Errors resulting in adverse events are a common cause of morbidity in hospitalized patients. A significant portion of these errors occurs in the operating room (OR) and may be avoidable. A successful operative outcome reflects more than disease factors and postoperative management in isolation. Comprehensive assessment of operative quality is not possible with traditional postevent analysis. In response to this, our group developed and pilot tested a multiport synchronized data capture and analytic platform called the OR Black Box. Previous recording devices have limited the data capture to only video and audio, which restricts the opportunities for automated analysis. The OR Black Box continuously acquires various intraoperative data feeds, such as audiovisual data, physiological parameters from both patients and health care professionals, and multiple other sensors and devices (Figure). Video is captured using in-room wide-angle cameras, and intracorporeal video is collected from the laparoscope or robotic camera or from light-mounted or wearable cameras in open surgical procedures. All inputs are synchronized, encrypted, and stored on a secure server for further analysis. Expert analysts and software-based algorithms populate a procedural timeline using relevant data drawn from these inputs. Data points include procedural steps, disruptive environmental and organizational factors, OR team technical and nontechnical skills, surgeon physiological stress, and intraoperative errors, events, and rectification processes.
Goldenberg MG, Jung J, Grantcharov TP. Using Data to Enhance Performance and Improve Quality and Safety in Surgery. JAMA Surg. 2017;152(10):972–973. doi:10.1001/jamasurg.2017.2888
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