The brand-new center combines real surgical environments with AI-driven data and objective feedback so that surgeons can continuously refine their training.
“It shifts education from subjective observation to measurable outcomes, accelerating mastery and ultimately improving patient care,” says Jill Goodwin, CEO of Axis Research and Technologies, and co-founder and COO of medical tech company OMNIMED.
Building an Objective Performance Baseline for Surgery
Instead of relying on subjective scoring, the OMNIMED SmartOR platform will help build objective performance baselines for training surgeons, says OMNIMED CTO Robert Brown. The platform uses synchronized data from 3D cameras, microphones, and location and environmental sensors to capture workflow timing, team movement, equipment use and room context. It all coalesces into structured metadata that offers a clearer picture for a surgery.
“These AI-based performance baselines are established and continuously refined in the performance center, aligned with institutional standards and expert benchmarks,” Brown says.
Instead of isolated assessments, the platform creates a continuous learning loop so that any surgical activity can be measured and linked to outcomes. An integrated AI agent allows teams to explore this information conversationally afterward using natural language queries.
DISCOVER: How is AI supporting hospitals’ operating rooms?
“Users can compare approaches, validate assumptions, test theories and identify best practices using simple speech rather than reviewing another static report,” Brown adds.
That performance data is used strictly for learning and improvement, and hospitals can define how insights are applied. Validation comes from linking execution baselines to real-world outcomes, such as complications, length of stay, procedure duration and operational efficiency.
“Teams can compare results before and after implementation and track progress across simulation, training and live operating rooms, using industry-desired baselines,” Brown says.
