Homogeneity of antimicrobial policy, yet heterogeneity of antimicrobial resistance: antimicrobial non-susceptibility among 108,717 clinical isolates from primary, secondary and tertiary care patients in London

Abstract

Objectives: We examined the 4 year trend in antimicrobial susceptibilities and prescribing across levels of care at two London teaching hospitals and their multisite renal unit, and for the surrounding community.

Methods: Laboratory and pharmacy information management systems were interrogated, with antimicrobial use and susceptibilities analysed between hospitals, within hospitals and over time.

Results: A total of 108,717 isolates from 71,687 patients were identified, with significant differences (at P < 0.05) in antimicrobial susceptibility between and within hospitals. Across the 4 years, rates of ESBL-/AmpC-producing Enterobacteriaceae ranged from 6.4% to 10.7% among community isolates, 17.8% to 26.9% at ward level and 25.2% to 52.5% in critical care. Significant variations were also demonstrated in glycopeptide-resistant enterococci (ward level 6.2%-17.4%; critical care 21.9%-56.3%), MRSA (ward level 18.5%-38.2%; critical care 12.5%-47.9%) and carbapenem-resistant Pseudomonas spp. (ward level 8.3%-16.9%; critical care 19.9%-53.7%). Few instances of persistently higher resistance were seen between the hospitals in equivalent cohorts, despite persistently higher antimicrobial use in Hospital 1 than Hospital 2. We found significant fluctuations in non-susceptibility year on year across the cohorts, but with few persistent trends.

Conclusions: The marked heterogeneity of antimicrobial susceptibilities between hospitals, within hospitals and over time demands detailed, standardized surveillance and appropriate benchmarking to identify possible drivers and effective interventions. Homogeneous antimicrobial policies are unlikely to continue to be suitable as individual hospitals join hospital networks, and policies should be tailored to local resistance rates, at least at the hospital level, and possibly with finer resolution, particularly for critical care.

Keywords: antibiograms; antimicrobial stewardship; healthcare-associated infections; multidrug-resistant organisms.

Figure 1.

(a) Proportion of Enterobacteriaceae from clinical samples displaying ESBL/AmpC resistance phenotypes among 55 600 isolates from primary, secondary and tertiary care patients in West London, 2009–13. Error bars indicate 95% CIs calculated by Wilson's method with continuity correction. (b) Proportion of Enterobacteriaceae from clinical samples resistant to ciprofloxacin among 55 600 isolates from primary, secondary and tertiary care patients in West London, 2009–13. Error bars indicate 95% CIs calculated by Wilson's method with continuity correction.

Figure 2.

(a) Proportion of Pseudomonas spp. from clinical samples displaying ciprofloxacin non-susceptibility among 12 616 isolates from primary, secondary and tertiary care patients in West London, 2009–13. Error bars indicate 95% CIs calculated by Wilson's method with continuity correction. (b) Proportion of Pseudomonas spp. from clinical samples displaying piperacillin/tazobactam non-susceptibility among 12 616 isolates from primary, secondary and tertiary care patients in West London, 2009–13. Error bars indicate 95% CIs calculated by Wilson's method with continuity correction. (c) Proportion of Pseudomonas spp. from clinical samples displaying meropenem non-susceptibility among 12 616 isolates from primary, secondary and tertiary care patients in West London, 2009–13. Error bars indicate 95% CIs calculated by Wilson's method with continuity correction.

Figure 2.

(a) Proportion of Pseudomonas spp. from clinical samples displaying ciprofloxacin non-susceptibility among 12 616 isolates from primary, secondary and tertiary care patients in West London, 2009–13. Error bars indicate 95% CIs calculated by Wilson's method with continuity correction. (b) Proportion of Pseudomonas spp. from clinical samples displaying piperacillin/tazobactam non-susceptibility among 12 616 isolates from primary, secondary and tertiary care patients in West London, 2009–13. Error bars indicate 95% CIs calculated by Wilson's method with continuity correction. (c) Proportion of Pseudomonas spp. from clinical samples displaying meropenem non-susceptibility among 12 616 isolates from primary, secondary and tertiary care patients in West London, 2009–13. Error bars indicate 95% CIs calculated by Wilson's method with continuity correction.

Figure 3.

(a) Proportion of enterococci from clinical samples displaying glycopeptide non-susceptibility among 13 643 isolates from primary, secondary and tertiary care patients in West London, 2009–13. Error bars indicate 95% CIs calculated by Wilson's method with continuity correction. (b) Proportion of enterococci from clinical samples displaying amoxicillin non-susceptibility among 13 643 isolates from primary, secondary and tertiary care patients in West London, 2009–13. Error bars indicate 95% CIs calculated by Wilson's method with continuity correction.

Figure 4.

Proportion of S. aureus from clinical samples displaying methicillin non-susceptibility among 26 858 isolates from primary, secondary and tertiary care patients in West London, 2009–13. Error bars indicate 95% CIs calculated by Wilson's method with continuity correction.