Document Detail


Using clinical variables to guide surgical site infection detection: A novel surveillance strategy.
MedLine Citation:
PMID:  25465259     Owner:  NLM     Status:  In-Data-Review    
Abstract/OtherAbstract:
BACKGROUND: Surgical site infections (SSIs) are a common and expensive health care-associated infection, and are used as a health care quality benchmark. As such, SSI detection is a major focus of infection prevention programs. In an effort to improve on conventional surveillance methods, a simple algorithm for SSI detection was developed using clinical variables not traditionally included in National Healthcare Safety Network definitions.
METHODS: A case-control study was conducted among surgeries performed at the Veterans Affairs Boston Healthcare System between January 2008 and December 2009. SSI cases were matched to controls without SSI. Clinical variables (administrative, microbiological, pharmacy, radiology) were compared between the groups to determine those that best identified SSI.
RESULTS: A total of 70 SSIs were matched to 70 controls. On multivariable analysis, variables significantly associated with SSI identification were wound culture order, computed tomography scan/magnetic resonance imaging order, antibiotic order within 30 days after surgery, and application of a relevant International Classification of Disease, Ninth Revision code. Among patients with no SSI identifiers, 98% were correctly classified as having no SSI. Among patients with multiple SSI identifiers, 97.1% were correctly identified as having SSI. The area under the curve for this model was 0.87.
CONCLUSION: We have derived a novel surveillance algorithm for SSI detection with excellent operating characteristics. This algorithm could be automated to streamline infection control efforts.
Authors:
Westyn Branch-Elliman; Judith Strymish; Kamal M F Itani; Kalpana Gupta
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Publication Detail:
Type:  Journal Article     Date:  2014-11-25
Journal Detail:
Title:  American journal of infection control     Volume:  42     ISSN:  1527-3296     ISO Abbreviation:  Am J Infect Control     Publication Date:  2014 Dec 
Date Detail:
Created Date:  2014-12-03     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  8004854     Medline TA:  Am J Infect Control     Country:  United States    
Other Details:
Languages:  eng     Pagination:  1291-5     Citation Subset:  IM    
Copyright Information:
Published by Elsevier Inc.
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