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Anesth Analg 2005;101:465-473
© 2005 International Anesthesia Research Society
doi: 10.1213/01.ANE.0000154536.34258.A8

ECONOMICS, EDUCATION, AND HEALTH SYSTEMS RESEARCH

Validation of Statistical Methods to Compare Cancellation Rates on the Day of Surgery

Franklin Dexter, MD, PhD*{dagger}{ddagger}, Eric Marcon, PhD§, Richard H. Epstein, MD||, and Johannes Ledolter, PhD{ddagger}

*Division of Management Consulting and Departments of {dagger}Anesthesia and {ddagger}Health Management and Policy, University of Iowa, Iowa City; §Department of Industrial Maintenance, Jean Monnet University, Roanne Cedex, France; and ||Department of Anesthesiology, Jefferson Medical College

Address correspondence and reprint requests to Franklin Dexter, Anesthesia 6-JCP, University of Iowa, Iowa City, Iowa 52242. Address e-mail to franklin-dexter{at}uiowa.edu.

We investigated the validity of several statistical methods to monitor the cancellation of electively scheduled cases on the day of surgery: {chi}2 test, Fisher’s exact test, Rao and Scott test, Student’s t-test, Clopper-Pearson confidence intervals, and Chen and Tipping modification of the Clopper-Pearson confidence intervals. Discrete-event computer simulation over many years was used to represent surgical suites with an unchanging cancellation rate. Because the true cancellation rate was fixed, the accuracy of the statistical methods could be determined. Cancellations caused by medical events, rare events, cases lasting longer than scheduled, and full postanesthesia or intensive care unit beds were modeled. We found that applying Student’s two-sample t-test to the transformation of the numbers of cases and canceled cases from each of six 4-wk periods was valid for most conditions. We recommend that clinicians and managers use this method in their quality monitoring reports. The other methods gave inaccurate results. For example, using {chi}2 or Fisher’s exact test, hospitals may erroneously determine that cancellation rates have increased when they really are unchanged. Conversely, if inappropriate statistical methods are used, administrators may claim success at reducing cancellation rates when, in fact, the problem remains unresolved, affecting patients and clinicians.




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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 © 2005 by the International Anesthesia Research Society.