Influence of an independent quarterly audit on publicly reported vancomycin-resistant enterocococi bacteremia data in Ontario, Canada

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HighlightsOver 25% of VRE bacteremias were incorrectly reported in public reporting.Quarterly audits were linked to reduced reporting errors among Ontario's hospitals.Independent and routine audits of VRE bacteremia are associated with improved data quality.Background:All Ontario hospitals are mandated to self-report vancomycin-resistant enterocococi (VRE) bacteremias to Ontario's Ministry of Health and Long-term Care for public reporting purposes. Independent quarterly audits of publicly reported VRE bacteremias between September 2013 and June 2015 were carried out by Public Health Ontario. VRE bacteremia case-reporting errors between January 2009 and August 2013 were identified by a single retrospective audit.Methods:Employing a quasiexperimental pre–post study design, the relative risk of VRE bacteremia reporting errors before and after quarterly audits were modeled using Poisson regression adjusting for hospital type, case counts reported to the Ministry of Health and Long-term Care, and autocorrelation via generalized estimating equation.Results:Overall, 24.5% (126 out of 514) of VRE bacteremias were reported in error; 114 out of 367 (31%) VRE bacteremias reported before quarterly audits and 12 out of 147 (8.1%) reported after audits were found to be incorrect. In adjusted analysis, quarterly audits of VRE bacteremias were associated with significant reductions in reporting errors when compared with before quarterly auditing (relative risk, 0.17; 95% confidence interval, 0.05-0.63). Risk of reporting errors among community hospitals were greater than acute teaching hospitals of the region (relative risk, 4.39; 95% CI, 3.07-5.70).Conclusions:This study found independent quarterly audits of publicly reported VRE bacteremias to be associated with significant reductions in reporting errors. Public reporting systems should consider adopting routine data audits and hospital-targeted training to improve data accuracy.

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