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QUALITY IMPROVEMENT

Decoding the OR Black Box and Similar Technologies in Otolaryngologic Surgery

Selene C Li, Andrew Bain, Donald Tan, Hongzhao Ji

Published by

World Journal of Surgery cover
World Journal of Surgery cover
Overview

This narrative review introduces the concept of Multimodal Operating-room Data Acquisition and Leveraging (MODAL) systems, which integrate data from multiple intraoperative sources such as surgical equipment, physiologic monitors, electronic health records, and ambient audiovisual recordings. The purpose of these systems is to create a comprehensive understanding of surgical activity in the operating room to improve safety, quality, and efficiency. The review focuses on how these technologies apply to otolaryngology, a specialty particularly suited to MODAL adoption because many procedures rely heavily on video-based visualization, including endoscopic sinus surgery, ear surgery, airway procedures, and transoral robotic surgery.

Results

The review found that emerging multimodal data-capturing technologies enable systematic collection and analysis of operating room data, offering benefits across clinical practice, education, and quality improvement. In otolaryngology, MODAL systems have shown value in supporting intraoperative checklist compliance, enhancing surgical training, and enabling postoperative review for patient safety analysis. These technologies also present growing opportunities for real-time decision support through integration with artificial intelligence and computer vision. Successful adoption requires careful attention to privacy, data management, institutional policy, and collaboration between clinical, technical, and administrative stakeholders.

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A world where every procedure advances the next.

One World Trade Center,
New York, NY 10007, USA

20 Queen St W, Toronto,
ON M5H 3R3, Canada

© 2026 Aimbient. All Rights Reserved.

A world where every procedure advances the next.

One World Trade Center,
New York, NY 10007, USA

20 Queen St W, Toronto,
ON M5H 3R3, Canada

© 2026 Aimbient. All Rights Reserved.