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Category: THCB

Research Bites Dog

Screen Shot 2016-04-03 at 10.42.56 AMWe live in a headline/hyperlinked world.  A couple of years back, I learned through happenstance that my most popular blog posts all had catchy titles.  I’m pretty confident that people who read this blog do more than scan the titles, but there is so much information coming at us these days, it’s often difficult to get much beyond the headline.  Another phenomenon of information overload is that we naturally apply heuristics or short cuts in our thinking to avoid dealing with a high degree of complexity.  Let’s face it: it’s work to think!

In this context, I thought it would be worth talking about two recent headlines that seem to be set backs for the inexorable forward march of connected health.  These come in the form of peer reviewed studies, so our instinct is to pay close attention.

In fact, one comes from an undisputed leader in the field, Dr. Eric Topol.  His group recently published a paper where they examined the utility of a series of medical/health tracking devices as tools for health improvement in a cohort of folks with chronic illness.  In our parlance, they put a feedback loop into these patients’ lives.  It’s hard to say for sure from the study description, but it sounds like the intervention was mostly about giving patients insights from their own data.  I don’t see much in the paper about coaching, motivation, etc.

If it is true that the interactivity/coaching/motivation component was light, that may explain the lackluster results.  We find that the feedback loops alone are relatively weak motivators.  It is also possible that, because the sample included a mix of chronic illnesses, it would be harder to see a positive effect.  One principle of clinical trial design is to try to minimize all variables between the comparison groups, except the intervention.  Having a group with varying diseases makes it harder to say for sure that any effects (or lack of effects) were due to the intervention itself.

Dr. Topol is an experienced researcher and academician.  When they designed the study, I am confident they had the right intentions in mind.  My guess is they felt like they were studying the effect of mobile health and wearable technology on health (more on that at the end of the post). But you can see that, in retrospect, the likelihood of teasing out a positive effect was relatively low.

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Telemedicine: Competition and Coopitition

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In 1985 I had the good fortune to study in Sweden. I made many good friends and loved the natural beauty. I also learned a lot about healthcare in what is essentially a socialist country.

Sweden was (and is) by no means perfect. Progressive taxation had disincentivized hard work leading to something of a brain drain. Many of the physicians I met were looking to emigrate. On the flip side, Swedish healthcare was accessible and high quality. The government viewed healthcare as a responsibility and right rather than an option. The relatively small and homogeneous population (8 million in 1985) allowed central planning. On the campus of the Karolinska Institute, their version of the NIH, there were regional specialty hospitals: a hospital for the heart, the G.I. tract, the nervous system, etc.

This contrasts with American healthcare where hospitals offer specialty services on nearly every corner. Here in Phoenix, a patient with cancer can choose from Banner / MD Anderson, Mayo Clinic, Dignity Health / UA Cancer Center, and Cancer Treatment Centers of America, along with several other institutes. How did such choice come about? As a nation, we hold certain truths to be self-evident. Near the top of the list, we believe competition is a good thing. In just about every business open markets lead to higher quality goods and services and ever decreasing prices. Right? So how come on almost every measure Swedish healthcare trumps the American system? Sweden spends half as much per capita

[JL1]  but on average its citizens live four years longer

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Unicornius Gorus: There’s More to the Theranos and Zenefits Story

flying cadeuciiA Correction to Unicornius Gorus – Theranos and Zenefits

I have a confession to make, my previous piece entitled Unicornius Gorus –Theranos and Zenefits, which identified these two companies as a new species in the Unicornius genus was not correct.

The problems at Theranos, as reported by John Carreyrou at the Wall Street Journal, just keep getting worse. While its now very clear Theranos has a serious problem with their Edison technology and its ability to produce accurate results, what is perhaps even more glaring is their complete disregard for operating a lab within standards.

Along with the measurement errors, the report by the Center for Medicare and Medicaid Services found Theranos:

  • used unqualified staff,
  • allowed unlicensed workers to review patient test results
  • did not properly operate equipment as per manufacturer recommendations,
  • lacked proper documentation and signatures and
  • failed to meet quality control standards.

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Repealed or Repaired?

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Last Wednesday marked the sixth anniversary of the passage of the Patient Protection and Affordable Care Act. As of this week, the five Presidential aspirants have each articulated key changes they’d propose, though polls show interest in the law is largely among Democrats who consider healthcare a major issue along with national security and the economy.

GOP candidates Trump, Cruz and Kasich say they will repeal the law; Democratic frontrunner Clinton says she will repair it, and her challenger, Bernie Sanders, promises to replace it with universal coverage. Some speculate that candidate Clinton’s plan will ultimately mirror her Health Security Act of 1993 that parallels the Affordable Care Act in many respects. But the law gets scant attention on the campaign trails other than their intent about its destiny if elected.

I have read the ACA at least 30 times, each time musing over its complexity, intended results, unintended consequences and hanging chads. At the risk of over-simplification, the law purposed to achieve two aims: to increase access to insurance for those unable to qualify or afford coverage, and to bend the cost curve downward from its 30 year climb. It passed both houses of Congress in the midst of our nation’s second deepest downturn since the Great Depression. Unemployment was above 10%, the GDP was flat, and companies were cutting costs and offshoring to adapt.

The “Patient Protection and Affordable Care Act” soon after became known as the “Affordable Care Act”, and then, in the 2010 Congressional Campaign season that followed its passage, “Obamacare”. It was then and now a divisive law: Kaiser tracking polls show the nation has been evenly divided for and against: those opposed see it as “the government takeover of healthcare” that will dismantle an arguably expensive system that works for most, while those supportive see it as a necessary to securing insurance coverage for those lacking.

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The Case for Case-Based Reasoning

flying cadeuciiCase-based reasoning has been formalized for purposes of computer reasoning as a four-step process[1]:

  • Retrieve: Given a target problem, retrieve cases from memory that are relevant to solving it. A case consists of a problem, its solution, and, typically, annotations about how the solution was derived.
  • Reuse: Map the solution from the previous case to the target problem. This may involve adapting the solution as needed to fit the new situation.
  • Revise: Having mapped the previous solution to the target situation, test the new solution in the real world (or a simulation) and, if necessary, revise.
  • Retain: After the solution has been successfully adapted to the target problem, store the resulting experience as a new case in memory.

The complexities associated with programming and implementation of a knowledge management system based on case histories is both non-obvious and difficult, but ironically this is the actual process that an expert physician uses in his day to day clinical work.

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Torture the Data Until it Confesses

flying cadeuciiDid you ever hear the old joke where the boss says floggings will continue until morale improves? Torturing the data until results improve…or the data confesses…is not uncommon. Which is a pity.

In my career I’ve worked with companies with over 100k covered lives the claim costs of which could swing widely, from year to year, all because of a few extra transplants, big neonatal ICU cases, ventricular assist cases, etc.

Here are just a few of the huge single case claims I’ve observed in recent years:

  • $3.5M    cancer case
  • $6M       neonatal intensive care
  • $8M       hemophilia case
  • $1.4M    organ transplant
  • $1M       ventricular assist device

This is not a complaint. After all this is what health insurance should be about, huge unbudgetable health events.

All plans have one organ transplant every 10k life years or so, most of which will cost about $1M over 6 years. A plan with 1k covered lives will have such an expense on the average of every 10 years. Of course the company may have none for 15 years and two in the 16th year. The same goes for $500k+ ventricular assist device surgeries.

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The Healthcare Data Sharing Conundrum

flying cadeuciiPeople are more likely to avoid loss than to seek gains. HIPAA creates a framework where it rewards risk adverse behavior for data sharing even when data sharing would ultimately be beneficial to the enterprise, the mission, and the patients. This is a general issue at the heart of making progress in healthcare regarding data sharing and interoperability. I have some new thoughts on how to bridge this divide.

Recently I read the book ‘Thinking, Fast and Slow’ by the Nobel Prize winning economist Daniel Kahneman. This book discusses the concept of Prospect Theory. In reading through it I could see a hint of why our industry has so much trouble trying to share medical records and in general has trouble sharing almost anything among trading partners and competitors. If you haven’t read about Prospect Theory, the following tests provide some of the basics into how humans make decisions about risk.

Decision 1: Which do you choose? Get $900 for sure OR 90% chance to get $1,000

Decision 2: Which do you choose? Lose $900 for sure OR 90% chance to lose $1,000″[i]

The common answer to #1 is to take the $900. The common answer to #2 is to take the 90% chance to avoid the loss. As a result, we take risks to avoid danger but avoid risks when we see certain rewards. This behavior is relevant to data sharing and access to PHI and can be instructive on how people will approach risk.

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Patient-Centered Service

flying cadeuciiAmerican healthcare has a customer service problem.  No, customer service in the US is terrible when it comes to healthcare.  No, the customer service in the US healthcare system is horrendous.  No, healthcare has the worst customer service of any industry in the US.

There.  That seems about right.

What makes me utter such a bold statement?  Experience.  I regularly hear the following from people when they come to my practice:

  • “You are the first doctor who has listened to me.”
  • “This office makes me feel comfortable.”
  • “I didn’t have to wait!”
  • “Where’s all the paperwork?”
  • “Your office staff is so helpful. They really care about my needs.”
  • “This is the first time I’ve been happy to come to the doctor.”
  • “It’s amazing to have a doctor who cares about how much things cost.”
  • “You explain things to me.”
  • “You actually return my calls.”

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HillaryCare 2.0 – Back to the Future

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It was 1993, nearly a generation ago.  President Bill Clinton had delegated massively to the First Lady the task of putting meat on the bones of his ambitious healthcare announcement.  Ms. Clinton, in turn, undertook the task of drafting and then selling to Congress what was titled the “Health Security Act of 1993,” but what is remembered as “Hillarycare.”

No one doubts Ms. Clinton’s intelligence and determination.  That she was so completely derailed and the way it happened is nothing short of remarkable.  In many ways, we were then so ready for reform.  Many things were aligned, including a newly robust economy that lasted for over 7 years.

There are many reasons why Hillarycare failed back then, not the least of which were the AHIP sponsored television ads,  Harry and Louise, who became famous for their very effective skewering of what was loosely represented to be the effects of the Act.  The entire debacle became a cautionary tale about how healthcare IS different and is extremely resistant to change.

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The Transparency Trap

flying cadeuciiOn a recent shift in the Emergency Department, a resident boasted to me that she had convinced a patient to have an MRI done after discharge, rather than in the hospital. She was proud of this achievement because MRIs cost much more in the hospital than they do elsewhere – sometimes thousands of dollars more. To advocates of “cost-conscious care,” a new movement in medical education that aims to instill in young doctors a sense of responsibility for the financial consequences of their decisions, this story seems to belong in the ‘win’ column.

But this story also raises troubling questions: Why wasn’t the resident more concerned about how the hospital’s charging practices were leading her to delay care for her patient? What about the prolonged anxiety the patient would suffer? What about the extra day of work she would have to miss? And most importantly, why does an MRI cost thousands of dollars more in the hospital than it does across the street?

Like many doctors, she had fallen into the ‘transparency trap.’ This phenomenon is an unintended consequence of price transparency efforts that have come in response to patients and doctors being kept in the dark for decades about the prices of common services. Unfortunately, as the CEO of one large hospital put it, “the vast majority of [prices] have no relation to anything, and certainly not to cost.” In fact, studies have shown that in a functional market, MRIs would cost somewhere around $250, and we wouldn’t be nearly as concerned about doing too many of them.

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