What is the problem with grounding medical practice in the cold logic of numbers? In theory, nothing. But in practice, as decades of work in fields like behavioral economics have shown, people — patients and doctors alike — often have a hard time making sense of quantified risks. Douglas B. White, a researcher at the University of Pittsburgh, has shown that the family members of seriously ill patients, when presented with dire prognoses, typically offer quite variable understandings not only of qualitative terms such as “extremely likely” but also of quantitative terms such as “5 percent.” We like our numbers, but despite our desire for better information and an ethic of “informed consent,” we don’t know how to use them.
Far more worrisome is where the numbers come from. Until the last decade or so, estimates of risk came from a doctor’s head. Now the numbers often come from a machine, which makes them seem objective and credible. But like Dorothy confronting the Wizard of Oz, we need to look behind the curtain. It seems that anyone with a Big Data set and a statistics software package can develop an algorithm, give it a user-friendly interface, and behold: Your future is foretold. It’s fast. It’s simple. But it’s opaque, and it may be wrong.
The Omnibus Risk Estimator is one of many available cardiovascular disease risk calculators. When you enter a patient’s data into them, you get a disturbingly wide range of results. Depending on which algorithm you use, you may need a lifetime of statin therapy. Or not.
Statins by numbers: