report’s interior.

You can’t get much more medical establishment than the Institute of Medicine (IOM), also called the National Academy of Medicine, author of the just-released Improving Diagnosis in Health Care. Yet in a chapter discussing the role played in diagnostic accuracy by clinician characteristics, there’s a shockingly forthright discussion of the perils of age and arrogance.

“As clinicians age, they tend to have more trouble considering alternatives and switching tasks during the diagnostic process,” the report says. Personality factors can cause errors, too: “Arrogance, for instance, may lead to clinician overconfidence.”

Wow. Sure, both those assertions are extensively footnoted and hedged later with talk of the importance of teams (see below). Still, given the source, this practically qualifies as “trash talking.”

Of course, those quotes didn’t make it into the press release. There, inflammatory language was deliberately avoided so as not to give opponents any easy targets. (Disclosure: I was an advocate of an IOM report on this topic while consulting to an organization that eventually helped fund it. After testifying at the first committee meeting, I had no subsequent involvement.)


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THCB congratulates (FD: content partner and corporate supporter) HealthCatalyst in the wake of last week’s sold out Healthcare Analytics Summit (HAS15) in Salt Lake City.

The Utah-based startup widely-rumored to be headed for the Hot IPO List  drew a crowd of over a thousand attendees, including vendors, clients, c-suite healthcare types, data geeks and industry observers.    

If you want to wrap your brain around what sets Health Catalyst apart from the growing number of pretenders in the red-hot analytics space, you had only to look at the jaw-droppingly impressive client list: Partners Health Care, Stanford Health System, Kaiser Permanente Colorado, Texas Children’s, Allina Health,  and many, many more.


Dale SandersThe number of mergers, acquisitions, and collaborative partnerships in healthcare continues to skyrocket. That’s not going to change for the next few years unless the FTC decides to be more restrictive. In all of these activities, older generation executives (I can say that because I’m older) have underestimated the importance and difficulties—technically and culturally—of integrating data and data governance in these new organizations, and the difficulties are exponentially more complicated in partnerships and collaboratives that have no formal overarching governance body. In 2014, 100 percent of Pioneer ACOs reported that they had underestimated the challenges of data integration and how the lack of data integration has had a major and negative impact on the performance of the ACOs.

Seamless Data Governance

After 33 years of professional observations and being buried up to my neck in this topic, especially the last two years as the topic finally matures in healthcare, I’m convinced that the role model organizations in data governance practice it seamlessly. That is, it’s difficult to point a finger directly at a thing called “Data Governance” in these organizations, because it’s completely engrained, everywhere. As I’ll state below, it reminds me of the U.S. transition in the early 1980s when organizations finally realized that product quality was not something that you could put in an oversight-driven Quality Department, operating as a separate function. Quality must be culturally embedded in every teammates’ DNA. Data governance is the same, especially data quality.


Healthcare is abuzz with calls for Universal Patient Identifiers. Universal people identifiers have been around for decades and experience can help us understand what, if anything, makes patients different from people. This post argues that surveillance may be a desirable side-effect of access to a health service but the use of unique patient identifiers for surveillance needs to be managed separately from the use of identifiers in a service relationship. Surveillance uses must always be clearly disclosed to the patient or their custodian each time they are sent by the service provider or “matched” by the surveillance agency. This includes health information exchanges or research data registries.

As a medical device entrepreneur, physician, engineer, and CTO of Patient Privacy Rights, I have decades of experience with patient identifier practices and standards. I feel particularly qualified to discuss patient identifiers because I serve on the Board and Management Council of the NIST-founded Identity Ecosystems Steering Group (IDESG) where I am the Privacy and Civil Liberties Delegate. I am also a core participant to industry standards groups Kantara-UMA and OpenID-HEART working on personal data and I consult on patient and citizen identity with public agencies.