What’s in a Number? Why All These Binary Definitions of Health and Disease?

A blood pressure of 139/89 would be considered okay, but a reading of 140/90 on the last visit of the year gives the treating physician a failing grade, also called a “Care Gap” in the category of Controlling Blood Pressure. Never mind if that last appointment happened while the patient had a broken rib and was in pain. The same binary standard applies to hemoglobin A1c as to whether diabetes is controlled or not co The same binary standard applies to hemoglobin A1c as to whether diabetes is controlled or not compare that with the Fed, changing interest rates by a quarter of a point every so many months and making big news in the proces. Compare that with the Fed, changing interest rates by a quarter of a point every so many months and making big news in the process.

The practice of medicine is getting sillier and sillier the more we are held to “quality” measures. That is a substitute marker for outcomes. If you think about it, I could start a heavy duty blood pressure medication on my patient with a broken rib and reactive blood pressure from that and bring him back for a recheck before the end of the year and thus meet my quality parameters. In early January, when the rib fracture is no longer causing pain, the patient has an orthostatic blood pressure drop, falls to the ground, landing on cement and dies from a subdural hematoma. I would still be in good shape with my quality metrics.

The modern risk calculators that we use to assess cardiovascular risk in people with elevated cholesterol make it very plain that cardiovascular risk is a multifactorial calculation. Why we don’t have a similar view of blood pressure when we could use the cholesterol risk calculators to illustrate the difference between two different blood pressure numbers, whether with or without medication is, simply, ignorant.

In medicine today, not even gender is considered a binary metric. Why in the world are we then viewing cholesterol, blood pressure, or even blood sugar for that matter, more clearly defined than gender? If medical providers are too lazy to plug in blood pressure numbers into the cardiac risk calculators to determine the value of treating such blood pressures, perhaps AI can be of help doing the math for us?