Sustainability of antimicrobial stewardship programs in Australian rural hospitals: a qualitative study*
Bibliographic record
Abstract
Objective The aim of this study was to explore the features of sustainable antimicrobial stewardship (AMS) programs in Australian rural hospitals and develop recommendations on incorporating these features into rural hospitals' AMS programs. Methods Lead AMS clinicians with knowledge of at least one AMS program sustained for >2 years in a health service in rural Australia were recruited to the study. A series of interviews was conducted and the transcripts analysed thematically using a framework method. Results Fifteen participants from various professional disciplines were interviewed. Key features that positively affected the sustainability of AMS programs in rural hospitals included a hospital executive who provided strong governance and accountability, dedicated resources, passionate local champions, area-wide arrangements and adaptability to engage in new partnerships. Challenges to building AMS programs with these features were identified, particularly in engaging hospital executive to allocate AMS resources, managing the burn out of passionate champions and formalising network arrangements. Conclusions Strategies to increase the sustainability of AMS programs in rural hospitals include using accreditation as a mechanism to drive direct resource allocation, explicit staffing recommendations for rural hospitals, greater support to develop formal network arrangements and a framework for integrated AMS programs across primary, aged and acute care. What is known about the topic? AMS programs facilitate the responsible use of antimicrobials. Implementation challenges have been identified for rural hospitals, but the sustainability of AMS programs has not been explored. What does this paper add? Factors that positively affected the sustainability of AMS programs in rural hospitals were a hospital executive that provided strong governance and accountability, dedicated resources, network or area-wide arrangements and adaptability. Challenges to building AMS programs with these features were identified. What are the implications for practitioners? Recommended actions to boost the sustainability of AMS programs in rural hospitals are required. These include using accreditation as a mechanism to drive direct resource allocation, explicit staffing recommendations for rural hospitals, greater support to develop network arrangements and support to create integrated AMS programs across acute, aged and primary care.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".