Efficient national surveillance for health-care-associated infections

BMC Public Health
B A D van BunnikMark E J Woolhouse

Abstract

Detecting novel healthcare-associated infections (HCAI) as early as possible is an important public health priority. However, there is currently no evidence base to guide the design of efficient and reliable surveillance systems. Here we address this issue in the context of a novel pathogen spreading primarily between hospitals through the movement of patients. Using a mathematical modelling approach we compare the current surveillance system for a HCAI that spreads primarily between hospitals due to patient movements as it is implemented in Scotland with a gold standard to determine if the current system is maximally efficient or whether it would be beneficial to alter the number and choice of hospitals in which to concentrate surveillance effort. We validated our model by demonstrating that it accurately predicts the risk of meticillin-resistant Staphylococcus aureus bacteraemia cases in Scotland. Using the 29 (out of 182) sentinel hospitals that currently contribute most of the national surveillance effort results in an average detection time of 117 days. A reduction in detection time to 87 days is possible by optimal selection of 29 hospitals. Alternatively, the same detection time (117 days) can be achieved using just 22 o...Continue Reading

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Citations

Oct 13, 2017·Journal of the American Medical Informatics Association : JAMIA·Jason Cory Brunson, Reinhard C Laubenbacher
Aug 5, 2017·PLoS Computational Biology·Tjibbe DonkerJulie V Robotham

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