Health Care

Aaron Brown | 2.3.2026 11:15 AM

Marty Makary was appointed commissioner of the Food and Drug Administration (FDA) in 2025. The prominent surgeon, medical researcher, bestselling author, and critic of the medical establishment—including the FDA and the Centers for Disease Control and Prevention—has made the incendiary claim that medical errors are the third-leading cause of death in the United States, roughly equal to the next four causes combined: smoking-related lung disease, suicide, firearms, and automobile accidents.

In January 2026, the FDA issued a draft for public comment advocating more use of Bayesian statistics in drug approvals and other FDA actions. "Bayesian methodologies help address two of the biggest problems of drug development: high costs and long timelines," Makary wrote. "Providing clarity around modern statistical methods will help sponsors bring more cures and meaningful treatments to patients faster and more affordably." The proposal also claims a Bayesian approach would result in more accurate and nuanced advice for patient subgroups. 

This move would be roughly analogous to regulators moving away from rigid rules specifically defining mandated and forbidden behavior and toward trying to achieve the same regulatory goals with sometimes market-based tools to help nudge people's behavior, such as auctions, subsidies, and taxes. 

Rather than central planners making one-size-fits-all choices for people they never met, don't understand, and wouldn't like if they did meet, that approach allows individuals to choose for themselves in individualized reaction to the carrots and sticks wielded by planners. It's a kinder, gentler central planning.

The public health/medical complex is a battleship, and it takes more than one commissioner waving a draft proposal to change its direction. Makary's proposal is incremental, not revolutionary. While the FDA's DNA is what statisticians call "frequentist," Bayesian methods have been sneaking in through the back door for decades. The Makary proposal is to open the front door for them, but to watch them carefully so they don't steal the frequentist silver. Only Bayesian tools are permitted entry, not Bayesian theory. 

A key theoretical divide runs between Bayesians and frequentists. Frequentists define probability as the long-run frequency of repeated independent trials. There are some severe philosophical issues with that, but it does seem to make some sense for events such as coin flips, dice rolls, and roulette spins. It's harder to apply that method to things that happen once, like the probability of rain tomorrow or of the Seattle Mariners winning the 2026 World Series. 

Bayesians define probability as subjective belief—loosely speaking, the value you would place on a bet. For example, according to recent odds posted at FanDuel, a claim that pays $100 if the Mariners win the World Series is worth $5.78 today, and FanDuel will sell you one for $7.14 (the difference is FanDuel's expected profit). Now that's a betting line offered by a commercial venture, not any individual's subjective belief, but it suggests a reasonable Bayesian estimate of the probability of the Mariners winning is 5.78 percent if you have no strong knowledge on the subject to outguess the bookies.

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