Antimicrobial Resistance Surveillance Systems: Are Potential Biases Taken into Account?

Author:

Rempel Olivia1,Pitout Johann DD.2,Laupland Kevin B.3

Affiliation:

1. O’Brien Centre for the Bachelor of Health Sciences Program, Health Sciences Centre, Faculty of Medicine, University of Calgary, Calgary, Alberta, Canada

2. Departments of Pathology and Laboratory Medicine and Microbiology and Infectious Diseases, University of Calgary and Alberta Health Services, Calgary, Alberta, Canada

3. Departments of Medicine, Critical Care Medicine, Pathology and Laboratory Medicine, and Community Health Sciences, and Centre for Antimicrobial Resistance, University of Calgary and Alberta Health Services, Calgary, Alberta, Canada

Abstract

The objective of this study was to assess potential biases that may influence the validity of contemporary antimicrobial-resistant (AMR) pathogen surveillance systems. Although surveillance data have been widely published and used by researchers and decision makers, little attention has been devoted to the assessment of their validity. A Medline search was used to identify reports, in 2008, of laboratory-based AMR surveillance systems. Identified surveillance systems were appraised for six different types of bias. Scores were assigned as ‘2’ (good), ‘1’ (fair) and ‘0’ (poor) for each bias. The results of this assessment indicate that there are several potential biases that can influence the validity of AMR surveillance information and, therefore, the potential for bias should be considered in the interpretation and use of AMR surveillance data.BACKGROUND: The validity of surveillance systems has rarely been a topic of investigation.OBJECTIVE: To assess potential biases that may influence the validity of contemporary antimicrobial-resistant (AMR) pathogen surveillance systems.METHODS: In 2008, reports of laboratory-based AMR surveillance systems were identified by searching Medline. Surveillance systems were appraised for six different types of bias. Scores were assigned as ‘2’ (good), ‘1’ (fair) and ‘0’ (poor) for each bias.RESULTS: A total of 22 surveillance systems were included. All studies used appropriate denominator data and case definitions (score of 2). Most (n=18) studies adequately protected against case ascertainment bias (score = 2), with three studies and one study scoring 1 and 0, respectively. Only four studies were deemed to be free of significant sampling bias (score = 2), with 17 studies classified as fair, and one as poor. Eight studies had explicitly removed duplicates (score = 2). Seven studies removed duplicates, but lacked adequate definitions (score = 1). Seven studies did not report duplicate removal (score = 0). Eighteen of the studies were considered to have good laboratory methodology, three had some concerns (score = 1), and one was considered to be poor (score = 0).CONCLUSION: Contemporary AMR surveillance systems commonly have methodological limitations with respect to sampling and multiple counting and, to a lesser degree, case ascertainment and laboratory practices. The potential for bias should be considered in the interpretation of surveillance data.

Publisher

Hindawi Limited

Subject

Infectious Diseases,Microbiology (medical)

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