Abstract

Behaviour change is key to combating antimicrobial resistance. Antimicrobial stewardship (AMS) programmes promote and monitor judicious antibiotic use, but there is little consideration of behavioural and social influences when designing interventions. We outline a programme of research which aims to co-design AMS interventions across healthcare settings, by integrating data-science, evidence- synthesis, behavioural-science and user-centred design. The project includes three work-packages (WP): WP1 (Identifying patterns of prescribing): analysis of electronic health-records to identify prescribing patterns in care-homes, primary-care, and secondary-care. An online survey will investigate consulting/antibiotic-seeking behaviours in members of the public. WP2 (Barriers and enablers to prescribing in practice): Semi-structured interviews and observations of practice to identify barriers/enablers to prescribing, influences on antibiotic-seeking behaviour and the social/contextual factors underpinning prescribing. Systematic reviews of AMS interventions to identify the components of existing interventions associated with effectiveness. Design workshops to identify constraints influencing the form of the intervention. Interviews conducted with healthcare-professionals in community pharmacies, care-homes, primary-, and secondary-care and with members of the public. Topic guides and analysis based on the Theoretical Domains Framework. Observations conducted in care-homes, primary and secondary-care with analysis drawing on grounded theory. Systematic reviews of interventions in each setting will be conducted, and interventions described using the Behaviour Change Technique taxonomy v1. Design workshops in care-homes, primary-, and secondary care. WP3 (Co-production of interventions and dissemination). Findings will be integrated to identify opportunities for interventions, and assess whether existing interventions target influences on antibiotic use. Stakeholder panels will be assembled to co-design and refine interventions in each setting, applying the Affordability, Practicability, Effectiveness, Acceptability, Side-effects and Equity (APEASE) criteria to prioritise candidate interventions. Outputs will inform development of new AMS interventions and/or optimisation of existing interventions. We will also develop web-resources for stakeholders providing analyses of antibiotic prescribing patterns, prescribing behaviours, and evidence reviews.

Highlights

  • Since the 1940s, antibiotics have transformed our ability to treat bacterial infections

  • In England, public health efforts to tackle antimicrobial resistance (AMR) have led to declines in antibiotic use across healthcare settings, but rates of prescribing remain high compared to some other European countries (ESPAUR, 2018)

  • Information on self-management of infections in the community and patterns of health-seeking behaviours is lacking. We would expect these findings to be of particular interest to researchers, clinicians and policy-makers involved in the field of AMR, as well as to a wider-audience

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Summary

Introduction

Since the 1940s, antibiotics have transformed our ability to treat bacterial infections. In England, public health efforts to tackle AMR have led to declines in antibiotic use across healthcare settings, but rates of prescribing remain high compared to some other European countries (ESPAUR, 2018). The number of drug-resistant infections continues to rise (Cassini et al, 2019), highlighting the need for renewed efforts to improve the quality of antibiotic prescribing. Antibiotic stewardship, defined as “...an organisational or healthcare-system-wide approach to promoting and monitoring judicious use of antimicrobials to preserve their future effectiveness.” (NICE: 2015 p8) plays a critical role in this (DoH, 2013; WHO, 2015). A wide range of interventions have been found to improve antibiotic stewardship when applied across diverse healthcare settings (Davey et al, 2015; Hulscher & Prins, 2017). With apparently similar interventions producing very different results (Davey et al, 2017)

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