Details

Autor(en) / Beteiligte

• Kwak, Y.G
• Choi, J.Y
• Yoo, H.M
• Lee, S-O
• Kim, H.B
• Han, S.H
• Choi, H.J
• Kim, S.R
• Kim, T.H
• Chun, H.K
• Koo, H-S

Titel

Validation of the Korean National Healthcare-associated Infections Surveillance System (KONIS): an intensive care unit module report

Ist Teil von

• The Journal of hospital infection, 2017-08, Vol.96 (4), p.377-384

Ort / Verlag

England: Elsevier Ltd

Erscheinungsjahr

2017

Link zum Volltext

Quelle

MEDLINE

Beschreibungen/Notizen

• Summary Background National surveillance data should be validated to identify methodological problems within the surveillance programme and data quality issues. Aim To test the validity of healthcare-associated infection (HAI) rate data from the Korean National Healthcare-associated Infections Surveillance System (KONIS). Methods Records from intensive care units of 12 (14.8%) of 81 participating hospitals for January–March 2014 were examined. The validation team reviewed 406 medical records of 110 patients with 114 reported HAIs – including 34 urinary tract infections (UTIs), 57 bloodstream infections (BSIs) and 23 cases of pneumonia (PNEU) – and 296 patients with no reported HAIs during one-day visits conducted in August and September 2014. The reviewers' diagnosis of HAI was regarded as the reference standard; in ambiguous cases, the KONIS Steering Committee confirmed the diagnosis of HAI. Findings Sensitivity values for UTIs, BSIs and PNEU were 85.3%, 74.0% and 66.7%, and specificity values were 98.7%, 99.1% and 98.7%, respectively. Positive predictive values were 85.3%, 94.7% and 78.3%, and negative predictive values were 98.7%, 94.6% and 97.7%, respectively. Sensitivity for PNEU was lower than that for UTIs and BSIs. The hospitals participating in KONIS infrequently reported conditions that were not HAIs. Sensitivity for BSIs was lower in this study than in KONIS validation studies conducted in 2008 and 2010. Conclusions KONIS data are generally reliable; however, sensitivity for BSIs exhibited a decrease. This study shows the need for ongoing validation and continuous training of surveillance personnel to maintain the accuracy of surveillance data.