Dr. Mathias Bostrom, orthopedic surgeon-in-chief at the Hospital for Special Surgery, said it plainly in *Fortune* this month: Americans have better data for choosing a restaurant than for choosing a surgeon.
He's right.
The argument patients haven't been allowed to have
For decades, the idea of publishing surgeon-level outcomes has run into the same objections:
• The cases aren't comparable
• Risk-adjustment is imperfect
• Publishing rates punishes the surgeons who take the hardest cases
• It drives defensive medicine
All of that is partly true. None of it is a reason to keep patients in the dark. It's a reason to do the work carefully.
What's changed in 2026 is that the work has already been done. The American College of Surgeons runs quality programs with the math and the benchmarks. CMS's new TEAM model, mandatory for roughly 740 hospitals starting January, forces tracking of the entire 30-day surgical episode — complications, readmissions, recovery — whether hospitals publish it or not.
The data exists. The question is whether it reaches the person who most needs it: the patient sitting in a consult room, trying to decide.
The signal the data can't see yet
Outcome numbers are lagging indicators. They tell you what happened to the last two hundred patients. They don't tell you how the surgeon behaves on a hard day, how they respond when the anatomy surprises them, or whether they listen when the scrub nurse says something isn't right.
The people who *can* tell you that are standing three feet from the table.
• The circulating nurse who's worked with forty different surgeons this year
• The scrub tech who can tell you, from muscle memory, whose cases run smooth and whose don't
• The device rep who's been in three hundred of the same procedure across dozens of operators
They don't need a risk-adjusted database. They have pattern recognition built from hundreds of direct observations.
Why both signals matter
Outcomes data and peer observation aren't competitors. They're the two halves of the same picture:
Outcomes data tells you what the pattern produced.
Peer observation tells you what the pattern looks like in real time.
A surgeon with a great complication rate and poor OR-team reviews is someone the system should be watching. A surgeon with middling outcomes but universal respect from their team is usually someone whose case mix is harder than the numbers reflect. Neither data point alone is enough. Together, they're hard to argue with.
This is why Physician Signal exists. Peer observation from verified OR staff isn't a replacement for outcomes transparency — it's the leading indicator outcomes eventually confirm.
What changes for patients
A patient considering surgery in 2026 has more available than ever:
• Hospital-level outcome data (Leapfrog, CMS Star Ratings)
• ACS-accredited quality programs at participating hospitals
• Surgeon-specific peer observations on Physician Signal
• Direct questions to ask the surgeon: complication rate, case volume, how their outcomes compare to national benchmarks
Dr. Bostrom's point — that the surgeon you're considering should be able to answer those questions — is the right one. A surgeon who treats "how do your outcomes compare?" as an insult is telling you something. A surgeon whose OR team respects them has already told you the rest.
The shift
The old model assumed patients couldn't handle the data. The new model — restaurant-review logic applied to the most consequential decisions patients ever make — assumes they can.
They can. They just need it handed over.
Physician Signal aggregates anonymous, role-verified peer observations from OR professionals. It is not medical advice and is not a substitute for clinical judgment, individual physician consultation, or formal credentialing data.