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Is Medicine a Big Data Problem?

Human beings are big data. We aren’t just 175 pounds of meat and bone. We aren’t just piles of hydrogen and carbon and oxygen.  What makes us all different is how it’s all organized and that is information.

We can no longer treat people based on simple numbers like weight, pulse, blood pressure, and temperature. What makes us different is much more complicated than that.

We’ve known for decades that we are all slightly different genetically, but now we can increasingly see those differences. The Hippocratic oath will require doctors to take this genetic variability into account.

I’m not saying there isn’t a place for hands-on medicine, empathy, psychology and moral support. But the personalized handling of each patient is becoming much more complicated.  The more data we can gather, the more each individual is different from others.

In our genome, we have approximately 3 billion base pairs in each of our trillions of cells.  We have more than 25,000 genes in that genome, sometimes called the exome.  Each gene contains instructions on how to make a useful protein.  And then there are long stretches of our genomes that regulate those protein-manufacturing genes.

In the early days, some researchers called this “junk DNA” because they didn’t know what it did.  But this was foolish because why would evolution conserve these DNA sequences between genes if they did nothing?  Now we know they too do things that make us unique.

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For Hospitals and Health Systems: Strategies for Doing More with Less

The conversation has changed.

The old conversation: “You cost too much.”

“But we have these sunk costs, patients who can’t pay … ”

“OK, how about a little less then?”

The new conversation: “You cost too much. We will pay half, or a third, of what you are asking. Or we will take our business elsewhere. Starting now.”

“But … but … how?”

Exactly: How will you survive on a lot less money? What are the strategies that turn “impossible” to “not impossible”?

New Strategies
The old conversation arises from the classic U.S. health care model: a fully insured fee-for-service system with zero price transparency, where the true costs of any particular service are unknown even to the provider. The overwhelmingly massive congeries of disjointed pieces that we absurdly call our health care “system” rides on only the loosest general relationship between costs and reimbursements.

It’s a messy system littered with black boxes labeled “Something Happens Here,” full of little hand waves and “These are not the droids you’re looking for.”

With bundling, medical tourism, mandated transparency, consumer price shopping, and reference pricing by employers and health plans, we increasingly are being forced to name a price and compete on it. Suddenly, we must be orders of magnitude more precise about where our money comes from and where it goes: revenues and costs.

We must find ways to discover how each part of the strategy affects others. And we need some ability to forecast how outside forces (new competition, new payment strategies by employers and health plans, new customer handling technologies) will affect our strategy.

Key Strategy Questions
For decades, whenever some path to profit in health care has arisen (in vitro fertilization, urgent care, retail, wellness and the others) most hospitals have said as if by ritual, “That is not the business we are in.” As long as we got paid for waste, few health care organizations got serious about rooting it out.

And most have seemed content with business structures that put many costs and many sources of revenue beyond their control.

In the Next Health Care, the key strategy questions become:

How PCORI’s Research Will Answer the Real World Questions Patients Are Asking

As a physician, I know the challenge of helping patients determine which health care options might work best for them given their personal situation and preferences.

Too often they — and their clinicians — must make choices about preventing, diagnosing and treating diseases and health conditions without adequate information. The Patient-Centered Outcomes Research Institute (PCORI) was created to help solve this problem — to help patients and those who care for them make better-informed health decisions.

Established by Congress through the Patient Protection and Affordable Care Act as an independent research institute, PCORI is designed to answer real-world questions about what works best for patients based on their particular circumstances and concerns. We do this primarily by funding comparative clinical effectiveness research (CER), studies that compare multiple care options.

But more research by itself won’t improve clinical decision-making. Patients and those who care for them must be able to easily find relevant evidence they can trust. That’s why our mandate is not just to fund high-quality CER and evidence synthesis but to share the results in ways that are meaningful to patients, clinicians and others.

We’re also charged with improving the methods used in conducting those studies and enhancing our nation’s capacity to do such research.

We will be evaluated ultimately on whether the research we fund can change clinical practice and help reduce the variations and disparities that stand between patients and better outcomes. We’re confident that the work we’re funding brings us and the audiences we serve closer to that goal.

Recently, some questions have been raised in health policy circles about our holistic approach to PCORI’s work. That view holds that direct comparisons of health care options — especially those involving high-priced interventions — should be the dominant if not sole focus of PCORI’s research funding approach as a path to limiting the use of expensive, less-effective options.

We agree that discovering new knowledge on how therapies compare with one another is a critical mandate of PCORI and is essential to improving the quality and effectiveness of care.  However, ensuring that patients and those who care for them have timely access to and can use this knowledge, so that they can effectively apply it to improve their decisions, is also very important.

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Here’s How We Can Fix Obamacare if We Act Now and Stop Pretending the Problems Don’t Exist

To properly price the exchange health insurance business going forward the carriers have to sharply increase the rates.

A senior executive for Wellpoint, which sells plans in 14 Obamacare exchanges, is quoted in a Reuters article telling Wall Street analysts there will be big rate increases in 2015, “Looking at the rate increases on a year-over-year basis on our exchanges, and it will vary by carrier, but all of them will probably be double digits.”

If the health plans do issue double digit rate increases for 2015, Obamacare is finished.

There are a ton of things that need to be fixed in Obamacare. But, I will suggest there is one thing that could save it.

The health insurance companies have to submit their new health insurance plans and rates between May 27 and June 27 for the 2015 Obamacare open-enrollment period beginning on November 15th. Any major modifications to the current Obamacare regulations need to be issued in the next month to give the carriers time to adjust and develop new products.

If the administration goes into the next open enrollment with the same unattractive plan offerings costing a lot more than they do today, they will not be able to reboot Obamacare.

Simply, health insurance plans that cost middle-class individuals and families 10% of their after-tax income and have average Silver Plan deductibles of more than $2,500 a month are not attractive and people won’t buy them any more enthusiastically next fall than they already have. See: Obamacare: The Uninsured Are Not Signing Up Because the Dogs Don’t Like It

Doubling the fines for not buying in 2015 will only give the Democrats more political problems––and it doesn’t look to me like they are going to enforce the fines anyway.

Health insurance plan executives are now faced with a daunting decision. How do they price the 2015 Obamacare exchange plans?

Even if the administration announces they have signed-up about 6 million people by March 31, the number of people enrolling would be well below expectations––only about 25% of those subsidy eligible will have signed up by the deadline. An enrollment that small guarantees the risk pool is sicker and more expensive than it needs to be in order to be sustainable.

But dramatically increasing the rates will only assure even fewer healthy people will sign up for 2015 and some of those who signed up for 2014 will back out over the higher rates. This is what a “death spiral” looks like.

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Google Flu Trends Shows Good Data > Big Data


In their best-selling 2013 book Big Data: A Revolution That Will Transform How We Live, Work and Think, authors Viktor Mayer-Schönberger and Kenneth Cukier selected Google Flu Trends (GFT) as the lede of chapter one.

They explained how Google’s algorithm mined five years of web logs, containing hundreds of billions of searches, and created a predictive model utilizing 45 search terms that “proved to be a more useful and timely indicator [of flu] than government statistics with their natural reporting lags.”

Unfortunately, no. The first sign of trouble emerged in 2009, shortly after GFT launched, when it completely missed the swine flu pandemic. Last year, Nature reported that Flu Trends overestimated by 50% the peak Christmas season flu of 2012. Last week came the most damning evaluation yet.

In Science, a team of Harvard-affiliated researchers published their findings that GFT has over-estimated the prevalence of flu for 100 out of the last 108 weeks; it’s been wrong since August 2011.

The Science article further points out that a simplistic forecasting model—a model as basic as one that predicts the temperature by looking at recent-past temperatures—would have forecasted flu better than GFT.

In short, you wouldn’t have needed big data at all to do better than Google Flu Trends. Ouch.

In fact, GFT’s poor track record is hardly a secret to big data and GFT followers like me, and it points to a little bit of a big problem in the big data business that many of us have been discussing: Data validity is being consistently overstated.

As the Harvard researchers warn: “The core challenge is that most big data that have received popular attention are not the output of instruments designed to produce valid and reliable data amenable for scientific analysis.”

The amount of data still tends to dominate discussion of big data’s value. But more data in itself does not lead to better analysis, as amply demonstrated with Flu Trends. Large datasets don’t guarantee valid datasets. That’s a bad assumption, but one that’s used all the time to justify the use of and results from big data projects.

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Commentology: The Creative Destruction of Healthcare

THCB reader and occasional contributor Dave Chase had this to say about Bill Crounse, MD’s recent post “Why the Creative Destruction of Healthcare May Not Be a Good Idea.

“There is no doubt there are some obnoxious people throwing around arrogant/naive ideas. However, the “creative destruction” and “disruptive innovation” that has been most impactful has come from physician-entrepreneurs. Often, they are the most provocative and hard-hitting in their language.

It seems loosely similar to how the most virulent anti-smokers are former smokers. They want others who they can relate to experience the liberation they’ve experienced.

I wouldn’t assume ill-intent from these MD-entrepreneurs using direct language. They simply were fed up with what they experienced as “broken” and stepped up with approaches that have out-performed.

I’m thinking about the MD-entrepreneurs and innovators who have led CareMore, Nuka Model of Care, Qliance, Iora Health, MedLion, Healthcare Partners, etc. Sometimes to catalyze change, one must use stark, hard-hitting language.

That doesn’t seem like a foreign concept to the many excellent MDs I’ve known over the years. I have enormous respect for any entrepreneur, especially one coming from tradition-bound professions who are willing to stick their neck out and endure enormous personal financial risk.

Bob Margolis shared how his colleagues referred to him as a “communist” and his team-based model as “communism” yet Bob’s org achieved far better outcomes. He had the last laugh when that “communist” sold his business for $4.4B last year.

The comments from these MD-entrepreneurs is they feel they aren’t doing their MD friends any favors by candy-coating what is widely recognized as a system that isn’t close to reaching its full potential.

In contrast, the orgs those MD-entrepreneurs are running are the reigning “Triple Aim Champs” that we should celebrate — colorful language or not. Often the most impactful entrepreneurs aren’t particularly “polite” in their language — Steve Jobs, Bill Gates, Larry Ellison et al called it like they saw it.

What’s wrong with that?”

Will eClinicalWorks Win the Race to “Engage” the Patient?


Patient engagement, for better or worse, is one of those buzzwords that won’t be leaving us anytime soon.

A whole slew of companies use it to describe their products, platforms, and services, but we’re still knee deep in marketing jargon trying to figure out exactly what these tools do and how “effective” they really are.

We got a closer look at one such tool last month at HIMSS from a company that also finds itself knee deep in patient engagement.

eClinicalWorks debuted in 1999 as the Southwest Airlines of electronic health records (EHR). They offered a relatively low cost combined EHR/practice management system, which quickly made them significant players in the small practice market, adding more than 3,000 doctors in just three years.

It wasn’t until 2007 though that eClinicalWorks really broke through when then Assistant New York City Health Commissioner and future National Coordinator for Health Information Technology Dr. Farzad Mostashari selected them for installation with more than 1,300 New York City physicians as part of Mayor Bloomberg’s Primary Care Information Project (PCIP).

Now, eClinicalWorks counts more than 100,000 physician users in over 50,000 facilities in addition to another 14 million users on their patient engagement tool, Healow.

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Actually, It’s a Great Time to Be a Doctor

Is this a good time to be a physician? Absolutely! In fact, I believe there has never been a better time to practice medicine. I hold this belief despite the barrage of negative comments and predictions from doomsayers remarking on the sorry state of health care in its current state.

Before I tell you why I’m so optimistic, I’d like to acknowledge one fact: practicing medicine is more complex and difficult than ever, however, this fact doesn’t dampen my enthusiasm. There is no doubt that over the past two decades a great many changes in the health care environment have consumed doctors’ time, distracted us from our core task of providing care, and impacted our incomes.

Meanwhile, patients’ expectations of the health care industry and of their physicians are changing. An increasing number of people want more involvement in their own health care and want to partner with their physician. So it is not hard to understand how practicing medicine can feel more challenging than ever.

For example: results from a national survey reported in the Archives of Internal Medicine in 2012 indicated that US physicians suffer from more burnout than other American workers.

Burnout, in this report, was defined by “loss of enthusiasm for work, feelings of cynicism, and a low sense of personal accomplishment”; 45.8% of responding physicians had at least 1 of these symptoms.

So why am I so optimistic?

Because when I read these survey results, and others like them, bureaucracy and complexity are often cited as the reasons why physicians are unhappy. Not patient care.

While these factors (bureaucracy and complexity) can momentarily take physicians away from their passion of practicing medicine, it is the passion of a physician, precisely, that fuels my optimism for the state of health care today.

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Employers 2.0

The most significant force for health system transformation in the United States is employer activism.

This month’s decision to delay the Affordable Care Act’s employer mandate until 2016 coupled with dramatic increases in health insurance premium costs assures employers will play a stronger role going forward.

The facts:

57% of all companies provide health insurance covering 149 million in the population. But participation varies widely by industry and size of company.

Participation: Manufacturing (72%), Services (65%), Transportation/Utilities/Communications (62%), Agriculture/Mining/Construction (60%), Wholesale (54%), Healthcare  (51%), Financial services (49%), Retail (29%) (Kaiser/HRET Survey of Employers)

Size: Smaller companies under 199 are less likely to provide health benefits than larger companies, though premiums they pay to insurers are slightly lower than their larger counterparts.

Declines in employer sponsored coverage declines are due to costs, not the Affordable Care Act. Consider: the percentage of non-elderly workers with employer-sponsored coverage decreased from 68% in 2000 to 61% in 2009 before the law passed.

Employers pay 82% of health costs for singles and 71% of costs for those in their family health plans. Over the past decade, they have shifted more financial responsibility to their employees.

  • Premiums for employers from 2003-2013 increased 80% but employee contributions increased 89%.
  • At the same time, employers have reduced coverage for retirees and dependents, and in many industries, kept wages low to offset health cost increases.

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How a Washing Machine Inspired Me to See the Future of a Safer ICU

Berg, the company the brought along fun internet-connected concepts and products such as the Little Printer released this interesting video recently.

[vimeo=87522764 W=900&H=325]

The amazing part of this is that Cloudwash is foundational and will just be built on. It shows where the current state of the Internet of Things is and where it can go in the future. What Berg did was amazing to me.

It took a regular “dumb” appliance with software and electronics that were trapped in and made the interaction richer and its meaning and value richer.

In a way, they radically changed the way I viewed how devices could be connected and created the possibility for a new class of devices in our daily lives.

And in a way, I saw so many parallels to healthcare.

In the video, Berg mentioned how the action of washing clothes can be quite complicated. There are baroque symbols on how clothes should be treated and this in turn is reflected by different sets of complicated icons on machines

Healthcare delivery can be far more complex though.

“In any given hospital, as many as 15 medical devices, including monitors, ventilators and infusion pumps, are connected to an ICU patient, but because they are made by different companies, they don’t “talk” with one another. Patient-controlled analgesic pumps that deliver powerful narcotics, where a known side effect is respiratory depression, aren’t linked to devices that monitor breathing, for example.”Today’s ICU is arguably more dangerous than ever,” says Peter Pronovost.

Just last week, I had the privilege of shadowing the pain service team at work. The team had to go one by one to each patient while rounding throughout the hospital. At each patient, a nurse practitioner checked their PCA. These are supposed to the safest ways to deliver analgesics and are self-containing boxes that are locked except for their interface.

No one except the pain service team is supposed to even touch those boxes due to the level of training needed to even interface with them. But it relies on human systems to ensure that the correct concentration of drug is put in with the right dosage according to each patient.

Yet like Dr. Pronovost mentions, these pumps aren’t linked to devices that monitor breathing so that IF a wrong dosage is placed in the PCA, there is no way of stopping it before its too late.

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