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Anesth Analg 1984; 63:79-82
© 1984 International Anesthesia Research Society
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Detection of Anesthesia Machine Faults

Charles W. Buffington, MD, Sivam Ramanathan, MD, and Herman Turndorf, MD

Recieved from the Department of Anesthesiology, University of Washington, Seattle, Washington; and the Department of Anesthesiology, New York University School of Medicine, New York, New York.

Abstract

One hundred ninety people attending an anesthesia meeting were given ten minutes to identify five faults intentionally created in a standard anesthesia machine. 7.3% of participants found no machine faults and 3.4% found all five faults. The average number of identified faults was 2.2. Professional background did not influence the scores, but fault detection ability was increased in practitioners with ten years or more of experience. Concealed faults that did not make the machine inoperable were most frequently missed. Greater emphasis should be placed on aggressive system checking in education programs and in daily clinical practice.

Key Words: EQUIPMENT—anesthesia machines




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 Anesth. Analg.Home page
E. R. Larson, G. A. Nuttall, B. D. Ogren, D. D. Severson, S. A. Wood, L. C. Torsher, W. C. Oliver, and M. E. S. Marienau
A Prospective Study on Anesthesia Machine Fault Identification
Anesth. Analg., January 1, 2007; 104(1): 154 - 156.
[Abstract] [Full Text] [PDF]


Lippincott, Williams & Wilkins Anesthesia & Analgesia® is published for the International Anesthesia Research Society® by Lippincott Williams & Wilkins with the assistance of Stanford University Libraries' HighWire Press®. Copyright 2006 by the International Anesthesia Research Society. Online ISSN: 1526-7598   Print ISSN: 0003-2999 HighWire Press
Copyright © 1984 by the International Anesthesia Research Society.