Autonomous Operating Room Monitoring Platforms: A Multicenter Evaluation

Abstract

Ceiling-mounted cameras, ambient microphones, and depth sensors are increasingly deployed in operating rooms as part of platforms marketed as autonomous monitoring systems, capable of tracking surgical phases, safety-checklist compliance, team traffic, and noise in real time. This review surveys the multicenter evidence for these platforms, tracing their conceptual lineage from aviation-style 'black box' recorders and decades-old automated anesthesia record keeping to current computer-vision and audio-analytic systems. Observational multicenter data show a consistent gap between assumed and actual safety-behavior compliance once continuous machine observation replaces self-report, along with measurable team traffic and distraction patterns not previously quantifiable at scale. The alarm-fatigue literature from bedside physiologic monitoring offers a direct cautionary parallel, and the platforms with the most credible evidence to date favor aggregated feedback over indiscriminate real-time alerting. We conclude that current evidence supports autonomous monitoring as a measurement and quality-improvement instrument rather than a validated driver of improved hard clinical outcomes, and we outline the generalizability, privacy, and alarm-management questions that remain open.