Surveillance for antimicrobial resistant organisms: Potential sources and magnitude of bias

Abstract

Surveillance has been recognized as a fundamental component in the control of antimicrobial- resistant infections. Although surveillance data have been widely published and utilized by researchers and decision makers, little attention has been paid to assessment of their validity. We conducted this review in order to identify and explore potential types and magnitude of bias that may influence the validity or interpretation of surveillance data. Six main potential areas were assessed. These included bias related to use of inadequate or inappropriate (1) denominator data, (2) case definitions, and (3) case ascertainment; (4) sampling bias; (5) failure to deal with multiple occurrences, and (6) those related to laboratory practice and procedures. The magnitude of these biases varied considerably for the above areas within different study populations. There are a number of potential biases that should be considered in the methodological design and interpretation of antimicrobial-resistant organism surveillance. © 2009 Cambridge University Press.