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Variability of Antibiotic Prescribing in a Large Healthcare Network Despite Adjusting for Patient-Mix: Reconsidering Targets for Improved Prescribing

BACKGROUND: In the outpatient setting, the majority of antibiotic prescriptions are for acute respiratory infections (ARIs), but most of these infections are viral and antibiotics are unnecessary. We analyzed provider-specific antibiotic prescribing in a group of outpatient clinics affiliated with a...

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Autores principales: Jung, Sophia, Sexton, Mary Elizabeth, Owens, Sallie, Spell, Nathan, Fridkin, Scott
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6386112/
https://www.ncbi.nlm.nih.gov/pubmed/30815500
http://dx.doi.org/10.1093/ofid/ofz018
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author Jung, Sophia
Sexton, Mary Elizabeth
Owens, Sallie
Spell, Nathan
Fridkin, Scott
author_facet Jung, Sophia
Sexton, Mary Elizabeth
Owens, Sallie
Spell, Nathan
Fridkin, Scott
author_sort Jung, Sophia
collection PubMed
description BACKGROUND: In the outpatient setting, the majority of antibiotic prescriptions are for acute respiratory infections (ARIs), but most of these infections are viral and antibiotics are unnecessary. We analyzed provider-specific antibiotic prescribing in a group of outpatient clinics affiliated with an academic medical center to inform future interventions to minimize unnecessary antibiotic use. METHODS: We conducted a cross-sectional study of patients who presented with an ARI to any of 15 The Emory Clinic (TEC) primary care clinic sites between October 2015 and September 2017. We performed multivariable logistic regression analysis to examine the impact of patient, provider, and clinic characteristics on antibiotic prescribing. We also compared provider-specific prescribing rates within and between clinic sites. RESULTS: A total of 53.4% of the 9600 patient encounters with a diagnosis of ARI resulted in an antibiotic prescription. The odds of an encounter resulting in an antibiotic prescription were independently associated with patient characteristics of white race (adjusted odds ratio [aOR] = 1.59; 95% confidence interval [CI], 1.47–1.73), older age (aOR = 1.32, 95% CI = 1.20–1.46 for patients 51 to 64 years; aOR = 1.32, 95% CI = 1.20–1.46 for patients ≥65 years), and comorbid condition presence (aOR = 1.19; 95% CI, 1.09–1.30). Of the 109 providers, 13 (12%) had a rate significantly higher than predicted by modeling. CONCLUSIONS: Antibiotic prescribing for ARIs within TEC outpatient settings is higher than expected based on prescribing guidelines, with substantial variation in prescribing rates by site and provider. These data lay the foundation for quality improvement interventions to reduce unnecessary antibiotic prescribing.
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spelling pubmed-63861122019-02-27 Variability of Antibiotic Prescribing in a Large Healthcare Network Despite Adjusting for Patient-Mix: Reconsidering Targets for Improved Prescribing Jung, Sophia Sexton, Mary Elizabeth Owens, Sallie Spell, Nathan Fridkin, Scott Open Forum Infect Dis Major Article BACKGROUND: In the outpatient setting, the majority of antibiotic prescriptions are for acute respiratory infections (ARIs), but most of these infections are viral and antibiotics are unnecessary. We analyzed provider-specific antibiotic prescribing in a group of outpatient clinics affiliated with an academic medical center to inform future interventions to minimize unnecessary antibiotic use. METHODS: We conducted a cross-sectional study of patients who presented with an ARI to any of 15 The Emory Clinic (TEC) primary care clinic sites between October 2015 and September 2017. We performed multivariable logistic regression analysis to examine the impact of patient, provider, and clinic characteristics on antibiotic prescribing. We also compared provider-specific prescribing rates within and between clinic sites. RESULTS: A total of 53.4% of the 9600 patient encounters with a diagnosis of ARI resulted in an antibiotic prescription. The odds of an encounter resulting in an antibiotic prescription were independently associated with patient characteristics of white race (adjusted odds ratio [aOR] = 1.59; 95% confidence interval [CI], 1.47–1.73), older age (aOR = 1.32, 95% CI = 1.20–1.46 for patients 51 to 64 years; aOR = 1.32, 95% CI = 1.20–1.46 for patients ≥65 years), and comorbid condition presence (aOR = 1.19; 95% CI, 1.09–1.30). Of the 109 providers, 13 (12%) had a rate significantly higher than predicted by modeling. CONCLUSIONS: Antibiotic prescribing for ARIs within TEC outpatient settings is higher than expected based on prescribing guidelines, with substantial variation in prescribing rates by site and provider. These data lay the foundation for quality improvement interventions to reduce unnecessary antibiotic prescribing. Oxford University Press 2019-01-18 /pmc/articles/PMC6386112/ /pubmed/30815500 http://dx.doi.org/10.1093/ofid/ofz018 Text en © The Author(s) 2019. Published by Oxford University Press on behalf of Infectious Diseases Society of America. http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs licence (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial reproduction and distribution of the work, in any medium, provided the original work is not altered or transformed in any way, and that the work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
spellingShingle Major Article
Jung, Sophia
Sexton, Mary Elizabeth
Owens, Sallie
Spell, Nathan
Fridkin, Scott
Variability of Antibiotic Prescribing in a Large Healthcare Network Despite Adjusting for Patient-Mix: Reconsidering Targets for Improved Prescribing
title Variability of Antibiotic Prescribing in a Large Healthcare Network Despite Adjusting for Patient-Mix: Reconsidering Targets for Improved Prescribing
title_full Variability of Antibiotic Prescribing in a Large Healthcare Network Despite Adjusting for Patient-Mix: Reconsidering Targets for Improved Prescribing
title_fullStr Variability of Antibiotic Prescribing in a Large Healthcare Network Despite Adjusting for Patient-Mix: Reconsidering Targets for Improved Prescribing
title_full_unstemmed Variability of Antibiotic Prescribing in a Large Healthcare Network Despite Adjusting for Patient-Mix: Reconsidering Targets for Improved Prescribing
title_short Variability of Antibiotic Prescribing in a Large Healthcare Network Despite Adjusting for Patient-Mix: Reconsidering Targets for Improved Prescribing
title_sort variability of antibiotic prescribing in a large healthcare network despite adjusting for patient-mix: reconsidering targets for improved prescribing
topic Major Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6386112/
https://www.ncbi.nlm.nih.gov/pubmed/30815500
http://dx.doi.org/10.1093/ofid/ofz018
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