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Semiautomated Surveillance of Deep Surgical Site Infections After Primary Total Hip or Knee Arthroplasty

Published online by Cambridge University Press:  03 April 2017

Meander E. Sips ,
Marc J. M. Bonten  and
Maaike S. M. van Mourik
Meander E. Sips*
Affiliation:
Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands
Marc J. M. Bonten
Affiliation:
Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands Department of Medical Microbiology, University Medical Center Utrecht, Utrecht, The Netherlands.
Maaike S. M. van Mourik
Affiliation:
Department of Medical Microbiology, University Medical Center Utrecht, Utrecht, The Netherlands.
*
Address correspondence to Meander E. Sips, University Medical Center Utrecht, Julius Center for Health Sciences and Primary Care, Huispost Str. 6.131, PO Box 85500, 3508 GA Utrecht, The Netherlands (m.e.sips-3@umcutrecht.nl).
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Abstract

Manual surveillance of surgical site infections (SSIs) after total hip or knee arthroplasty is time-consuming and prone to error. Semiautomated surveillance based on routine care data extracted from electronic health records can retrospectively identify deep SSIs and substantially reduce workload while maintaining 100% sensitivity.

Infect Control Hosp Epidemiol 2017;38:732–735

Type
Concise Communications
Information
Infection Control & Hospital Epidemiology , Volume 38 , Issue 6 , June 2017 , pp. 732 - 735
Copyright
© 2017 by The Society for Healthcare Epidemiology of America. All rights reserved 

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Footnotes

PREVIOUS PRESENTATION: These data were previously presented at the European Congress of Clinical Microbiology and Infectious Diseases (ECCMID) on April 10, 2016, in Amsterdam, The Netherlands (oral presentation no. O342).

References

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