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Tuesday, January 1, 2013

A 2013 Happy New Year to the HIT sector

May you all thrive and continue your good works.


Congress is "working" today. It is now reported that the Senate as passed H.R. 8 and sent it back over to the House. Among other things, this double-spaced 157 page draft proposes to 
  • make permanent the bulk of the Bush tax cuts; 
  • extended the ag price support program for another year (the "Dairy Cliff" thing);
  • again kick the Medicare SGR can down the road for another year;
  • extend unemployment benefits for another year;
  • kick the "automatic sequester" problem down the sidewalk for two months (which assures us of a "deficit ceiling" circus in late February);
  • and, it says nothing about recission of Meaningful Use incentive funds (an issue sure to be raised again in less than two months per the "sequester" wrangle.
 I will be following developments. I guess, for now, I'll still have a job in the morning.

WASHINGTON [Wall St. Journal] —House Democrats on Tuesday pressed for a vote on a bipartisan plan to avert year-end tax increases and spending cuts known as the fiscal cliff, as conservatives in the Republican-controlled House resisted the proposal.

The deal met opposition from House Majority Leader Eric Cantor (R., Va.) and many House Republicans because it didn't do more to reduce federal spending—returning to a central disagreement between the parties for the past two years.

Republicans said they may try to change a deal that cleared the Senate in an 89-8 vote in the early hours of the new year. The Senate agreement would boost income-tax rates for the first time in 20 years, maintain unemployment benefits and delay spending cuts that were part of the fiscal cliff...
Maybe I'll still have a job in the morning.



Patient compliance is important.

From Forbes, by way of THCB: HIT, THE ROAD AHEAD

Turning Information Into Impact: Digital Health's Long Road Ahead

A leading scientist once claimed that, with the relevant data and a large enough computer, he could “compute the organism” – meaning completely describe its anatomy, physiology, and behavior. Another legendary researcher asserted that, following capture of the relevant data, “we will know what it is to be human.” The breathless excitement of Sydney Brenner and Walter Gilbert —voiced more than a decade ago and captured by the skeptical Harvard geneticist Richard Lewontin [1]– was sparked by the sequencing of the human genome. Its echoes can be heard in the bold promises made for digital health today.

The human genome project, while an extraordinary technological accomplishment, has not translated easily into improved medicine nor unleashed a torrent of new cures. Perhaps the most successful “genomics” company, Millennium Pharmaceuticals, achieved lasting success not by virtue of the molecular cures they organically discovered, but by the more traditional pipeline they shrewdly acquired (notably via the purchase of LeukoSite, which ultimately yielded Campath and Velcade).

The enduring lesson of the genomics frenzy was succinctly captured by Brown and Goldstein, when they observed, “a gene sequence is not a drug.”

Flash forward to today: technologists, investors, providers, and policy makers all exalt the potential of digital health [2]. Like genomics, the big idea – or leap of faith — is that through the more complete collection and analysis of data, we’ll be able to essentially “compute” healthcare – to the point, some envision, where computers will become the care providers, and doctors will at best be customer service personnel, like the attendants at PepBoys, interfacing with libraries of software driven algorithms.

A measure of humility is in order. Just as a gene sequence is not a drug, information is not a cure. Getting there will take patience, persistence, money and aligned interests. The most successful innovators in digital health will see the promise of the technology, but also accept, embrace, and ideally leverage the ambiguity of disease, the variability of patients, and the complexities of clinical care.

We’ll also need to incorporate four key lessons of the genetics experience: 

  • Don’t confuse data with insight: it can be difficult to extract robust, clinically-relevant conclusions from reams of data; 
  • Don’t confuse insight with value: many solid scientific findings, while interesting, do little to inform existing practice or significantly improve today’s outcomes; 
  • Don’t overestimate your ability to forecast from data: even the best data often afford only limited insight into health outcomes; a lot may depend upon chance or other factors; 
  • Don’t underestimate the implementation challenges: leveraging data successfully requires a care delivery system prepared to embrace new methodologies, requiring significant investment of time and capital, and the alignment of economic interests. 
Digital health will ultimately revolutionize medicine, but it will get there through a series of evolutionary phases. These won’t be tidily sequential – some disease areas and some delivery systems may offer more fertile ground initially and see early successes.

But for the healthcare experienced by the vast majority of providers and patients and influencing a meaningful share of the dollars spent, the process will take much longer. Ten to fifteen year adoption cycles are typical (even rapid) in healthcare, and digital health is well advanced in only one domain (digital capture of data in today’s workflows through electronic medical records [EMRs] and digital diagnostics) of the many required for far-reaching impact...
Excellent article. Read the entire piece.
Concluding Thoughts

While we believe deeply in the promise of digital health, our optimism is tempered: human health is complex, our understanding is incomplete, and change – for both individuals and systems – is very, very hard.   While media reports often focus on exceptional examples of early adopters, we would be foolish to use these to calibrate our expectations (a specific example of a more general publication bias).

We are likely to discover that even if we could acquire all the data we could imagine, there are fundamental limits on what this might reveal.  It’s unlikely we’ll ever be able to “compute the whole organism.”

Even so – and with humbled mien — we should push digital health technologies hard, and leverage the resulting data as best we can to improve the human condition.


The House passed H.R. 8: 11:01:15 P.M., H.R. 8: On motion that the House agree to the Senate amendments Agreed to by recorded vote: 257 - 167 (Roll no. 659).

The SGR "Doc Fix"

Kick this one again down the road for another year.

No HIPAA Omnibus Final Rule yet, btw. Like, c'mon.

Well, H.R. 8 didn't cut any Meaningful Use money, so it's back off to work. MU incentive funds will likely again be in the crosshairs during the upcoming "Debt Ceiling" wrangle in mid- late February.



Dr. Oz Doubles Down on Green Coffee Bean with a Made-for-TV Clinical TrialPublished by Scott Gavura under Clinical Trials,Herbs & Supplements,Medical Ethics
“One of the most important discoveries I believe we’ve made that will help you burn fat – green coffee been extract” – Dr. Oz, September 10, 2012, Episode “The Fat Burner that Works”

Dr. Mehmet Oz may be biggest purveyor of health pseudoscience on television today. How he came to earn this title is a bit baffling, if you look at his history. Oz is a bona fide heart surgeon,  (still operating 100 times per year), an academic, and a research scientist, with 300+ or 400+ (depending on the source) publications to his name. It’s an impressive CV, even before the television fame. He gained widespread recognition as the resident “health expert” on Oprah, and went on to launch his own show in 2009. Today “The Dr. Oz Show” is a worldwide hit, with distribution in 118 countries, a massive pulpit from which he offers daily health advice to over 3 million viewers in the USA alone. For proof of his power to motivate, just look at the “Transformation Nation Million Dollar You” program he launched in 2011, enrolling an amazing 1.25 million participants. Regrettably, what Oz chooses to do with this platform is often disappointing.  While he can offer some sensible, pragmatic health advice, his show’s content seems more focused on TV ratings than medical accuracy, and it’s a regular venue for questionable health advice (his own, or provided by guests) and poorly substantiated “quick fixes” for health issues. (And I won’t even touch Oz’s guests like psychic mediums.) One need only look at the number of times the term “miracle” is used on the show as a marker of the undeserved hyperbole. Just this week, Julia Belluz and Stephen J Hoffman, writing in Slate, itemized some of the dubious advice that Oz has offered on his show, with a reality check against what the scientific evidence says. It’s not pretty...
My SBM comment:
#BobbyG on 03 Jan 2013 at 7:17 am PST
“Also this will never reach the eyes and ears of Oz viewers sadly”

I wouldn’t give up that easily. I just tweeted him, with relevant hashtags. He has almost 2.5 million Twitter followers. This will get SOMEONE’S attention. I exhort everyone to do likewise.

@DrOz SBM takes issue with you here. #OzTip #TheDrOzShow #OzResolution #OzQuestion I will cite this on my REC blog.

I also posted it on his Facebook page:
It’s not about attacking HIM, it’s about defending the scientific method.


Heath IT is supposed to help "bend the cost curve" downward, recall? I graphed these data from a CMS NHE projection (pdf). $39 trillion across a decade? (Yeah, it's aggregate estimated cost by year, not per capita, and thus is not adjusted for population growth. I'm sure it takes into account a greying population, though).

Below, an interesting graphic I found on Forbes.

Look at the U.S. "hockey stick" curve (red). Notice that in the 50-60 year old segment is wear the wear and tear of aging starts to show up (and is reflected in UTIL). What jumps out at me is the consequence of the way we in the U.S. frame health care "coverage" -- in mostly annual enrollment, the upshot being that in any one year, 5% of patient consume 50% of health care, half the population spends nil, and the remaining 45% is somewhere in between, heading inexorably toward the high UTIL 5%. If half of the population is getting off cheaply at any one time, coming to political consensus on a more cost-effective payment paradigm is made significantly more difficult.

While UTIL is to a degree an inevitable result of aging, framing "coverage" as that of spanning a lifetime dramatically mitigates the uptick. This is not theory; these are data.

But, hey, that sort of reform would be "Socialist."

Below: it's lonely out there on the right. Ruinously so.

These data were posted on Forbes, no less, not on

More to come... 

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