Stanford University’s Technology Enabled Clinical Improvement Center and 7-SIGMA
use sensor and magnetic motion tracking technology for a first-of-its-kind study.
MINNEAPOLIS, MN, October 2, 2018 – 7-SIGMA and Stanford University’s Technology Enabled Clinical Improvement (T.E.C.I.) Center are excited to announce the launch of a sensor-driven data collection at the 2018 American Society of Anesthesiologists Meeting in San Francisco, CA.
While simulation technology is frequently used for training intubation skills, manikinbased simulators either do not provide quantifiable feedback or they lack fidelity and realism. What if you could harness high fidelity with data-driven and research-supported feedback?
7-SIGMA and the T.E.C.I. Center’s sensorized data collection is taking intubation simulation to the next level by harnessing motion tracking and imbedded sensor technology to provide instantaneous feedback and measurements of success to trainees.
The above figure highlights the sensor technology (A, B) that will be used in the upcoming data collection at the American Society of Anesthesiologists Meeting. The sensor outputs (C, B) provide the objective means for characterizing one’s intubation performance.
To characterize expert intubation and ultimately map that information into an effective teaching and learning system, expert intubation must first be robustly characterized. 7-SIGMA and the T.E.C.I Center invite you to contribute your intubation expertise by intubating two different high fidelity airway manikins, representative of a basic and an
advanced (burned) airway. The study is occurring in booths 346 and 347 on October 13-17 at the 2018 American Society of Anesthesiologists Meeting in San Francisco, CA. Research results will be shared with the medical education community via publications.
Research results will be shared with the medical education community via publications.
Additional Information: In a 2018 study titled “Errors and Clinical Supervision of Intubation Attempts by the Inexperienced” (Satyapal, Rout, & Sommerville), 18% of intubations performed on real patients by junior doctors and allied health trainees were unsuccessful and required a supervisor or assistant to step in. The study involved the identification of key common problematic phrases during intubation (based upon video observation) and found that “step-by-step analysis of the intubation sequence” can facilitate the process of skill acquisition and ultimately, improve patient outcomes. Furthermore, the outcomes of the study highlight three potentially problematic phases of
the intubation process: positioning of the patient’s head, use of the laryngoscope, and manipulation of the ET tube. The authors note that individual intubation attempts could be influenced by the “action or inaction of supervisor and/or assistant, in making more explicit manoeuvers leading to conscious competence upon which the trainee could build expertise.” While these conclusions compelling, the reality is, not all facilities and training scenarios allow for such structured feedback and analysis.
With the advent of 7-SIGMA and the T.E.C.I. Center’s Intubation Excellence Database, there is vast potential to significantly improve the intubation training experience as well as intubation outcomes by providing quantified, personalized and deliberate feedback on an individual’s intubation performance. Globally, the use of sensor-enabled manikins and motion tracking technology to build a database that characterizes expertise for any given procedure, challenges the current paradigm for evaluating clinical training and outcomes.
About 7-SIGMA: 7-SIGMA Simulation Systems ( 7S3 ) has developed a line of innovative, high-fidelity airway simulation training products. Drawing upon 50 years of material science, patented technology, and precision manufacturing, 7-SIGMA, through collaborations with educators and health care professionals, is providing the premier training platform for airway management. Responding to the industry demand for quantitative and qualitative feedback, 7S3 has incorporated its conformable sensor technology into the next generation of training tools, further enhancing the skill development of the trainee and the assessment value to the trainer. 7-SIGMA’s modular designed products provide ease of use, and facilitate an expanding portfolio of pathologies, making them the premier ducational tools for health care simulation training.
About TECI Center: The Technology Enabled Clinical Improvement (T.E.C.I.) Center is a multidisciplinary team of researchers dedicated to the design and implementation of advanced engineering technologies that facilitate data acquisition relating to clinical performance. The T.E.C.I. team has had great success in quantifying physicians’ clinical experiences using sensor, video, and motion tracking technologies. This work has resulted in an information rich database that enables empirical evaluation of clinical excellence and medical decision making. By leveraging highly specific and objective clinical performance metrics, the T.E.C.I. Center is harnessing the unique opportunity to support peer to peer data sharing and clinical collaborations that can transform the clinical workflow and benefit healthcare providers. Ultimately, the T.E.C.I. Center aims to transform human health and welfare through advances in data science and personalized, technology-based performance metrics for healthcare providers.
Contact: If you would like more information, please contact 7-SIGMA at email@example.com or 612-252-6296.