Left Digit Bias in Medicine

From my review in the WSJ of Random Acts of Medicine by Jena and Worsham:

You have probably heard of left-digit bias—the idea that $7.99 seems cheaper than $8, even though $8 is only negligibly different than $8.01. Left-digit bias is widely observed in pricing but the effect is more general. A car with 39,990 miles on the odometer, for instance, sells for more than a car with 40,005 miles (so be smart and buy the car with 40,005 miles). Could left-digit bias show up in medicine?

People who end up in the emergency room complaining of chest pains a few weeks before their 40th birthday are very similar to people who end up in the emergency room with chest pains a few weeks after their 40th birthday. But on a chart, the former are 39 years old and the latter are 40.

The big 40 is a heuristic among physicians for potential heart attack. Looking at more than five million patient records, the economist Stephen Coussens found that patients who were slightly over the age of 40 were almost 10% more likely to be tested for a heart attack than those just under 40. The difference shows up as a discontinuity, a jump up in the probability of being tested as patients cross their 40th birthday.

Messrs. Jena and Worsham show that similar discontinuities appear throughout medicine. Heart-attack patients just under the age of 80, for instance, are more likely to be given coronary artery bypass surgery than those just over 80. Kidneys from patients who die at age 69, just short of their 70th birthday, are more likely to be used for transplant than kidneys from patients just over 70, even though by all objective measures the kidneys are equally viable and valuable. Perhaps most tellingly, “children” just under the age of 18 are less likely to be prescribed opioids than “adults” slightly over the age of 18, even though these groups are statistically indistinguishable.

The point of these studies isn’t to titter or sigh at the peculiarities of human reasoning but to use these natural experiments to estimate the effect of medical procedures. If the only reason that near-18 and 18-year-olds are prescribed opioids differently is the semantics of “child” and “adult,” then we can use the discontinuity in prescriptions as a natural experiment—it’s as if prescribing around the age of 18 were randomly assigned. The authors find, for example, that compared to the just-under-18s, the just-over-18s were 12.6% more likely to later be diagnosed for an opioid-related adverse event such as an overdose. The greater rate of overdose is valuable information—but imagine the difficulty of trying to convince an Institutional Review Board that it would be ethical to randomly prescribe opioids to young people.