OBJECTIVES: Using a prospective interrupted time series design, our goal was to determine whether a change in urine antibiotic susceptibility reporting from co-amoxiclav to cefalexin to community clinicians served by Southmead General Hospital led to a change in antibiotic prescribing. METHODS: We used longitudinal data on antibiotic prescribing using a clinician questionnaire to identify prescribing for urinary tract infections (UTIs) when a urine specimen was submitted to microbiology; MIQUEST computer search in general practices for prescribing for all UTIs in the community; and Prescribing Analysis and Cost (PACT) data to determine antibiotic prescribing for all infections. RESULTS: Cefalexin and cephalosporin prescribing increased when cefalexin was reported and co-amoxiclav prescribing decreased when co-amoxiclav was not reported by the laboratory. This was seen for episodes of UTI in which a general practitioner (GP) sent a specimen as determined with: the questionnaire results (9-fold rise in cephalosporins, 70% fall in co-amoxiclav); episodes of UTI identified by MIQUEST searches in the practice (50% increase in cefalexin, 25% reduction in co-amoxiclav); and overall antibiotic prescribing in the practice determined with PACT data (20% increase in cefalexin, 8% reduction in co-amoxiclav). MIQUEST data indicated that prescribing reverted to pre-intervention levels once the change in antibiotic reporting had stopped. CONCLUSIONS: Our data provide more evidence that changing laboratory antibiotic susceptibility reporting has a direct effect on antibiotic prescribing by GPs. Our data indicate that much of the change in prescribing was attributable to the use of cefalexin and co-amoxiclav for persistent or recurrent infections. Microbiology laboratories can influence antibiotic use by selectively reporting antibiotics they would prefer GPs to prescribe.
OBJECTIVES: Using a prospective interrupted time series design, our goal was to determine whether a change in urine antibiotic susceptibility reporting from co-amoxiclav to cefalexin to community clinicians served by Southmead General Hospital led to a change in antibiotic prescribing. METHODS: We used longitudinal data on antibiotic prescribing using a clinician questionnaire to identify prescribing for urinary tract infections (UTIs) when a urine specimen was submitted to microbiology; MIQUEST computer search in general practices for prescribing for all UTIs in the community; and Prescribing Analysis and Cost (PACT) data to determine antibiotic prescribing for all infections. RESULTS:Cefalexin and cephalosporin prescribing increased when cefalexin was reported and co-amoxiclav prescribing decreased when co-amoxiclav was not reported by the laboratory. This was seen for episodes of UTI in which a general practitioner (GP) sent a specimen as determined with: the questionnaire results (9-fold rise in cephalosporins, 70% fall in co-amoxiclav); episodes of UTI identified by MIQUEST searches in the practice (50% increase in cefalexin, 25% reduction in co-amoxiclav); and overall antibiotic prescribing in the practice determined with PACT data (20% increase in cefalexin, 8% reduction in co-amoxiclav). MIQUEST data indicated that prescribing reverted to pre-intervention levels once the change in antibiotic reporting had stopped. CONCLUSIONS: Our data provide more evidence that changing laboratory antibiotic susceptibility reporting has a direct effect on antibiotic prescribing by GPs. Our data indicate that much of the change in prescribing was attributable to the use of cefalexin and co-amoxiclav for persistent or recurrent infections. Microbiology laboratories can influence antibiotic use by selectively reporting antibiotics they would prefer GPs to prescribe.
Authors: Tamar F Barlam; Sara E Cosgrove; Lilian M Abbo; Conan MacDougall; Audrey N Schuetz; Edward J Septimus; Arjun Srinivasan; Timothy H Dellit; Yngve T Falck-Ytter; Neil O Fishman; Cindy W Hamilton; Timothy C Jenkins; Pamela A Lipsett; Preeti N Malani; Larissa S May; Gregory J Moran; Melinda M Neuhauser; Jason G Newland; Christopher A Ohl; Matthew H Samore; Susan K Seo; Kavita K Trivedi Journal: Clin Infect Dis Date: 2016-04-13 Impact factor: 9.079
Authors: K de With; F Allerberger; S Amann; P Apfalter; H-R Brodt; T Eckmanns; M Fellhauer; H K Geiss; O Janata; R Krause; S Lemmen; E Meyer; H Mittermayer; U Porsche; E Presterl; S Reuter; B Sinha; R Strauß; A Wechsler-Fördös; C Wenisch; W V Kern Journal: Infection Date: 2016-06 Impact factor: 3.553