Prioritizing research areas for antibiotic stewardship programmes in hospitals: a behavioural perspective consensus paper
Bibliographic record
Abstract
SCOPE: Antibiotic stewardship programmes (ASPs) are necessary in hospitals to improve the judicious use of antibiotics. While ASPs require complex change of key behaviours on individual, team organization and policy levels, evidence from the behavioural sciences is underutilized in antibiotic stewardship studies across the world, including high-income countries (HICs). A consensus procedure was performed to propose research priority areas for optimizing effective implementation of ASPs in hospital settings using a behavioural perspective. METHODS: A workgroup for behavioural approaches to ASPs was convened in response to the fourth call for leading expert network proposals by the Joint Programming Initiative on Antimicrobial Resistance (JPIAMR). Eighteen clinical and academic specialists in antibiotic stewardship, implementation science and behaviour change from four HICs with publicly funded healthcare systems (e.g. Canada, Germany, Norway and the UK) met face-to-face to agree on broad research priority areas using a structured consensus method. Question addressed and recommendations: The consensus process assessing the ten identified research priority areas resulted in recommendations that need urgent scientific interest and funding to optimize effective implementation of ASPs for hospital inpatients in HICs with publicly funded healthcare systems. We suggest and detail behavioural science evidence-guided research efforts in the following areas: (a) comprehensively identifying barriers and facilitators to implementing ASPs and clinical recommendations intended to optimize antibiotic prescribing; (b) identifying actors ('who') and actions ('what needs to be done') of ASPs and clinical teams; (c) synthesizing available evidence to support future research and planning for ASPs; (d) specifying the activities in current ASPs with the purpose of defining a control group for comparison with new initiatives; (e) defining a balanced set of outcomes and measures to evaluate the effects of interventions focused on reducing unnecessary exposure to antibiotics; (f) conducting robust evaluations of ASPs with built-in process evaluations and fidelity assessments; (g) defining and designing ASPs; (h) establishing the evidence base for impact of ASPs on resistance; (i) investigating the role and impact of government and policy contexts on ASPs; and (j) understanding what matters to patients in ASPs in hospitals. CONCLUSIONS: Assessment, revisions and updates of our priority-setting exercise should be considered at intervals of 2 years. To propose research priority areas in low- and middle-income countries, the methodology reported here could be applied.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".