TY - JOUR T1 - Variation in hospital mortality in an Australian neonatal intensive care unit network JF - Archives of Disease in Childhood - Fetal and Neonatal Edition JO - Arch Dis Child Fetal Neonatal Ed SP - F331 LP - F336 DO - 10.1136/archdischild-2017-313222 VL - 103 IS - 4 AU - Mohamed E Abdel-Latif AU - Gen Nowak AU - Barbara Bajuk AU - Kathryn Glass AU - David Harley Y1 - 2018/07/01 UR - http://fn.bmj.com/content/103/4/F331.abstract N2 - Background Studying centre-to-centre (CTC) variation in mortality rates is important because inferences about quality of care can be made permitting changes in practice to improve outcomes. However, comparisons between hospitals can be misleading unless there is adjustment for population characteristics and severity of illness.Objective We sought to report the risk-adjusted CTC variation in mortality among preterm infants born <32 weeks and admitted to all eight tertiary neonatal intensive care units (NICUs) in the New South Wales and the Australian Capital Territory Neonatal Network (NICUS), Australia.Methods We analysed routinely collected prospective data for births between 2007 and 2014. Adjusted mortality rates for each NICU were produced using a multiple logistic regression model. Output from this model was used to construct funnel plots.Results A total of 7212 live born infants <32 weeks gestation were admitted consecutively to network NICUs during the study period. NICUs differed in their patient populations and severity of illness.The overall unadjusted hospital mortality rate for the network was 7.9% (n=572 deaths). This varied from 5.3% in hospital E to 10.4% in hospital C. Adjusted mortality rates showed little CTC variation. No hospital reached the +99.8% control limit level on adjusted funnel plots.Conclusion Characteristics of infants admitted to NICUs differ, and comparing unadjusted mortality rates should be avoided. Logistic regression-derived risk-adjusted mortality rates plotted on funnel plots provide a powerful visual graphical tool for presenting quality performance data. CTC variation is readily identified, permitting hospitals to appraise their practices and start timely intervention. ER -