Tech

flying cadeuciiEverywhere we turn these days it seems “Big Data” is being touted as a solution for physicians and physician groups who want to participate in Accountable Care Organizations, (ACOs) and/or accountable care-like contracts with payers.

We disagree, and think the accumulated experience about what works and what doesn’t work for care management suggests that a “Small Data” approach might be good enough for many medical groups, while being more immediately implementable and a lot less costly. We’re not convinced, in other words, that the problem for ACOs is a scarcity of data or second rate analytics. Rather, the problem is that we are not taking advantage of, and using more intelligently, the data and analytics already in place, or nearly in place.

For those of you who are interested in the concept of Big Data, Steve Lohr recently wrote a good overview in his column in the New York Times, in which he said:

“Big Data is a shorthand label that typically means applying the tools of artificial intelligence, like machine learning, to vast new troves of data beyond that captured in standard databases. The new data sources include Web-browsing data trails, social network communications, sensor data and surveillance data.”

Applied to health care and ACOs, the proponents of Big Data suggest that some version of IBM’s now-famous Watson, teamed up with arrays of sensors and a very large clinical data repository containing virtually every known fact about all of the patients seen by the medical group, is a needed investment. Of course, many of these data are not currently available in structured, that is computable, format. So one of the costly requirements that Big Data may impose on us results from the need to convert large amounts of unstructured or poorly structured data to structured data. But when that is accomplished, so advocates tell us, Big Data is not only good for quality care, but is “absolutely essential” for attaining the cost efficiency needed by doctors and nurses to have a positive and money-making experience with accountable care shared-savings, gain-share, or risk contracts.

Continue reading “The Power of Small”

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I’ve been thinking about EMRs, electronic medical records, lately. It’s a subject, despite some professional experience, I don’t feel particularly close to. In fact, if anything, they are a source of consternation.

As an industry insider, I see them as an expensive albatross around our collective neck. As a human centered design advisor, I see them as an encumbrance for both providers and patients.

And, as a patient I see them largely as an opaque blob of data about me with a placating window in the form of a portal.

Which makes me wonder, am I obsessed with EMRs lately?

One of the reasons is certainly my personal interest in technology. And, while I don’t work in health IT, it’s natural to draw some connections. For instance,Wikipedia is consistently in among the top 10 most visited internet sites ( it is currently number 6 ).

And, say what you will about citing Wikipedia, but a 2010 study found it as accurate as Britanica.

Google trusts Wikipedia enough to use it as the primary source for its knowledge graph cards; and we’ve all settled a bar bet by finding some fact where a Wikipedia article is the canonical answer.

The secret sauce for Wikipedia is in it’s roots. Literally, the root of its name, wiki, describes the underlying structure. Wikis were the internet’s a solution to knowledge bases – large repositories of information about a process or thing. Companies had been using knowledge base software for years. Traditionally, a central maintainer, often a sort of corporate librarian, curated information, such as common answers to customer questions, so customer service reps could find it quickly.

Continue reading “What If EMRs Worked Like Wikipedia?”

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Data Response Curve

All medical students learn about the dose response curve in pharmacology lectures. The dose-response curve informs us of how we should dose a medication in the context of its efficacy and its toxicity. Too little medicine won’t have the desired effect, and too much medicine can be toxic.

In the era of digital health, data have become the new “big pharma,” and we are facing the emergence of a data-response curve in which access to too little data is inactionable, and access to too much data can be overwhelming. Digital health devices abound today, and has enabled quantification of nearly every health and wellness metric imaginable. Sadly, in our exuberance about these new sources of data, we often conflate “more data” with “better data.”

In the era in which data have become the booming commodity of exchange in healthcare, we describe an emerging data-response curve. Large data sets can be at best clarifying or at worst self-contradictory. Too little data on the data-response curve, as with medication dosing, can be insufficient for effective action or decision-making. Too much data can be toxic to the user such as the physician, leading to poor decisions or worse, to analysis paralysis.

We live in a world of exploding data, and we need to be thoughtful. Medicine is a people business in need of data, not a data business on need of people. In reductive form, all humans make decisions based on inputs (data) from their environment and on individual analysis of the data in the form of non-linear, non-quantifiable perception. When we as doctors, policy-makers, or simply as human beings receive these inputs, one of three things happens: 1. We make a decision to do something (for example a treatment decision based on abnormal data), 2. We make a decision to do nothing (for example, normal data which we believe requires no action), or 3. We need more data in order to make an informed decision to do item #1 or item #2. More does not necessarily equal better data. More data is simply more.

Better data are actionable data wrapped in the context of the patient and the patient’s condition. Imagine each piece of objective data connected to concurrent subjective data, and surfaced in the context of a specific condition relevant to the patient. HealthLoop enables patients to generate contextual objective data married to their subjective symptoms and served to a clinician in an actionable context. High signal and low noise are the digital health equivalents of on the dose-response curve of a favorable therapeutic window.

See where some folks live on the Chart. Where do you live?

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Leslie Kernisan new headshotA friend called me the other day: he is moving his 93 year old father from New England to the Bay Area.

This is, of course, a relatively common scenario: aging adult moves — or is moved by family — to a new place to live.

Seamless transition to new medical providers ensues. As does optimal management of chronic health issues. Not.

Naturally, my friend is anxious to ensure that his father gets properly set up with medical care here. His dad doesn’t have dementia, but does have significant heart problems.

My friend also knows that the older a person gets, the more likely that he or she will benefit from the geriatrics approach and knowledge base. So he’s asked me to do a consultation on his father. For instance, he wants to make sure the medications are all ok for a man of his father’s age and condition.

Last but not least, my friend knows that healthcare is often flawed and imperfect. So he sees this transition as an opportunity to have his father’s health — and medical management plan — reviewed and refreshed.

This last request is not strictly speaking a geriatrics issue. This is just a smart proactive patient technique: to periodically reassess an overall medical care plan, and consider getting the input of new doctors while you do this. (Your usual doctors may or may not be able to rethink what they’ve been doing.) But of course, if you are a 93 year old patient — or the proxy for an older adult — it’s sensible to see if a geriatrician can offer you this review.

Continue reading “What PHR Should I Use? It’s Complicated.”

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Tech Skool

An article in Information Week caught my eye recently . It reviews a new program offered by Texas A&M with support from Dell to help medical students and other healthcare professionals “come to terms with  the ways technology is changing their jobs”. The article, Doctors Can Go Back to Tech School, says Texas A&M will launch its new health technology academy later this year as part of its continuing medical education program.

Now, don’t get me wrong. I’m all for education and career improvement. I’m just not sure that the best way to improve Health IT is to get more physicians trained in IT so they can, as the article suggests, move into IT roles. How about giving full time clinicians who have an interest in improving Health IT some extra support and time so they can help those who work in IT better understand what clinicians need to do their jobs efficiently and safely? How about just a little paid time away from the daily treadmill of patient care to educate IT about the nuances of medicine and clinical workflow? I believe understanding that would do more to help IT deliver better solutions.

Over the course of my career, I’ve been many things. First and foremost, I am a physician. Only a true clinician understands how clinicians think and work. For many years, I continued to practice even when it no longer made a whole lot of sense with regards to my income or available time. I was a biology major in college. I went to medical school and did a residency in family medicine. I never had any formal training in either business or technology. I learned the ropes by doing. It was often trial by fire. I’ve had my share of success as well as a few failures along the way. When I advanced into the role of a hospital CIO and CMIO, it wasn’t because I knew tech. When my then CEO asked me to step into the CIO role, I’ll never forget what he said to me. He said, “I want to put a civilian in charge of the military”, meaning a doctor in charge of a department that existed to serve clinicians and their patients but had become a renegade army running out of control and way over budget.

Continue reading “Should We Send Docs to Tech School?”

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Apple store NYC

MU stage 2 is making everyone miserable.  Patients are decrying lack of access to their records and providers are upset over late updates and poor system usability. Meanwhile, vendors are dealing with testy clients and the MU certification death march.  While this may seem like an odd time to be optimistic about the future of HIT, nevertheless, I am.

The EHR incentive programs have succeeded in driving HIT adoption. In doing so, they have raised expectations of what electronic health record systems should do while bringing to the forefront problems that went largely unnoticed when only early adopters used systems.  We now live in a time when EHR systems are expected to share information, patients expect access to their information, and providers expect that electronic systems, like their smartphones, should make life easier.

Moving from today’s EHR landscape to fully-interoperable clinical care systems that intimately support clinical work requires solving hard problems in workflow support, interface design, informatics standards, and clinical software architecture.  Innovation is ultimately about solving old problems in new ways, and the issues highlighted by the current level of EHR adoption have primed the pump for real innovation.   As the saying goes, “Necessity is the mother of invention,” and in the case of HIT, necessity has a few helpers.

Continue reading “Why I Am Still Optimistic About the Future of HIT”

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Is healthcare going to the dogs?  In at least one way, it probably should.

While not often spoken of together, physicians and veterinarians share an otherwise unique position of helping people make healthcare decisions in the awkward and charged space between risk, benefit and cost.  Both share an ethical requirement to provide the information necessary for informed decision making. Before starting a treatment or procedure, patients (and pet owners) need to understand the potential risks and benefits of their care, as well as the reasonable alternatives.

But veterinarians often share some other important information, information that physicians seldom share, or even know – that being: exactly what will it cost.

When our family dog recently became very sick, my veterinarian shared not only about the diagnosis, her recommended treatment, its risks, benefits and the plausible alternatives, but she also provided a detailed estimate of what Cosmo’s care was going to cost me.

Isn’t it crazy that when it comes to our own healthcare, we don’t get the same information?

Continue reading “Informed Consent 2.0″

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flying cadeuciiThe Meaningful Use program is at a critical inflection point.  On one hand, the payers could jump on the MU bandwagon, follow Medicare’s example and demand provider MU attestation.

On the other hand, they could throw private practice a bone and help them weather the storm until MU goes away or loses its teeth. Let me explain.

Payers could take the easy money and penalize according to the upcoming ACA “adjustment” schedule.  Lots of people think this is inevitable. This would certainly provide an easy way to increase payer revenue and is as simple as letting the practices [continue] to do all the work.

However, this would be incredibly short-sighted.

Meaningful use, as things stand in 2014,  has not been shown to improve patient care. Indeed, it is common for Stage 1 attesting MDs to abandon the program during Stage 2, with many doctors citing lack of efficacy of the program. Stage 3 MU is projected to have even worse results.

What this tells me is that the stress and time-cost of MDs and their staff is not worth the benefits of Meaningful Use.  Don’t get me wrong – there are some great things in the MU guidelines, and we are implementing them in the software we create, but they are overshadowed by the onerous, less-effective 5% and it’s all or nothing. There is no MU wiggle-room.  These days you have to have real grit and determination to stay in private practice, no matter your specialty.

Without financial support or legislative reform, Meaningful Use will eventually drive independent doctors out of business.

That’s bad news for payers.

Continue reading “The Case For Payers to Oppose Meaningful Use”

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Screen Shot 2014-08-11 at 9.43.45 AMHealthcare is very different from most other industries. It is fragmented, conservative, highly regulated, and hierarchical. It doesn’t follow most of the usual business rules around supply and demand or consumerism. An important aspect of my role at Microsoft is helping my colleagues at the company understand the many ways that healthcare is different from other “businesses”.

Having said that, there are a lot of things that healthcare could learn from a company like Microsoft or other technology companies. When someone asks me what it’s like to work at Microsoft, I often say what someone told me when I started at the company 13 years ago. Microsoft is like a global colony of ants, working independently and yet together but always “neurally” connected by enabling technologies. At any given moment, I can be connected to any one of my 100,000 fellow workers or tens of thousands of partners with just a couple of clicks or taps on a screen. I have tools that show me who’s available, what they do, what they know, and where they are. I can engage in synchronous or asynchronous communication and collaboration activities with a single member or multiple members of my team using messaging, email, voice, video or multi-party web conferencing. We can use business analytics tools, exchange information, review documents, co-author presentations, and collaborate with our customers and partners anywhere in the world from anywhere we might be. Our business moves, and changes, at the speed of light. It is the rhythm of the industry.

I sometimes wake up in the morning and think, “If only my clinical colleagues could avail themselves of similar tools and technologies how different could healthcare be?” I’ve been using information communications technologies in my daily work for so long that I almost take for granted that this is the way work is done. But I also know that in the real world of healthcare the journey is still quite different. That hit home again last week when I asked my mother’s family doctor for a copy of a report on an imaging study he had ordered. It took five phone calls to make something happen and my only choice was to receive the report via fax machine. Fax machine, really?

Continue reading “What Healthcare Could Learn From a Technology Company”

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Screen Shot 2014-07-30 at 8.23.49 PMWe are residents and a software developers. Before starting residency, we spent time as software developers in the startup community. We were witness to tremendous enthusiasm directed at solving problems and engaging people in their health. The number of startups trying to disrupt healthcare using data and technology has grown dramatically and every day established healthcare companies appear eager to feed this frenzy through App and Design Competitions.

When we started residency, the restrictiveness of data and reliance on decades-old technology was grossly apparent. Culturally, hospitals are an environment of budgets and deadlines that are better suited towards maintaining the status quo than promoting the creative process. Hospital IT departments harbor a deep cover-your-rear-end mentality and are incentivized for two things: first, keep systems running, and second, prevent security breaches. Perhaps rightly so–privacy and security need to be prioritized–but this environment has delayed them from facing the inevitable challenges of effectively using their own data and investing in new tools, including ones that could improve the triple aim of greater quality care with greater patient satisfaction and lower cost.

In the future, as hospitals and health systems become more accountable for the long term outcome of patients, we are optimistic that they will innovate as much out of cost-cutting necessity as for providing a better product to patients. We have little evidence that established players can power innovation solely on their own engines and expect many of the solutions will come from problem-solvers outside medicine. Doctors and patients will choose from an arsenal of apps to interact with the health information in EMRs. These healthcare apps come in three major categories: education, workflow, and decision support.

Continue reading “The Non-Physician’s Guide to Hacking the Healthcare System”

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Matthew Holt
Founder & Publisher

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Alex Epstein
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Munia Mitra, MD
Chief Medical Officer

Vikram Khanna
Editor-At-Large, Wellness

Joe Flower
Contributing Editor

Michael Millenson
Contributing Editor

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