eVent in the Human Patient Simulator
To Evaluate the Efficacy of the Expert System in Enhancing the Anesthesiologist's Ability to Detect Critical Events in a Simulated OR Environment.
|Study Design:||Observational Model: Case-Crossover
Time Perspective: Prospective
|Official Title:||eVENT: An Expert System for Detecting Critical Events During Anesthesia (Human Patient Simulator Study)|
|Study Start Date:||December 2010|
|Study Completion Date:||June 2011|
|Primary Completion Date:||June 2011 (Final data collection date for primary outcome measure)|
The development of new sensors or the intelligent synthesis of existing signals (smart sensors) cannot reliably prevent adverse events unless the investigators assimilate the data produced from these devices and provide it to the clinician in a format that is easy to comprehend. The expert system that the investigators are developing will provide intelligent synthesis of data. The clinician focus can then be directed toward the patient rather than continual observation of the monitors.
Clinicians need an expert system to augment vigilance and situation awareness, and to aid in decision making to prevent patient harm.
The development of an expert system to assist the everyday anesthesiologist in the operating room is a significant challenge that is in urgent need of being addressed. Assistance is required in interpreting the overwhelming stream of physiological data, intelligently extracting key features from these data, and bringing them to the attention of the clinician.
Please refer to this study by its ClinicalTrials.gov identifier: NCT01240317
|Canada, British Columbia|
|BC Children's Hospital|
|Vancouver, British Columbia, Canada, V6H 3V4|
|Principal Investigator:||Mark Ansermino||University of British Columbia|