Background

The global rise in antimicrobial resistance (AMR) is one of the major public health threats, with a disproportionate impact in low- and middle-income countries. The overuse and misuse of antimicrobial agents are one of the key drivers of emerging AMR. In response to this crisis, the WHO has launched a global action plan, including strategies for surveillance and mitigation of antimicrobial overuse.

Antimicrobial stewardship programs (ASP) provide an integrated approach to optimising antibiotic use and reducing drug-resistant infections associated with poor patient outcomes and higher costs.

The systematic collection of data on antimicrobial use (AMU) as the primary driver of AMR is vital for understanding the emergence of AMR. However, identifying reliable estimates for AMU is exceptionally challenging, and antibiotic practices may vary hugely between health care professionals, disciplines, departments, and hospitals. Furthermore, several complex factors, ranging from individual characteristics to broader economic constraints, cultural norms, social frameworks, healthcare provision and even political structures, can influence how antibiotics are used.

Understanding the cultural, behavioural and contextual factors driving antimicrobial prescribing practices in hospitals is critical to identifying the most locally suitable strategies to achieve effective ASP.

Indonesia, a populous (274 million) and diverse low- and middle-income country (LMIC), is potentially an AMR hotspot due to persistently high infectious disease burdens, coupled with liberal antibiotic practices and fragile health systems. The national government has included ASP in the National Action Plan for AMR and has made hospital accreditation conditional on implementing ASP. Yet, data on antimicrobial use are scarce and fragmented.

To comprehensively understand the problem and contextualise the AMU data, we propose a mixed-method design, combining quantitative measures of observed use (Probability Proportional to Size, hospital ASP checklist, prescriber Knowledge, Attitude and Practice survey) and qualitative approaches of reported experiences (interviews and ethnographic observations of prescribers). Triangulation of all data will allow maximum contextualisation and interpretation of data to create institutional awareness about AMU/AMR and will be instrumental in planning and supporting context-specific ASP interventions.

Aims

Three objectives of the study are:

1. To assess antibiotic use and prescribing patterns in Indonesian hospitals. The outcome measures are quantitative measures of antibiotic use (i.e., rate, antibiotic type, diagnosis and indication), quality indicators (e.g., guideline compliance, documentation of indication), and operational measures (e.g., time and resources);
2. To assess the knowledge, attitudes, practices and perceptions of antimicrobial prescribers in Indonesian hospitals on AMR, AMU, and ASP. The outcome measures are quantitative measures of knowledge, attitudes, and practices;
3. To explore the drivers of antibiotic use and dynamics in ASP in Indonesian hospitals. Outcome indicators are social constructs of antibiotic use and ASP implementation.

Study Design

This observational study adopts a mixed-method design, combining quantitative (observed use) and qualitative (reported experience) measures to assess antimicrobial use, prescribing practices and ASP implementation status in hospitals.

Methods of data collection are AMU survey; knowledge, attitudes, practices and perceptions survey; ASP survey; semi-structured interviews, and observation.