J Broom1,2, A Broom3, E Kirby3. 1. Sunshine Coast University Hospital, Birtinya, QLD, Australia. 2. University of Queensland, Brisbane, QLD, Australia. 3. Practical Justice Initiative, Centre for Social Research in Health, University of New South Wales, Sydney, NSW, Australia.
Abstract
OBJECTIVES: Significant antimicrobial overuse persists worldwide, despite overwhelming evidence of antimicrobial resistance and knowledge that optimization of antimicrobial use will slow the development of resistance. It is critical to understand why this occurs. This study aims to consider the social influences on antimicrobial use within hospitals in Australia, via an in-depth, multisite analysis. METHODS: We used a qualitative multisite design, involving 222 individual semi-structured interviews and thematic analysis. Participants (85 doctors, 79 nurses, 31 pharmacists and 27 hospital managers) were recruited from five hospitals in Australia, including four public hospitals (two metropolitan, one regional and one remote) and one private hospital. RESULTS: Analysis of the interviews identified social relationships and institutional structures that may have a strong influence on antimicrobial use, which must be addressed concurrently. (i) Social relationships that exist across settings: these include the influence of personal risk, hierarchies, inter- and intraprofessional dynamics and sense of futility in making a difference long term in relation to antimicrobial resistance. (ii) Institutional structures that offer context-specific influences: these include patient population factors (including socioeconomic factors, geographical isolation and local infection patterns), proximity and resource issues. CONCLUSIONS: The success of antimicrobial optimization rests on adequate awareness and incorporation of multilevel influences. Analysis of the problem has tended to emphasize individual 'behaviour improvement' in prescribing rather than incorporating the problem of overuse as inherently multidimensional and necessarily incorporating personal, interpersonal and institutional variables. A paradigm shift is urgently needed to incorporate these critical factors in antimicrobial optimization strategies.
OBJECTIVES: Significant antimicrobial overuse persists worldwide, despite overwhelming evidence of antimicrobial resistance and knowledge that optimization of antimicrobial use will slow the development of resistance. It is critical to understand why this occurs. This study aims to consider the social influences on antimicrobial use within hospitals in Australia, via an in-depth, multisite analysis. METHODS: We used a qualitative multisite design, involving 222 individual semi-structured interviews and thematic analysis. Participants (85 doctors, 79 nurses, 31 pharmacists and 27 hospital managers) were recruited from five hospitals in Australia, including four public hospitals (two metropolitan, one regional and one remote) and one private hospital. RESULTS: Analysis of the interviews identified social relationships and institutional structures that may have a strong influence on antimicrobial use, which must be addressed concurrently. (i) Social relationships that exist across settings: these include the influence of personal risk, hierarchies, inter- and intraprofessional dynamics and sense of futility in making a difference long term in relation to antimicrobial resistance. (ii) Institutional structures that offer context-specific influences: these include patient population factors (including socioeconomic factors, geographical isolation and local infection patterns), proximity and resource issues. CONCLUSIONS: The success of antimicrobial optimization rests on adequate awareness and incorporation of multilevel influences. Analysis of the problem has tended to emphasize individual 'behaviour improvement' in prescribing rather than incorporating the problem of overuse as inherently multidimensional and necessarily incorporating personal, interpersonal and institutional variables. A paradigm shift is urgently needed to incorporate these critical factors in antimicrobial optimization strategies.
Authors: Carolyn Tarrant; Andrew M Colman; David R Jenkins; Edmund Chattoe-Brown; Nelun Perera; Shaheen Mehtar; W M I Dilini Nakkawita; Michele Bolscher; Eva M Krockow Journal: Antibiotics (Basel) Date: 2021-01-19
Authors: Justin Dixon; Eleanor Elizabeth MacPherson; Susan Nayiga; Salome Manyau; Christine Nabirye; Miriam Kayendeke; Esnart Sanudi; Alex Nkaombe; Portia Mareke; Kenny Sitole; Coll de Lima Hutchison; John Bradley; Shunmay Yeung; Rashida Abbas Ferrand; Sham Lal; Chrissy Roberts; Edward Green; Laurie Denyer Willis; Sarah G Staedke; Clare I R Chandler Journal: BMJ Glob Health Date: 2021-11
Authors: Hazel Parker; Julia Frost; Jo Day; Rob Bethune; Anu Kajamaa; Kieran Hand; Sophie Robinson; Karen Mattick Journal: PLoS One Date: 2022-07-20 Impact factor: 3.752
Authors: Emma Kirby; Alex Broom; Kristen Overton; Katherine Kenny; Jeffrey J Post; Jennifer Broom Journal: BMJ Open Date: 2020-10-29 Impact factor: 2.692