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Tag: Nassim Taleb

How to Practice Medicine in a World We Can Never Truly Understand

Central to the problem of how best to live in a world that we cannot understand is how to regard:

“The Extended Disorder Family (or Cluster): (i) uncertainty, (ii) variability, (iii) imperfect, incomplete knowledge, (iv) chance, (v) chaos, (vi) volatility, (vii) disorder, (viii) entropy, (ix) time, (x) the unknown, (xi) randomness, (xii) turmoil, (xiii) stressor, (xiv) error, (xv) dispersion of outcomes, (xvi) unknowledge.” (Nassim Nicholas Taleb, Antifragile, London: Allen Lane, 2012)

To this impressive list, I would add seventeenth and eighteenth items:  failure and death. All of these characteristics scare and frighten most of us, and so we do our best to avoid them.

Despite the popularity of self-help books emphasizing the pursuit of happiness, a vocal minority has advocated embracing all of the above negative items in order to live fully and successfully.

Eric G. Wilson perhaps provides the best overview of this minority report when he observes that

“To desire only happiness in a world undoubtedly tragic is to become inauthentic, to settle for unrealistic abstractions that ignore concrete situations.”

And

“Our passion for felicity hints at an ominous hatred for all that grows and thrives and then dies.” (Eric G. Wilson, Against Happiness, New York:  Sarah Crichton Books, 2008)

To be alive and to realize that you are going to die means being insecure and vulnerable.  According to Martha Nussbaum one should embrace this uncertainty.

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The Antifragile CDC

flying cadeuciiSome years ago I was in Australia’s Northern Territory. The intrepid explorer that I was, I was croc-spotting from the comfortable heights of a bridge over the East Alligator River. The river derives its name because it is east of something. And because it’s croc-infested.

I was reading a story about a German tourist (it’s usually a German) who was attacked by a saltwater crocodile in the vicinity (1). The story concluded to reassure that one is more likely to be killed by a vending machine than a saltwater crocodile.

I imagined what the apotheosis of a left brain thinker, the data-driven Renaissance man, might have done with that statistic. Might he have peeked in to the East Alligator River looking for a vending machine and seeing none, jumped right in?

This empirical fact is useful if you suffer from croc-phobia and live in the Upper East Side of Manhattan, and the biggest voyage you ever plan to undertake is to the Hamptons. But it’s not terribly useful, and marginally harmful, if you’re deciding whether to kayak rivers in Northern Australia.

The vending machine has reared its deadly head again. It seems that more Americans have been killed by vending machines than have died from Ebola. Well let’s head to Liberia for the winter, because there are fewer vending machines there.

Sorry, I jest. But this is not a joke. Some actually think this is a relevant statistic to put Ebola in perspective. And some are actually reassured by it!

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The Chart-Eating Virus, Me Too Software and Other Emerging Digital Threats

The ability to gather, analyze, and distribute information broadly is one of the great strengths of digital health, perhaps the most significant short-term opportunity to positively impact medical practice. Yet, the exact same technology also carries a set of intimately-associated liabilities, dangers we must recognize and respect if we are to do more good than harm.

Consider these three examples:

  • Last week, a study from Case Western reported that at least 20% of the information in most physician progress notes was copy-and-pasted from previous notes. As recently discussed at kevinmd.com and elsewhere, this process can adversely affect patient care in a number of ways, and there’s actually an emerging literature devoted to the study of “copy-paste” errors in EMRs. The ease with which information can be transferred can lead to the rapid propagation of erroneous information – a phenomenon we used to call a “chart virus.” In essence, this is simply another example of consecrating information without first appropriately analyzing it (e.g. by asking the patient, when this is possible).
  • At a recent health conference, a speaker noted that a key flaw with most electronic medical record (EMR) platforms is that they are “automating broken processes.” Rather than use the arrival of new technology to think carefully, and from the ground up, about the problems that need to be solved, most EMRs simply digitally reify what already exists. Not only does this perpetuate (and usual exacerbate) notoriously byzantine operational practices and leave many users explicitly complaining they are worse off than before, but it also misses the chance to offer conceptually original approaches that profoundly improve workflow and enhance user experience.

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Through a Scanner Darkly: Three Health Care Trends for 2013

As we anticipate a new year characterized by unprecedented interest in healthcare innovation, pay particular attention to the following three emerging tensions in the space.

Tension 1: Preventive Health vs Excessive Medicalization

A core tenet of medicine is that it’s better to prevent a disease (or at least catch it early) than to treat it after it has firmly taken hold.   This is the rationale for both our interest in screening exams (such as mammography) as well as the focus on risk factor reduction (e.g. treating high blood pressure and high cholesterol to prevent heart attacks).

The problem, however, is that intervention itself carries a risk, which is sometimes well-characterized (e.g. in the case of a low-dose aspirin for some patients with a history of heart disease) but more often incompletely understood.

As both Eric Topol and Nassim Taleb have argued, there’s a powerful tendency to underestimate the risk associated with interventions.  Topol, for example, has highlighted the potential risk of using statins to treat patients who have never had heart disease (i.e. primary prevention), a danger he worries may exceed the “relatively small benefit that can be derived.”  (Other cardiologists disagree – see this piece by colleague Matt Herper).

In his new book Antifragile, Taleb focuses extensively on iatrogenics, arguing “we should not take risks with near-healthy people” though he adds “we should take a lot, a lot more, with those deemed in danger.”

Both Topol and Taleb are right that we tend to underestimate iatrogenicity in general, and often fail to factor in the small but real possibility of potential harm.

At the same time, I also worry about external experts deciding categorically what sort of risk is or isn’t “worth it” for an individual patient – a particular problem in oncology, where it now seems  fashionable to declare the possibility of a few more months of life a marginal or insignificant benefit.

Even less dramatically, a treatment benefit that some might view as trivial (for hemorrhoids, say) might be life-altering for others.  For these sufferers, a theoretical risk that some (like Taleb) find prohibitive might be worth the likelihood of symptom relief.  Ideally, this decision would ultimately belong to patients, not experts asserting to act on patients’ behalf.

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Why Getting to a Digital Health Care System Is Going to Be Harder Than We Thought Ten Years Ago

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.
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