Literature DB >> 28366180

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

Meander E Sips1, Marc J M Bonten1, Maaike S M van Mourik2.   

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.

Entities:  

Mesh：

Year:  2017        PMID： 28366180     DOI： 10.1017/ice.2017.37

Source DB:  PubMed          Journal:  Infect Control Hosp Epidemiol        ISSN： 0899-823X            Impact factor:   3.254


  3 in total

1.  Natural Language Processing for the Identification of Surgical Site Infections in Orthopaedics.

Authors:  Caroline P Thirukumaran; Anis Zaman; Paul T Rubery; Casey Calabria; Yue Li; Benjamin F Ricciardi; Wajeeh R Bakhsh; Henry Kautz
Journal:  J Bone Joint Surg Am       Date:  2019-12-18       Impact factor: 5.284

2.  Research methodology for orthopaedic surgeons, with a focus on outcome.

Authors:  Anne Lübbeke
Journal:  EFORT Open Rev       Date:  2018-05-21

3.  Electronically assisted surveillance systems of healthcare-associated infections: a systematic review.

Authors:  H Roel A Streefkerk; Roel Paj Verkooijen; Wichor M Bramer; Henri A Verbrugh
Journal:  Euro Surveill       Date:  2020-01
  3 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.