C Schröder1, M Behnke2, P Gastmeier2, F Schwab2, C Geffers2. 1. Institute of Hygiene and Environmental Medicine, Charité Berlin, Berlin, Germany; German National Reference Center for the Surveillance of Nosocomial Infections, Berlin, Germany. Electronic address: christin.schroeder@charite.de. 2. Institute of Hygiene and Environmental Medicine, Charité Berlin, Berlin, Germany; German National Reference Center for the Surveillance of Nosocomial Infections, Berlin, Germany.
Abstract
BACKGROUND: National surveillance systems depend on accurate and reproducible diagnosis of infections. AIM: To investigate the effect of accuracy of diagnosing healthcare-associated infections (HCAIs) on HCAI rates in a national healthcare-associated surveillance system. METHODS: Data from the validation process from the intensive care unit (ICU) surveillance component of the German Krankenhaus Infektions Surveillance System (KISS; Hospital Infection Surveillance System) were used to calculate the accuracy of diagnosing HCAI for each individual surveillance person (SP) responsible for surveillance of HCAI in the ICU of his or her hospital. Multivariate analyses were performed to identify factors that were attributed to surveillance accuracy. FINDINGS: A total of 189 SPs responsible for surveillance in 218 ICUs assessed 30 case vignettes. The chance of belonging to the group of SPs with high accuracy was increased by being a physician (odds ratio: 3.14; P = 0.02) and by being an external SP (odds ratio: 4.69; P ≤ 0.01). ICU HCAI rates depend on the sensitivity of the ICU's SP [incidence rate ratio (IRR): 1.28 (1.07, 1.53); P ≤ 0.01]. High sensitivity increases healthcare-associated urinary tract infection rates [IRR: 1.33 (1.02, 1.75); P = 0.03] and bloodstream infection rates [IRR: 1.33 (1.06, 1.68); P = 0.01]. High specificity was not a significant factor. CONCLUSION: In light of the link between sensitivity of diagnosing HCAI by case vignettes and the ICU HCAI rates, this validation method can be recommended for validation of other surveillance systems.
BACKGROUND: National surveillance systems depend on accurate and reproducible diagnosis of infections. AIM: To investigate the effect of accuracy of diagnosing healthcare-associated infections (HCAIs) on HCAI rates in a national healthcare-associated surveillance system. METHODS: Data from the validation process from the intensive care unit (ICU) surveillance component of the German Krankenhaus Infektions Surveillance System (KISS; Hospital Infection Surveillance System) were used to calculate the accuracy of diagnosing HCAI for each individual surveillance person (SP) responsible for surveillance of HCAI in the ICU of his or her hospital. Multivariate analyses were performed to identify factors that were attributed to surveillance accuracy. FINDINGS: A total of 189 SPs responsible for surveillance in 218 ICUs assessed 30 case vignettes. The chance of belonging to the group of SPs with high accuracy was increased by being a physician (odds ratio: 3.14; P = 0.02) and by being an external SP (odds ratio: 4.69; P ≤ 0.01). ICU HCAI rates depend on the sensitivity of the ICU's SP [incidence rate ratio (IRR): 1.28 (1.07, 1.53); P ≤ 0.01]. High sensitivity increases healthcare-associated urinary tract infection rates [IRR: 1.33 (1.02, 1.75); P = 0.03] and bloodstream infection rates [IRR: 1.33 (1.06, 1.68); P = 0.01]. High specificity was not a significant factor. CONCLUSION: In light of the link between sensitivity of diagnosing HCAI by case vignettes and the ICU HCAI rates, this validation method can be recommended for validation of other surveillance systems.
Authors: Philip L Russo; Adrian G Barnett; Allen C Cheng; Michael Richards; Nicholas Graves; Lisa Hall Journal: Antimicrob Resist Infect Control Date: 2015-07-19 Impact factor: 4.887