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Antibiotic overuse in the primary health care setting: a secondary data analysis of standardised patient studies from India, China and Kenya

INTRODUCTION: Determining whether antibiotic prescriptions are inappropriate requires knowledge of patients’ underlying conditions. In low-income and middle-income countries (LMICs), where misdiagnoses are frequent, this is challenging. Additionally, such details are often unavailable for prescripti...

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Autores principales: Sulis, Giorgia, Daniels, Benjamin, Kwan, Ada, Gandra, Sumanth, Daftary, Amrita, Das, Jishnu, Pai, Madhukar
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BMJ Publishing Group 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7493125/
https://www.ncbi.nlm.nih.gov/pubmed/32938614
http://dx.doi.org/10.1136/bmjgh-2020-003393
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author Sulis, Giorgia
Daniels, Benjamin
Kwan, Ada
Gandra, Sumanth
Daftary, Amrita
Das, Jishnu
Pai, Madhukar
author_facet Sulis, Giorgia
Daniels, Benjamin
Kwan, Ada
Gandra, Sumanth
Daftary, Amrita
Das, Jishnu
Pai, Madhukar
author_sort Sulis, Giorgia
collection PubMed
description INTRODUCTION: Determining whether antibiotic prescriptions are inappropriate requires knowledge of patients’ underlying conditions. In low-income and middle-income countries (LMICs), where misdiagnoses are frequent, this is challenging. Additionally, such details are often unavailable for prescription audits. Recent studies using standardised patients (SPs) offer a unique opportunity to generate unbiased prevalence estimates of antibiotic overuse, as the research design involves patients with predefined conditions. METHODS: Secondary analyses of data from nine SP studies were performed to estimate the proportion of SP–provider interactions resulting in inappropriate antibiotic prescribing across primary care settings in three LMICs (China, India and Kenya). In all studies, SPs portrayed conditions for which antibiotics are unnecessary (watery diarrhoea, presumptive tuberculosis (TB), angina and asthma). We conducted descriptive analyses reporting overall prevalence of antibiotic overprescribing by healthcare sector, location, provider qualification and case. The WHO Access–Watch–Reserve framework was used to categorise antibiotics based on their potential for selecting resistance. As richer data were available from India, we examined factors associated with antibiotic overuse in that country through hierarchical Poisson models. RESULTS: Across health facilities, antibiotics were given inappropriately in 2392/4798 (49.9%, 95% CI 40.8% to 54.5%) interactions in India, 83/166 (50.0%, 95% CI 42.2% to 57.8%) in Kenya and 259/899 (28.8%, 95% CI 17.8% to 50.8%) in China. Prevalence ratios of antibiotic overuse in India were significantly lower in urban versus rural areas (adjusted prevalence ratio (aPR) 0.70, 95% CI 0.52 to 0.96) and higher for qualified versus non-qualified providers (aPR 1.55, 95% CI 1.42 to 1.70), and for presumptive TB cases versus other conditions (aPR 1.19, 95% CI 1.07 to 1.33). Access antibiotics were predominantly used in Kenya (85%), but Watch antibiotics (mainly quinolones and cephalosporins) were highly prescribed in India (47.6%) and China (32.9%). CONCLUSION: Good-quality SP data indicate alarmingly high levels of antibiotic overprescription for key conditions across primary care settings in India, China and Kenya, with broad-spectrum agents being excessively used in India and China.
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spelling pubmed-74931252020-09-24 Antibiotic overuse in the primary health care setting: a secondary data analysis of standardised patient studies from India, China and Kenya Sulis, Giorgia Daniels, Benjamin Kwan, Ada Gandra, Sumanth Daftary, Amrita Das, Jishnu Pai, Madhukar BMJ Glob Health Original Research INTRODUCTION: Determining whether antibiotic prescriptions are inappropriate requires knowledge of patients’ underlying conditions. In low-income and middle-income countries (LMICs), where misdiagnoses are frequent, this is challenging. Additionally, such details are often unavailable for prescription audits. Recent studies using standardised patients (SPs) offer a unique opportunity to generate unbiased prevalence estimates of antibiotic overuse, as the research design involves patients with predefined conditions. METHODS: Secondary analyses of data from nine SP studies were performed to estimate the proportion of SP–provider interactions resulting in inappropriate antibiotic prescribing across primary care settings in three LMICs (China, India and Kenya). In all studies, SPs portrayed conditions for which antibiotics are unnecessary (watery diarrhoea, presumptive tuberculosis (TB), angina and asthma). We conducted descriptive analyses reporting overall prevalence of antibiotic overprescribing by healthcare sector, location, provider qualification and case. The WHO Access–Watch–Reserve framework was used to categorise antibiotics based on their potential for selecting resistance. As richer data were available from India, we examined factors associated with antibiotic overuse in that country through hierarchical Poisson models. RESULTS: Across health facilities, antibiotics were given inappropriately in 2392/4798 (49.9%, 95% CI 40.8% to 54.5%) interactions in India, 83/166 (50.0%, 95% CI 42.2% to 57.8%) in Kenya and 259/899 (28.8%, 95% CI 17.8% to 50.8%) in China. Prevalence ratios of antibiotic overuse in India were significantly lower in urban versus rural areas (adjusted prevalence ratio (aPR) 0.70, 95% CI 0.52 to 0.96) and higher for qualified versus non-qualified providers (aPR 1.55, 95% CI 1.42 to 1.70), and for presumptive TB cases versus other conditions (aPR 1.19, 95% CI 1.07 to 1.33). Access antibiotics were predominantly used in Kenya (85%), but Watch antibiotics (mainly quinolones and cephalosporins) were highly prescribed in India (47.6%) and China (32.9%). CONCLUSION: Good-quality SP data indicate alarmingly high levels of antibiotic overprescription for key conditions across primary care settings in India, China and Kenya, with broad-spectrum agents being excessively used in India and China. BMJ Publishing Group 2020-09-15 /pmc/articles/PMC7493125/ /pubmed/32938614 http://dx.doi.org/10.1136/bmjgh-2020-003393 Text en © Author(s) (or their employer(s)) 2020. Re-use permitted under CC BY. Published by BMJ. https://creativecommons.org/licenses/by/4.0/ https://creativecommons.org/licenses/by/4.0/This is an open access article distributed in accordance with the Creative Commons Attribution 4.0 Unported (CC BY 4.0) license, which permits others to copy, redistribute, remix, transform and build upon this work for any purpose, provided the original work is properly cited, a link to the licence is given, and indication of whether changes were made. See: https://creativecommons.org/licenses/by/4.0/.
spellingShingle Original Research
Sulis, Giorgia
Daniels, Benjamin
Kwan, Ada
Gandra, Sumanth
Daftary, Amrita
Das, Jishnu
Pai, Madhukar
Antibiotic overuse in the primary health care setting: a secondary data analysis of standardised patient studies from India, China and Kenya
title Antibiotic overuse in the primary health care setting: a secondary data analysis of standardised patient studies from India, China and Kenya
title_full Antibiotic overuse in the primary health care setting: a secondary data analysis of standardised patient studies from India, China and Kenya
title_fullStr Antibiotic overuse in the primary health care setting: a secondary data analysis of standardised patient studies from India, China and Kenya
title_full_unstemmed Antibiotic overuse in the primary health care setting: a secondary data analysis of standardised patient studies from India, China and Kenya
title_short Antibiotic overuse in the primary health care setting: a secondary data analysis of standardised patient studies from India, China and Kenya
title_sort antibiotic overuse in the primary health care setting: a secondary data analysis of standardised patient studies from india, china and kenya
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7493125/
https://www.ncbi.nlm.nih.gov/pubmed/32938614
http://dx.doi.org/10.1136/bmjgh-2020-003393
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