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Record W2024566355 · doi:10.12927/hcq.2013.21672

Establishing an Antimicrobial Stewardship Program

2010· article· en· W2024566355 on OpenAlexaffabout
Andrew M. Morris, T. D. Stewart, Maureen Shandling, Scott McIntaggart, W. Conrad Liles

Bibliographic record

VenueHealthcare Quarterly · 2010
Typearticle
Languageen
FieldImmunology and Microbiology
TopicAntibiotic Use and Resistance
Canadian institutionsUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsAntimicrobial stewardshipAccreditationGovernment (linguistics)Infection controlBusinessBest practiceStewardship (theology)Control (management)Antibiotic StewardshipMedicineAntibioticsIntensive care medicineAntibiotic resistancePolitical scienceMedical educationManagementMicrobiology

Abstract

fetched live from OpenAlex

Hospitals are faced with increasing challenges of antibiotic-resistant organisms and rising antimicrobial costs despite widespread attention to infection prevention and control measures. Government, professional organizations and accreditation bodies are all signalling an urgent need for the establishment of programs in hospitals to address antibiotic misuse. Although variations of such "antimicrobial stewardship programs" have been functioning in Canada for some time, a formal approach using change management and quality improvement principles has largely been lacking. We describe how we have established such a program in a teaching hospital, modelled on John Kotter's eight steps of leading change.

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.

How this classification was reachedexpand

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.673
Threshold uncertainty score0.708

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.013
GPT teacher head0.288
Teacher spread0.275 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations16
Published2010
Admission routes2
Has abstractyes

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