Unlearning 101

Doctor Heal Thyself ... By Unlearning

When physicians are asked to state the relative risks of classical predictors of heart disease (such as smoking or diabetes) many, according to this article, are likely to cite a figure of between "10 to 15 times."

This is not only wrong, it is dangerously wide of the mark. Most of the predictors have only relative risks of around 1.8 to 2-fold.

Too many people it might seem that the danger of over-assessing the relative risk of, say, smoking to heart disease is a good thing -- or, at least, it doesn't do any harm. This may be true but I'd argue it can have a dangerous side-effect by causing physicians to under-assess other risks.

For example, due to the accelerating rate of genomic information (which I have written about before), physicians have a better ability to use genetic information to more effectively treat disease. In many cases, in fact, this genetic information is just as predictive of health as the more classical predictors.

Unfortunately, most doctors aren't aware of this reality. They, therefore, mistakenly continue to believe other risk factors are more important.

To understand the magnitude of the problem consider this statement from Felix Frueh, president and head of genomics initiatives at Medco: "Less than 1 percent of all opportunities are being realized with respect to genetic testing."

Put another way, 99% of all patients are receiving less-than-optimal care due to physicians under-estimating the predictive power of genetic information!*

I am convinced that before new learning can take place, often, unlearning must first take place. In this case, physicians need to unlearn their misunderstanding of the relative risks of classical predictors (e.g. smoking, diabetes, etc.) before they can learn the new powers of genetic testing.

(*At the present time, there are more than 1,200 genetic tests for more than 1,000 different diseases and yet only 13% of 10,000 doctors surveyed had ordered a genetic test for a patient in the preceding 6 months.)

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Start Treating Employees Like Customers

Here is a novel idea many employers might want to begin implementing: start treating your employees like customers. Why? Because it can save money.

I recently came across this article explaining how Genentech has begun developing apps to help make its sales force more productive. One problem area identified by the company was that sales personnel were often taking more than a week to record their sales call visits to doctors.

As someone who despises paperwork, I can relate to why it might take a salesperson so long to record this information. By making an intuitive, easy-to-use app, however, Genentech alleviated a major hassle for its sales force and, in the process, was able to increase its profits.

The bottomline doesn't always have to only be about the company's bottomline. If more companies would start treating their employees as customers and providing them better tools to do their job they are likely to find that their increased profits more than exceed the cost of developing and implementing many of these new tools.

Am I -- and Your CFO -- to Blame for Spiraling Health Care Costs?

Earlier today I had the opportunity to deliver the closing keynote presentation at the Alabama Hospitals Associations' Annual Leadership Conference. Before my talk, I had the great pleasure of listening to Bill Ward, the director of the Master Health Administration Degree at the Johns Hopkins University's Bloomberg School of Public Health.

At one point, Bill brought up a slide and asked the audience which drug a hospital should buy: Drug A, at a cost $1.80 per dose; or Drug B, at a cost of $11.50 per dose.

At this point, I thought to myself, "Yes! This is exactly the problem with healthcare. Many people continue to prescribe brand name drugs when a cheaper but equally effective generic version is available."

While this is undoubtedly a real issue and many generic drugs should be prescribed, this was not the point Bill was trying to make. As a result of his next slide, I found myself unlearning.

The initial cost of the drug is only one of the variables which must be considered. Review the following:

Drug A Drug B

Drug cost/dose $1.80 $11.50

Administration cost/dose $15.oo $1.00

Nurse intervention/dose $3.00 $3.00

Total cost per dose $19.80 $15.50

Drug A is actually more expensive. The point, of course, is that all of us need to view healthcare costs from a broader perspective -- myself included. (Ed. Obviously, the effectiveness of the drug and the length it must be administered must also be considered.)

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Unlearning Knee, Back and Spinal Surgery

"It is difficult to get a man to understand something when his salary depends on not understanding it." Upton Sinclair

I really enjoy the above quote because there is so much truth to it. I was especially reminded of the quote after reading this article about the efficacy of spinal surgery in today's Wall Street Journal. 

According to the article (and based upon research published in the New England Journal of Medicine) a popular surgery designed to repair fractured bones in the spine was found to deliver no detectable benefit when compared with a placebo procedure.

This is not an inconsequential finding because an estimated 100,000 people had the surgery last year at an estimated cost of between $2,000-$5,000.

Not surprisingly, members of the Society of Interventional Radiology (whose members perform the surgery), have taken issue with the study. According to one doctor who performs the technique the study must be wrong because "We take a patient who's been lying in bed in a hospital, bedridden, you do the procedure and they're home the next day."

The response mirrors almost identically the response to a 1994 study in the New Journal of Medicine chronicling the ineffectiveness of MRI's for spinal injury (documented in the book, How We Decide, Pp. 160-165) as well as a 2002 study in the New England Journal of Medicine documenting the ineffectiveness of arthroscopic surgery. (This case is highlighted in the book, Predictably Irrational.)

In both cases, doctors who had performing surgeries simply could not believe the procedures they had been conducting for years -- often at great expense -- were no more effective than placebo procedures. In response, they either attacked the methodology of the study or highlighted cases of individual patients who benefited from the surgery.

It is not that the doctors are unintelligent, uncaring or greedy; rather when confronted with information that contradicts what they think they know it is easier to avoid the truth -- by either questioning the study or offering antidotes -- than it is to unlearn. (This is especially so when their salaries are highly dependent upon said procedure.)

But my advice is this: If the doctors won't unlearn then it is incumbent upon you to unlearn. Next time you need an MRI (for a spinal injury); arthroscopic surgery for your knee; or have a fractured bone in your spine, get a second and, if necessary, a third opinion before proceeding!

Unlearn the Future, Today

Effective today, June 8, 2009, General Motors and Citigroup are no longer components of the Dow 30. In and of itself this news has no great relevance, but it does highlight how fast today’s economy continues to change. As I mentioned the other day on my other blog (www.jumpthecurve.net), many people think that "tomorrow will be pretty much like yesterday.” This simply isn’t true.

One strategy I have advocated for unlearning the future is to "develop a future bias.” As a thought exercise and to help you unlearn, I’d like to suggest a second exercise: review the members of the current Dow 30 and imagine which company will be the next to be removed from the list and explain why it might go. (For extra credit, I invite you to imagine which company might replace it.) The purpose of this exercise is to force you what of your comfort zone and come face-to-face with the reality that “the only constant is change” and unlearning is a critical skill for the future. (Also see "The Future Requires Unlearning.)

To help you get started, here are some possibilities. Advances in nanotechnology could cause many of the materials Alcoa makes to become either irrelevant or obsolete, and the company will be replaced by a nanomaterial company. Or perhaps Caterpillar will not remain competitive due to advances in robotics and it will be replaced by iRobot. A third alternative is that intense competition from Nokia will wreak havoc on both AT&T and Verizon and they will be replaced on the Dow 30 by Google, which may continue to make strides in the communication field with its new Android platform. A fourth possibility is that new advances in biotechnology will render many existing drugs obsolete and Pfizer will be replaced on the Dow 30 with a biotech company such as Genentech.

Really, there is no shortage of possibilities but one of the best ways to prepare for the future is to simply acknowledge that it is going to change. And, as Darwin said: “It is not the strongest of a species that survives, nor is it the fittest; it is those that can adapt the fastest.” Are you and your organization prepared to adapt -- and unlearn? Quickly?

If not, you could go the way of General Motors.

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Unlearning Disease

With all of the information now pulsing around us, it is easy to forget that "we don't know what we don't know." I constantly try to remind my clients in the health care sector of this simple fact. A case-in-point is the extraordinary strides being made in the field of genomics -- which, due to accelerating gene sequencing technologies, are occurring on a daily basis.

One the bigger implications of these cascading discoveries is that they will likely fundamentally alter how we classify disease in the future. As a little historical reference, it is useful to consider that in 1850 there were only 140 categories of disease. In 1993, the last time the World Health Organization undertook the classification of all diseases, there were some 12,000. The next classification isn't expected to occur until 2015, but it is not hard to imagine that the number of diseases -- and how they will be classified -- will increase even more.

For a great primer on this possibility, I'd encourage you to read this article, Redefining Disease, Genes and All. I especially liked this quote at the end of the article. One doctor, responding to the fact that as late as 1909 one of the leading causes of death was listed as "visitation of God," he went on to offer this warning: "Imagine how they are going to to be laughing at us," he said, "not 100 years from now, but even 50 or 20 years now."

As a result of accelerating technological change, it is certain that "we don't know what we don't know" about a wide variety of diseases. To stay open to the possibility that these diseases might soon be both classified and treated differently , it is helpful to keep in mind the possibility that if you don't change your views you will likely be widely mocked at some point in the future -- and it might even be sooner than you expect.

Pharmaceutical Industry Needs to Unlearn

In 2003, I wrote the book, ”The Next Big Thing is Really Small: How Nanotechnology Will Change the Future of Your Business.” In it, I outlined the many ways in which nanotechnology will impact the pharmaceutical industry in the near future. Recently, researchers at Children’s Hospital in Boston have uncovered a method of reviving a once-promising cancer drug, TNP-470—which was cancelled in the mid-1990’s due to concerns over toxicity.

The problem of toxicity is not a new one to the pharmaceutical industry. In fact, it is a big reason why so many early stage drugs fail to make it to market.

This vexing problem may soon be partially alleviated due to advances in nanotechnology. One advantage of reformulating drugs at the nanoscale is that they are water soluble and, as such, don’t require the solvents which so often cause nasty side-effects in patients.

Another application being employed from the nanotechnology bag of tricks is to use nanoscale platforms such as micelles and dendrimers to prevent drugs from crossing the blood-brain barrier. In this fashion, older drugs may be reformulated so as to prevent certain drugs from wreaking havoc on the human brain. (This was one of the problems with TNP-470).

The pharmaceutical industry has invested billions of dollars developing promising drugs. Unfortunately, most developmental drugs end being shelved when it is found they cause some unintended consequence. Nanotechnology holds the promise that a handful of older drugs may now be revisited. Some may even find their way to the commercial marketplace.

With a single drug’s ability to add billions of dollars to a pharmaceutical company’s bottom-line, it is time many of them begin turning their attention to nanotechnology. It’s a small technology, but it could pay big dividends. All the industry needs to do is unlearn the idea that just because something didn't work in the past, that doesn't mean that it is necessarily doomed to fail forever.

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Does the Pharmaceutical Industry Also Need to Unlearn

Unlearning Models

Chris Anderson, the editor of Wired, has written an excellent article entitled "The End of Theory: The Data Deluge Makes Scientific Method Obsolete" in which he convincingly argues that massive amounts of data, in combination with sophisticated algorithms and super powerful computers, offers mankind a whole new way of understanding the world.

Anderson believes that our technological tools have now progressed to the point where the "old way" of doing science -- hypothesize, model and test -- is becoming obsolete. In its place, a new paradigm is now emerging whereby scientists, researchers and entrepreneurs simply allow statistical algorithms to find patterns where science cannot.

If Anderson is correct -- and I believe he very well could be -- this will take unlearning to a whole new level. In short, instead of having to do the unlearning ourselves (e.g. when our hypothesis doesn't work out or is proved wrong) scientists and researchers can instead rely on intelligent algorithms to do the heavy lifting.

The implication for a field such as biology which, as Anderson points out is actually becoming more difficult to model as learn more about it (due to our limited understanding of how genetics, microbes, personal behavior, the environment and a host of other factors work in partnership to determine a person's health), could be profound.

More specifically for the field of unlearning, this means we will be able to analyze data without allowing hypotheses (which may be wrong) to cloud our view of what the data is really showing us.

Before this vision can be achieved, however, it will require a great many brilliant scientists to unlearn the idea that their "model-based" method of trying to make sense of today's increasingly complex world is the only way to search for new meaning. Increasingly, we will be able to allow computers to crunch the data and extract the meaning for us.

Unlearn or Die Even More Unneccesarily

A few weeks back I had a posting  entitled "Change or Die ... Unnecessarily” in which I provided a few examples of how our inability to unlearn could, quite literally, cost some people their lives. Well, the other day, one of my favorite thinkers, Josh Wolfe, sent me a copy his weekly newsletter, The Forbes/Wolfe Weekly Insider. In it, he unveiled some startling research from a forthcoming book: apparently, six times as many people died in their cars from the 9/11 terrorist attacks as did the number of people who died in planes.

The authors don't state their research in quite this bold of a fashion; nevertheless this is one implication of their finding. On the face of it, the idea sounds absurd -- everyone knows only a few hundred people perished in the airplanes that crashed into the Twin Towers, the Pentagon, and in the rural field in Pennsylvania.

Essentially, it is the author's contention that because millions of people refused to fly after the 9/11 attacks -- and instead chose to drive (which is demonstrably more risky in statistical terms than flying) -- an estimated 1,595 additional people have since died as a result of the 9/11 attack than is generally recognized.

If these people could have unlearned that their fear of flying was an irrational act because it caused them to engage in an even riskier activity, it is likely they would be alive today.

On a somewhat related note, I recently received a copy of a powerpoint presentation from one of the world's leading epidemiologists, Michael Osterholm. In it, he coherently argues that the United States is woefully unprepared to deal with the very real possibility of a major pandemic.

Interestingly, in his slides, Osterholm makes the point that it possible that more people will die from non-influenza-related deaths than from the flu itself.

How so, you ask? Well, much of the pharmaceutical industry utilizes "just-in-time" inventory procedures. In the event of a pandemic; major shipping, trucking and distribution centers will be hampered and maybe even shut down entirely. As a result, hospitals -- which already have a dangerously low supply of many critical life-savings drugs -- will run out of important drugs in a matter of days.

The effect: people will die unnecessarily. That is, unless, we can unlearn the idea that "just-in-time" inventory for certain critical supplies is not necessarily a good idea.

Unlearn Genetic Nihilism

WebMD has interesting article suggesting our behavior can influence how are genes act. According to research by Dean Ornish people can change how certain genes perform by making modest adjustments to their life style. Ornish found that by engaging in exercise and eating a more low-fat diet "more than 500 genes changed the way they worked." More specifically, he found that some tumor-suppression genes became more active, while other genes with negative effects -- including some cancer-promoting genes -- were turned off when people engaged in a healthier lifestyle.

I especially liked this quote from Ornish, "People say, 'Oh, it is all in my genes, what can I do?' That's what I call genetic nihilism." Undoubtedly, many people do subscribe to the idea that our genes determine our fate. If, however, Ornish's findings prove to be true, it will dispel that idea and will require people to unlearn the idea that while "genes may be our predisposition, they are not are fate."