G88 Monitoring of Healthcare-Associated Infection Outbreaks in Neonatal Units in England. (4th June 2013) - Edelstein, M; Kortsalioudaki, C; Johnson, A; Hope, R; Chickowska, A; Sharland, M
Abstract : Aims: Outbreaks of healthcare-associated infection (HCAI) in neonatal units (NNUs) have a significant burden of morbidity and mortality and cause substantial disruption and cost to neonatal networks. The number of NNU HCAI clusters in 2011 in England, their size and causative organisms, were estimated using currently available surveillance tools. Methods: Data derived from voluntary laboratory reporting (LabBase 2), national reference laboratories and a Health Protection Agency outbreak reporting tool (HPZone) were searched to identify potential NNU HCAI clusters. The analysis was limited to the most likely causative organisms ( S. aureus, Enterobacter spp., E. coli, Acinetobacter spp., Klebsiella s pp., Pseudomonas spp., Serratia spp.) . Clusters were defined as: (i) any neonatal cluster or outbreak reported in HPZone; (ii) laboratory reports of at least 2 isolates originating from the same hospital and sharing the same VNTR or strain type, with at least one case below the age of 28 days, and with a maximum of 14 days between two cases, and (iii) 2 or more reports of the same infection in neonates in the same hospital in a 14 day period in LabBase. Cross linkage of the 3 data sources was then attempted. Results: 116 neonatal clusters including both colonisation and invasive disease were identified, involving at least 666 neonates. 43.4% of the clusters were MRSA, followed by MSSA (26%), E.coli (13%), Enterobacter (12%), and Pseudomonas (10%). There were on average 9.2 neonatal clusters per month (range 0–14). The median number of babies per cluster was 3 (range 2–80). When only bacteraemia samples were considered, E.coli was the most common organism accounting for 57% of clusters. The study likely underestimates the number of clusters due to a lack of standardised reporting. It was not always possible to fully characterise the clusters as formal outbreaks due to data limitations. Conclusion: This analysis identified a high number of HCAI clusters in English NNUs. A standardised approach to the definition, reporting, management and surveillance of NNU HCAI outbreaks is required to enable reliable outbreak detection and appropriate action.