Nudging In MicroBiology Laboratory Evaluation (NIMBLE): A scoping review
Bibliographic record
Abstract
BACKGROUND: Nudging in microbiology is an antimicrobial stewardship strategy to influence decision making through the strategic reporting of microbiology results while preserving prescriber autonomy. The purpose of this scoping review was to identify the evidence that demonstrates the effectiveness of nudging strategies in susceptibility result reporting to improve antimicrobial use. METHODS: A search for studies in Ovid MEDLINE, Embase, PsycINFO, and All EBM Reviews was conducted. All simulated and vignette studies were excluded. Two independent reviewers were used throughout screening and data extraction. RESULTS: Of a total of 1,346 citations screened, 15 relevant studies were identified. Study types included pre- and postintervention (n = 10), retrospective cohort (n = 4), and a randomized controlled trial (n = 1). Most studies were performed in acute-care settings (n = 13), and the remainder were in primary care (n = 2). Most studies used a strategy to alter the default antibiotic choices on the antibiotic report. All studies reported at least 1 outcome of antimicrobial use: utilization (n = 9), appropriateness (n = 7), de-escalation (n = 2), and cost (n = 1). Moreover, 12 studies reported an overall benefit in antimicrobial use outcomes associated with nudging, and 4 studies evaluated the association of nudging strategy with subsequent antimicrobial resistance, with 2 studies noting overall improvement. CONCLUSIONS: The number of heterogeneous studies evaluating the impact of applying nudging strategies to susceptibility result reports is small; however, most strategies do show promise in altering prescriber's antibiotic selection. Selective and cascade reporting of targeted agents in a hospital setting represent the majority of current research. Gaps and opportunities for future research identified from our scoping review include performing prospective randomized controlled trials and evaluating other approaches aside from selective reporting.
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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 | 0.057 | 0.206 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.008 | 0.008 |
| Bibliometrics | 0.035 | 0.029 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.009 | 0.009 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.006 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".