Decoding the OR Black Box and Similar Technologies and Considerations in Otolaryngologic Surgery

Comprehensive Summary

Several forms of data-capturing systems are used within the operating room (OR) including technologies such as computer vision, audio signaling processing, and enterprise data warehouses. The authors of this article propose referring to these systems with the term: Multimodal Operating-­room Data Acquisition and Leveraging (MODAL). The term MODAL provides a framework to understand these technologies and envision their application in the field of otolaryngology. Speed and timing are two defining characteristics of MODAL technologies as they determine the availability and application of data. Data acquisition using MODAL technologies can be delayed or generated in near-real time or real time. MODAL systems can be used to facilitate safety and checklist compliance with the integration of various data sources including audio, video, and quantitative data points. It can also be used to provide a largely unbiased assessment of quality improvement to identify areas of improvement in the surgical setting and produce comprehensive operative reports. An exciting avenue for MODAL exists in its potential integration with artificial intelligence (AI) which would allow for real-time feedback by AI on data collected by MODAL systems to serve as a clinical-decision making tool for otolaryngologists in surgery. Although promising, the concept of MODAL systems remains fairly new and there are several consideration to examine prior to its integration into the OR workflow. For instance, implementing MODAL systems is expected to require acceptance and approval from OR staff, availability of local specialists to assist with technology, and consideration of the legal implications of using MODAL tools.

Outcomes and Implications

MODAL technologies are promising for their ability to provide a unifying system for data capturing that can be used for various purposes such as quality improvement, safety assessments, and clinical-decision making support in cooperation with AI. Integrating MODAL systems into the OR setting raises questions about privacy concerns as data captured and stored in the form of voice and audio recordings could be vulnerable to cyberattacks. This is especially relevant in the field of otolaryngology where procedures largely involve the patient's face being in view for the duration of the surgery. MODAL systems would also create demands on institutions when it comes to technological requirements and legal implications that come with adopting such frameworks.