Abstract

BackgroundDetecting 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.MethodsUsing 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.ResultsWe 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 optimally selected hospitals. Increasing the number of sentinel hospitals to 38 (teaching and general hospitals) reduces detection time by 43 days; however decreasing the number to seven sentinel hospitals (teaching hospitals) increases detection time substantially to 268 days.ConclusionsOur results show that the current surveillance system as it is used in Scotland is not optimal in detecting novel pathogens when compared to a gold standard. However, efficiency gains are possible by better choice of sentinel hospitals, or by increasing the number of hospitals involved in surveillance. Similar studies could be used elsewhere to inform the design and implementation of efficient national, hospital-based surveillance systems that achieve rapid detection of novel HCAIs for minimal effort.Electronic supplementary materialThe online version of this article (doi:10.1186/s12889-015-2172-9) contains supplementary material, which is available to authorized users.

Highlights

  • Detecting novel healthcare-associated infections (HCAI) as early as possible is an important public health priority

  • Examples of HCAIs causing concern are those caused by both meticillin-susceptible Staphylococcus aureus

  • In Scotland there is the Scottish Healthcare Associated Infection Programme supported by Health Protection Scotland (HPS) and the Scottish methicillin-resistant Staphylococcus aureus (MRSA) Reference Laboratory [9] which collectively gather data and monitor trends in the number of MRSA bacteraemias as well as antimicrobial resistance and virulence profiles

Read more

Summary

Introduction

Detecting novel healthcare-associated infections (HCAI) as early as possible is an important public health priority. There is currently no evidence base to guide the design of efficient and reliable surveillance systems. We address this issue in the context of a novel pathogen spreading primarily between hospitals through the movement of patients. HCAIs can spread rapidly throughout a network of hospitals [3, 4] Rapid intervention for such outbreaks is of major importance, firstly to keep the number of infected patients to a minimum and secondly because there are considerable costs associated with large disease outbreaks [5, 6]. There is not a good evidence base to guide the design of national surveillance programmes

Methods
Results
Conclusion
Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.