Tag: Quantification

Medicine is Not Like Math


We do a lot of things in our head in this business. Once a patient reports a symptom, we mentally run down lists of related followup questions, possible diagnoses, similar cases we have seen. All this happens faster than we could ever describe in words (let alone type).

And, just like in math class, we are constantly reminded that it doesn’t matter if we have the right answer if we can’t describe how we got there.

So the ninth doctor who observes a little girl with deteriorating neurologic functioning and after less than ten minutes says “your child has Rett Syndrome” could theoretically get paid less than the previous eight doctors whose explorations meandered for over an hour before they admitted they didn’t know what was going on.

Does anybody care how Mozart or Beethoven created their music? Or do we mostly care about how it makes us feel when we listen to it?

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The Quantified Doctor

flying cadeucii88.2 % of all statistics are made up on the spot
– Victor Reeves

There’s a growing movement in medicine in general and imaging in particular which wishes to attach a number to everything.

It no longer suffices to say: “you’re at moderate risk for pulmonary embolism (PE).”

We must quantify our qualification.

Either by an interval. “Your chances of PE are between 15 and 45 %.”

Or, preferably, a point estimate. “You have a 15 % chance of PE.”

If we can throw a decimal point, even better. “You have a 15.2 % chance of PE.”

The rationale is that numbers empower patients to make a more informed choice, optimizing patient-centered medicine and improving outcomes.

Sounds reasonable enough. Although I find it difficult to believe that patients will have this conversation with their physicians.

“Thank god doctor my risk of PE is 15.1 % not 15.2 %. Otherwise I’d be in real trouble.”

What’s the allure of precision? Let’s understand certain terms: risk and uncertainty; prediction and prophesy.

By certainty I mean one hundred percent certainty. Opposite of certainty is uncertainty. Frank Knight, the economist, divided uncertainty to Knightian risk and Knightian uncertainty (1).

What’s Knightian risk?

If you toss a double-headed coin you’re certain of heads. If you toss a coin with head on one and tail on the other side, chance of a head is 50 %, assuming it’s a fair coin toss. Although you don’t know for certain that the toss will yield head or tail, you do know for certain that the chance of a head is 50 %. This can be verified by multiple tosses.

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