3 Ways AI Is Rewriting the Rules of OR Efficiency

Being "watched" by video cameras collecting and analyzing OR activities through AI-enabled computer vision might make any OR team member feel hesitant.

At AdventHealth Celebration in Florida, OR Senior Nurse Manager Nicholas DeStefano, BSN, RN, CNOR, saw that concern firsthand.

Securing Team Comfort with AI

To help teams understand how AI would be used, DeStefano coordinated open forums, secured physician champions, and shared the goals of the AI tools. An important part of this conversation was to confirm that "video recordings from the OR would not be used to punish mistakes."

With his teams informed and prepared to adopt AI, their ORs were first equipped with video cameras for computer-vision capability in June 2024.

The tool quickly became a central resource for improving OR efficiency, DeStefano says. "It's a real-time analytics engine that captures critical timestamps like 'wheels in to incision' and monitors traffic patterns, surgical readiness, and environmental inefficiencies."

By integrating AI and the data it provides, DeStefano and his teams have shifted from relying on anecdotal observations about delays to capturing objective, time-stamped data. "It's completely reframed how we define and measure surgical efficiency," he said.

Applying AI-Driven OR Efficiencies

DeStefano is preparing to present these AI-driven improvements at AORN Global Surgical Conference & Expo in New Orleans, April 11–14. Ahead of the conference, he shared several ways AI computer vision is advancing efficiency in their ORs.

1. Creates Predictive Readiness Monitoring

By analyzing annotated room activity, such as surgeon, staff, and anesthesia entry and exit, the team identified recurring workflow bottlenecks. These insights supported targeted staffing adjustments, refined room readiness protocols, and more effective parallel processing for breaks and lunches.

2. Improves Documentation Accuracy

AI analytics helped flag discrepancies in electronic documentation and informed the development of preprocedural readiness tools to support patient preparedness. The data also assist with pre-op auditing and tracking turnover delays by hour of the day.

3. Increases Real-Time Accountability

Verifiable timestamps provided through AI align with internal observations and enable clearer conversations about delay sources. "This has helped turn assumptions into actionable data," DeStefano says.

After implementing AI, the team launched a department-wide accountability initiative that increased on-time first case starts from 61.87 percent to 78 percent within a few months, the highest rate in three years. They also reduced turnover times and cut turnover times in half for some service lines, including neurosurgery.

When guiding teams through AI adoption, DeStefano emphasizes leading "with empathy, not enforcement."

Register now for AORN Global Surgical Conference & Expo 2026 and plan time to attend DeStefano's education session, "From Resistance to Precision: AI's Path to Surgical Transition."