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Internal Validation Process of Health Care-associated Infections (HAI) Data in a Group of Private Hospitals from Brazil

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      Background

      The primary goal of health care-associated infections (HAI) surveillance is to identify and measure the progress towards achieving the lowest number of infections. Assessing the accuracy of reporting data using independent validation is critical to this goal. In 2018, with a perspective of strengthening the patient's quality and safety strategies, one group of 21 general private hospitals in Brazil were updated the system of reporting data of HAIs including central line-associated bloodstream infections (CLABSI), catheter-associated urinary tract infections (CAUTI), and ventilator-associated pneumonia (PAV). These data began to be manage by a corporate infection control team. Aim: to test the accuracy of HAI rate, notified by a group of private hospitals in Brazil.

      Methods

      Based on NHSN diagnostic criteria HAIs, all infections notified in 21 hospitals from five different states in Brazil was validate by four Infection Control Preventionists (corporative team). The validation process included a systematic retrospective chart review associated with the analysis of positive cultures over a period of five months (August to December 2018).

      Results

      1357 cultures was evaluate of which 1314 (97%) met the NHSN definition for HAI. The HAI compliance rate separated by topography was: CLABSI 96%; CAUTI: 86% and PAV: 96%. Components of the case definition that were a source of misinterpretation included the following: CLABSI – misinterpretation of NHSN criteria between primary and secondary bacteremia, and differentiation regarding laboratory-confirmed bloodstream criteria 1 (recognized pathogen) and criteria 2 (skin contaminant); PAV - pneumonia cases notified only by clinical and non-epidemiological definition; CAUTI – reports of asymptomatic bacteriuria.

      Conclusions

      The data of the hospitals studied are generally reliable. However, this study shows the need for systematic validation process and continuous training of the infection control preventionists to maintain the accuracy, transparency, safe and comparability of surveillance data.
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