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.)
Related Posts
The Future of Healthcare is Accelerating
Why the Healthcare Industry Must Be Prepared to Unlearn
