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Using Samples to Estimate the Sensitivity and Specificity of a Surveillance Process

Published online by Cambridge University Press:  02 January 2015

Emma S. McBryde ,
Heath Kelly ,
Caroline Marshall ,
Philip L. Russo ,
D. L. Sean McElwain  and
Anthony N. Pettitt
Emma S. McBryde*
Affiliation:
Victorian Infectious Diseases Service, Melbourne, Australia Hospital Acquired Infection Surveillance System Coordinating Centre, Victoria, Australia School of Mathematical Sciences, Queensland University of Technology, Brisbane, Australia
Heath Kelly
Affiliation:
Victorian Infectious Diseases Reference Laboratory, Melbourne, Australia
Caroline Marshall
Affiliation:
Victorian Infectious Diseases Service, Melbourne, Australia Royal Melbourne Hospital, VICNISS Hospital Acquired Infection Surveillance System Coordinating Centre, and Centre for Clinical Research Excellence in Infectious Diseases, University of Melbourne, Melbourne, Australia
Philip L. Russo
Affiliation:
Hospital Acquired Infection Surveillance System Coordinating Centre, Victoria, Australia
D. L. Sean McElwain
Affiliation:
School of Mathematical Sciences, Queensland University of Technology, Brisbane, Australia
Anthony N. Pettitt
Affiliation:
School of Mathematical Sciences, Queensland University of Technology, Brisbane, Australia
*
Victorian Infectious Diseases Service, Royal Melbourne Hospital, Grattan St., Parkville, Melbourne, VIC, Australia (Emma.McBryde@mh.org.au)
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Abstract

Determining sensitivity and specificity of a postoperative infection surveillance process is a difficult undertaking. Because postoperative infections are rare, vast numbers of negative results exist, and it is often not reasonable to assess them all. This study gives a methodological framework for estimating sensitivity and specificity by taking only a small sample of the number of patients who test negative and comparing their findings to the reference or “gold standard” rather than comparing the findings of all patients to the gold standard. It provides a formula for deriving confidence intervals for these estimates and a guide to minimum requirements for sampling results.

Type
Concise Communications
Information
Infection Control & Hospital Epidemiology , Volume 29 , Issue 6 , June 2008 , pp. 559 - 563
Copyright
Copyright © The Society for Healthcare Epidemiology of America 2008

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