The drivers of antimicrobial use across institutions, stakeholders and economic settings: a paradigm shift is required for effective optimization

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.