Implementation of microbial whole-genome sequencing
For individual patient care, local outbreak recognition and national surveillance
Dates: | April 2012 - March 2015 |
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Funding: | Health Innovation Challenge Fund |
Principal Investigator: | Professor Derrick Crook, Oxford University Hospitals NHS Trust and NIHR Biomedical Research Centre, and Public Health England |
Information: | Sarah Wordsworth |
This study evaluates the use of whole-genome sequencing to sequence bacterial genomes in NHS microbiology laboratories. Unlike other genomic tests, in this clinical area it is the bugs (pathogens), rather than the patient’s DNA which are tested. Currently, very slow, labour-intensive methods are used to identify the cause of an infection and establish which treatments could be effective. The information provided by WGS could transform the way these laboratories work, helping clinicians to manage patients with suspected infections faster and more effectively.
The health economic component is assessing the cost-effectiveness of current methods for testing MRSA, C. difficile and E. coli against the use of WGS. The main outcome measures for the cost-effectiveness analysis includes new infections averted (through enhanced outbreak detection methods) and inappropriate antimicrobials avoided. The effectiveness data will be derived from a combination of primary data collection within the study, plus relevant literature and expert opinion. The costs of undertaking WGS compared to current testing methods will be estimated by performing a micro-costing of both processes in the Oxford laboratory. This will include the resources associated with staff time, equipment, reagents, ongoing training costs, laboratory, intensive care capacity to respond to outbreaks, resilience (e.g. to machine failure) and the costs of necessary backup systems. The costs of alternative antimicrobials will also be estimated. The main analysis will estimate average costs and effects on a per patient basis and from this the incremental cost-effectiveness ratios for the different testing approaches will be derived, producing an incremental cost per infection avoided and inappropriate antimicrobial avoided.