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eVent in the Human Patient Simulator

The safety and scientific validity of this study is the responsibility of the study sponsor and investigators. Listing a study does not mean it has been evaluated by the U.S. Federal Government. Read our disclaimer for details. Identifier: NCT01240317
Recruitment Status : Completed
First Posted : November 15, 2010
Last Update Posted : June 26, 2017
Information provided by (Responsible Party):
Mark Ansermino, University of British Columbia

Brief Summary:
In this study, the investigators are testing the expert system called eVENT. eVENT provides expert advice about the patient's breathing. The investigators have developed and tested a prototype of eVENT and now want to test how it works in practice. To do this the investigators plan to use computer based simulations and test it when used by anesthesiologists in a full size human simulator. If these tests are successful the investigators will then be ready to evaluate eVENT on real patients.

Condition or disease
Efficacy of the Expert System's Ability to Help Detect Critical Events

Detailed Description:

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.

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Study Type : Observational
Actual Enrollment : 36 participants
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
Actual Primary Completion Date : June 2011
Actual Study Completion Date : June 2011

Information from the National Library of Medicine

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Ages Eligible for Study:   Child, Adult, Older Adult
Sexes Eligible for Study:   All
Accepts Healthy Volunteers:   Yes
Sampling Method:   Non-Probability Sample
Study Population
anesthesiologists, anesthesia residents and fellows

Inclusion Criteria:

  • Staff anesthesiologist, fellows and 3rd - 5th year residents will be able to participate in this study.
  • Subjects willing to provide informed consent.

Exclusion Criteria:

  • Inability/failure to provide informed consent.
  • Presence of any of the following conditions oPrevious participation in similar experiment oTaken sedative medication within last 24 hours
  • Inability/failure to obtain 75% or above in the post-training quiz on the correct use of the eVent.
  • Evaluation will be immediately discontinued at request of subject at any point during the study.

Information from the National Library of Medicine

To learn more about this study, you or your doctor may contact the study research staff using the contact information provided by the sponsor.

Please refer to this study by its identifier (NCT number): NCT01240317

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Canada, British Columbia
BC Children's Hospital
Vancouver, British Columbia, Canada, V6H 3V4
Sponsors and Collaborators
University of British Columbia
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Principal Investigator: Mark Ansermino University of British Columbia
Publications automatically indexed to this study by Identifier (NCT Number):
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Responsible Party: Mark Ansermino, Principle Investigator, University of British Columbia Identifier: NCT01240317    
Other Study ID Numbers: H10-02621
First Posted: November 15, 2010    Key Record Dates
Last Update Posted: June 26, 2017
Last Verified: June 2017
Keywords provided by Mark Ansermino, University of British Columbia:
expert system
decision support system
human patient simulator