Pilot validation of central line-associated bloodstream infection data in a voluntary surveillance system in Taiwan between October and December 2021

Autor: Hao-Hsin Wu, Shu-Ling Chang, Chiu-Hsia Su, Shu-Hui Tseng, Li-Jung Chien
Jazyk: angličtina
Rok vydání: 2024
Předmět:
Zdroj: Infection Prevention in Practice, Vol 6, Iss 1, Pp 100326- (2024)
Druh dokumentu: article
ISSN: 2590-0889
DOI: 10.1016/j.infpip.2023.100326
Popis: Summary: Background: Central line-associated bloodstream infection (CLABSI) surveillance data are voluntarily submitted to the Taiwan Healthcare-associated Infection and Antimicrobial Resistance Surveillance (THAS) System. Validation of the CLABSI data is important to ensure the quality of surveillance data. We aimed to validate the CLABSI surveillance data reported to the THAS system. Methods: This study was a retrospective medical record review of patients with positive blood cultures admitted to the intensive care units (ICUs) of 13 participating hospitals between October and December 2021. An external validation team was convened to perform the validation process according to the standardised protocol and to record the reasons for misclassification. Discussion: During the study period, 688 patients with 1,238 positive blood cultures from 59 ICUs at 13 hospitals were evaluated. Among the 185 potential CLABSI events which met the THAS definition by either the external reviewers or the hospital reviewers, 24 (13.0%) events were identified by only the external reviewers, and six (3.2%) were identified by only the hospital reviewers, with an agreement rate of 83.8%. Using external reviewers as the gold standard, the pooled mean sensitivity and positive predictive value of CLABSI reporting were 86.6% (155/179) and 96.3% (155/161), respectively. Among the 37 misclassification episodes, missed case findings were the most common reason for misclassification (N=16, 43.2%). Conclusions: The CLABSI data reported to the THAS system are generally reliable. This study showed the need for ongoing validation processes and quality improvement to maintain the accuracy and validity of the surveillance data.
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