Modeling surgeon belief updating under bias: a Bayesian simulation in shoulder arthroplasty

This Bayesian simulation provides a practical framework to demonstrate how prior beliefs and cognitive bias can markedly influence the way shoulder surgeons interpret and act upon new evidence, contributing to unwarranted variation in care. When it comes to treatment recommendations, what surgeons believe at the outset may matter as much or more than the data itself. Implementing targeted strategies such as foundational principles based in behavioral ethics, evidence-based decision and debiasing aids, structured peer review, and routine performance feedback may help align treatment decisions more closely with a patient's values based on the best available evidence. The use of rTSA-favoring evidence in this simulation is solely for illustrative purposes and should not be interpreted as an endorsement of increased rTSA use in clinical practice.