Tampa General Hospital

Over 50% of surgical procedures experience at least one delay, increasing the risk of complications such as surgical site infections, blood clots, and pneumonia. Surgical teams were forced to simultaneously deliver patient care and manually document every OR movement, creating data gaps that undermined scheduling accuracy. Without real-time visibility, schedulers could not identify bottlenecks or optimize block utilization.

Tampa General deployed ambient AI and computer vision (via Apella) to automatically capture and analyze key OR turnover events in real time. The system generated scheduling recommendations, enabled block consolidation analysis, and provided live-stream access so clinicians could remotely check surgical case progress without physically entering the OR. This eliminated manual documentation burden while producing accurate, continuous operational data.

OR turnover times decreased by 12% among surgical teams with the longest turnover times, creating capacity for an estimated 38 additional cases per year. Block consolidation recommendations reallocated 56 hours of block time per week, enabling an estimated 832 additional cases annually. From March through December 2024, staff accessed live streams 22,858 times, saving approximately 40,000 minutes of clinician time and reducing door interruptions by ~1.4 opens per case.

• Real-time ambient AI removes the documentation burden from clinical staff, generating more accurate OR data without competing with patient care priorities.
• Reducing OR door openings is both an efficiency and an infection control win — fewer airborne particles enter the sterile field, directly lowering SSI risk.
• Block-time analysis powered by AI can unlock significant hidden capacity (56 hrs/week here) without adding physical resources or new spend.