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Improving Antibiotic Selection

2006· review· en· W2094834250 on OpenAlex
Michael A. Steinman, Sumant R Ranji, Kaveh G Shojania, Ralph Gonzales

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueMedical Care · 2006
Typereview
Languageen
FieldImmunology and Microbiology
TopicAntibiotic Use and Resistance
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsMedicinePsychological interventionInterquartile rangeMEDLINESample size determinationRandomized controlled trialFamily medicineIntensive care medicineInternal medicineNursing

Abstract

fetched live from OpenAlex

OBJECTIVE: We sought to assess which interventions are most effective at improving the prescribing of recommended antibiotics for acute outpatient infections. DESIGN AND METHODS: We undertook a systematic review with quantitative analysis of the Cochrane Registry Effective Practice and Organization of Care (EPOC) database, supplemented by MEDLINE and hand-searches. Inclusion criteria included clinical trials with contemporaneous or strict historical controls that reported data on antibiotic selection in acute outpatient infections. The effect size of studies with different intervention types were compared using nonparametric statistics. To maximize comparability between studies, quantitative analysis was restricted to studies that reported absolute changes in the amount of or percent compliance with recommended antibiotic prescribing. RESULTS: Twenty-six studies reporting 33 trials met inclusion criteria. Most interventions used clinician education alone or in combination with audit and feedback. Among the 22 comparisons amenable to quantitative analysis, recommended antibiotic prescribing improved by a median of 10.6% (interquartile range [IQR] 3.4-18.2%). Trials evaluating clinician education alone reported larger effects than interventions combining clinician education with audit and feedback (median effect size 13.9% [IQR 8.6-21.6%] vs. 3.4% [IQR 1.8-9.7%], P = 0.03). This result was confounded by trial sample size, as trials having a smaller number of participating clinicians reported larger effects and were more likely to use clinician education alone. Active forms of education, sustained interventions, and other features traditionally associated with successful quality improvement interventions were not associated with effect size and showed no evidence of confounding the association between clinician education-only strategies and outcome. CONCLUSIONS: Multidimensional interventions using audit and feedback to improve antibiotic selection were less effective than interventions using clinician education alone. Although confounding may partially account for this finding, our results suggest that enhancing the intensity of a focused intervention may be preferable to a less intense, multidimensional approach.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesResearch integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.984
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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.

Opus teacher head0.013
GPT teacher head0.285
Teacher spread0.273 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it