1232. Incorporation of Theory to Develop and Implement a Multi-Faceted Antimicrobial Stewardship Intervention for Hospitalized Adults with Bacteriuria
Bibliographic record
Abstract
Abstract Background Inappropriate treatment of bacteriuria is commonly reported. While evidence to support antimicrobial stewardship (AMS) interventions has been published, few studies justify intervention components or incorporate theory into designing interventions. The objective of the study was to develop a theory-informed multifaceted AMS intervention to improve management of bacteriuria in adults admitted to hospital. Methods We used the 4-step approach described by French and colleagues to develop a theory informed intervention. A systematic review of AMS interventions to improve antibiotic use for bacteriuria was completed. In addition, local barriers to improving antimicrobial use in hospitalized adults with bacteriuria were assessed through a qualitative study using focus groups with health care providers. Barriers identified through the qualitative study were mapped to the Theoretical Domains Framework and the COM-B model then linked to the Behaviour Change Wheel. Published literature, focus group results, and practical considerations were used by our team to identify and rank possible solutions. Consensus on which interventions to implement locally was achieved using the Nominal Group Technique. Results Ten interventions that could address local challenges with antimicrobial prescribing for bacteriuria were identified. The highest-ranking interventions were audit and feedback (to individuals or teams), active educational sessions, development of clinical order sets, and incorporating clinical decision support with culture results. A multifaceted intervention that included monthly audit and feedback on management of bacteriuria to multidisciplinary teams in combination with case-based virtual education sessions was developed and is currently being piloted at four tertiary and community hospitals. Conclusion Use of theory to identify local barriers and facilitators to improving antimicrobial use in combination with evidence and practical considerations should be incorporated into design and implementation of AMS interventions. Further work will evaluate impact of this theory-informed AMS intervention on antimicrobial prescribing for bacteriuria in hospitalized adults. Disclosures Emily Black, BSc(Pharm), PharmD, Drug Evaluation Alliance of Nova Scotia: Grant/Research Support|Research Nova Scotia: Grant/Research Support Paul Bonnar, MD, BioMerieux: Honoraria|Paladin Labs: Honoraria Samuel G. Campbell, FRCP (Edin), Astra Zeneca: Board Member
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.018 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".