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Title: Rapid infection diagnostics in the context of augmented care : investigating their role in antimicrobial prescribing and bacterial resistance
Author: Moore, Luke Stephen Prockter
ISNI:       0000 0004 6496 0457
Awarding Body: Imperial College London
Current Institution: Imperial College London
Date of Award: 2016
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Introduction: Augmented care is a potentially significant reservoir of antimicrobial resistance (AMR). In the context of augmented care, this thesis investigates AMR variation and its drivers, barriers to optimising antimicrobial use, and the role of rapid infection-related diagnostics in addressing this. Methods: Mixed methods were used. AMR and antimicrobial consumption were quantitatively analysed, and driving factors explored using (i) statistical algorithms and (ii) thematic analysis of semi-structured interviews. As a case study, the role of rapid microbiology diagnostics was investigated with interrupted time series analysis of introduction of matrix-assisted laser desorption/ionisation time-of-flight (MALDI-ToF). The added value of computerised decision support was then assessed. Results: Analysis of 174,434 isolates demonstrated significant AMR variation between and within hospitals, with an excess in augmented care. Multiple ‘mini-outbreaks’ partly account for this, as does variation in antimicrobial consumption. Communication, knowledge, and personalisation of prescribing significantly influence the latter. Microbiology results are suboptimally utilised in these three areas. MALDI-ToF introduction, as a case study of a rapid microbiology diagnostic, significantly improved bacterial identification, but did not alter antimicrobial consumption. A role in surveillance is apparent, through identifying and investigating outbreaks, and in infection control, through carbapenemase detection. A computerised decision support system, derived from analysis of augmented care antimicrobial prescribing, facilitates wider impact from such rapid microbiology diagnostics. Conclusion: Augmented care areas have high, yet heterogeneous, levels of AMR, in part due to previously undetected outbreaks, and in part from variation in prescribing. Lost opportunities in communication, personalisation, and knowledge-holding influence the latter. Increasing the rapidity and specificity of microbial identification plays only a limited role in antimicrobial stewardship, but wider roles in surveillance and infection control will further impact AMR in augmented care. Decision support systems add further value, facilitating integration of clinical data, and shaping empiric antimicrobial choice where results are not available.
Supervisor: Holmes, Alison ; Donaldson, Hugo Sponsor: National Institute for Health Research
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral