Azra Bihorac

@azrabihorac.com

Physician, scientist, institution builder. Senior Associate Dean for Research and Founding Director of the AI for Health Institute, University of Florida. I write Nonalgorithmic: on what medicine must not let go of in the AI era. nonalgorithmic.com

A decision-support tool aimed at an outcome should not go live unless that outcome is routinely assessed in the population it targets. Otherwise the trial, and the quality dashboard after it, will measure the screening practice rather than the tool.

Night sky with the moon behind clouds and palm fronds. Text: The Standing Order. Who was never assessed. A trial of AI decision support for postoperative delirium could not count most of the patients it was meant to help. Author's photograph.

On Tuesday I asked who pays for human oversight. Before a clinician checks an AI output comes something plainer: a person counting what happened to the patient. In a new delirium trial, no one counted for 6,039 of 7,294 patients.

Night sky with the moon behind clouds and palm fronds. Text: The Standing Order. Who was never assessed. A trial of AI decision support for postoperative delirium could not count most of the patients it was meant to help. Author's photograph.

A trial of AI decision support for postoperative delirium flagged 7,294 surgical patients. A delirium assessment was documented for only 1,255 of them. The trial left screening to routine care, and routine care counted fewer than 1 in 5. #MedSky

Night sky with the moon behind clouds and palm fronds. Text: The Standing Order. Who was never assessed. A trial of AI decision support for postoperative delirium could not count most of the patients it was meant to help. Author's photograph.

Payment cuts are easy to measure, which makes claims automation attractive. Picture insurers' AI finding ever smaller grounds to reduce payment, and providers' AI contesting each one. For patients, could this add cost, raise premiums or limit access to care? #MedSky

Title card: The Standing Order, When AI Changes What Care Is Paid For. Insurance decisions shape what care is recognized, covered, and paid for. Over a pine tree at dusk.

A DC bill would bar insurers from using AI to downcode claims and require a clinician in the same specialty to review each one. Georgia lets AI help with utilization review, but not overrule the clinical peer. What must a human reviewer be able to do for the review to count? #MedSky

Title card: The Standing Order, When AI Changes What Care Is Paid For. Insurance decisions shape what care is recognized, covered, and paid for. Over a pine tree at dusk.

Our new Perspective in npj Digital Medicine: AI is entering every stage of medical education. The least developed part is continuing education for practicing physicians, who use clinical AI every day and model it for every trainee watching them. Where should that training live? #MedSky #MedEd

Figure 1, AI across the medical education continuum: a grid of three systems (institutional, learning, readiness and safety) across medical students, residents and fellows, and attending physicians. From Patel, Haziroglu et al., npj Digital Medicine 2026, CC BY 4.0.

Scientific credit is “the currency of the realm,” writes Jeffrey Flier. When Anthropic said Claude found a new enzyme system, researchers questioned its novelty. Before assigning credit to an AI discovery, what evidence should we require about who, and what, did the work? #MedSky

Title card: Reviewing AI agents in medicine and science: what the record leaves out, over a photograph of a pine against the sky in Gainesville, Florida.

An AI agent chatted with 98 patients under live physician supervision. No safety stop was triggered. One exchange was judged somewhat harmful afterward. Omar and Nadkarni: harm may emerge after supervision ends. What should the follow-up review include? #MedSky

Title card: Reviewing AI agents in medicine and science: what the record leaves out, over a photograph of a pine against the sky in Gainesville, Florida.

1/9 The FDA is asking how to evaluate generative AI in medicine. We also need to measure what using it does to the clinicians who judge it. Oversight is being built on clinicians as both the standard and the safeguard. I am wary of that double bind, for three reasons.

Forest on a hillside in autumn, a valley visible through the trees. Author's photograph, Asheville.

AB 1979 does not prohibit clinical decision support. It prohibits a facility from deploying AI to independently perform a licensed act. The duty binds the deployer, not the developer. And it sits in Division 8, so a licensing board enforces it. nonalgorithmic.com/2026/09/15/a...

Three cardiovascular AI moves in 8 days: ADVOCATE, AB 1979’s Chapter 25.5, and the FDA’s 3 sites

Where a rule is written decides who enforces it: AB 1979 puts clinical AI in the Business and Professions Code.

nonalgorithmic.com