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Validation of Administrative Population-Based Data Sets for the Detection of Cesarean Delivery Surgical Site Infection

Published online by Cambridge University Press:  02 January 2015

Nick Daneman*
Affiliation:
Institute for Clinical Evaluative Sciences, Toronto, Ontario, Canada Division of Infectious Diseases, Department of Medicine, Sunnybrook Health Sciences Centre, University of Toronto, Ontario, Canada
Xiaomu Ma
Affiliation:
Institute for Clinical Evaluative Sciences, Toronto, Ontario, Canada
Melanie Eng-Chong
Affiliation:
Department of Infection Prevention and Control, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada
Sandra Callery
Affiliation:
Department of Infection Prevention and Control, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada
Astrid Guttmann
Affiliation:
Institute for Clinical Evaluative Sciences, Toronto, Ontario, Canada Division of Pediatric Medicine, Hospital for Sick Children, Toronto, Ontario, Canada Department of Health Policy, Management and Evaluation, University of Toronto, Ontario, Canada
*
Division of Infectious Diseases, Sunnybrook Health Sciences Centre, University of Toronto, 2075 Bayview Avenue, Toronto, Ontario M4N 2M5, Canada (nick.daneman@sunnybrook.ca)

Abstract

We validated population-based hospital, emergency room, and physician claim databases for the detection of surgical site infections against the reference standard of clinical surveillance. Although these data sets are highly specific and could be used to define research cohorts, their low sensitivity and positive predictive value make them inadequate for use as quality indicators.

Type
Concise Communications
Copyright
Copyright © The Society for Healthcare Epidemiology of America 2011

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