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Record W2755139436 · doi:10.1093/ofid/ofx163.1260

High- vs. Low-Intensity Prospective Audit and Feedback on Internal Medicine Wards and Impact on Antimicrobial Use at a Community Hospital

2017· article· en· W2755139436 on OpenAlexaff
Bradley J. Langford, April Chan, Kevin A. Brown, Mark Downing

Bibliographic record

VenueOpen Forum Infectious Diseases · 2017
Typearticle
Languageen
FieldHealth Professions
TopicPatient Satisfaction in Healthcare
Canadian institutionsPublic Health OntarioUniversity of TorontoSt Joseph's Health Centre
Fundersnot available
KeywordsMedicineAntimicrobial stewardshipAntimicrobialDefined daily dosePsychological interventionInternal medicineAntibioticsEmergency medicineIntensive care medicineAntibiotic resistanceMedical prescriptionNursing

Abstract

fetched live from OpenAlex

Antimicrobial stewardship program (ASP) interventions, such as prospective audit and feedback (PAF), have been shown to reduce antimicrobial use and improve patient outcomes. However, there is a lack of data comparing different PAF approaches. We examined the impact of a high-intensity interdisciplinary rounds-based PAF compared with low-intensity PAF on antimicrobial use on internal medicine wards in a 400-bed community hospital. Prior to the intervention, low-intensity PAF was performed by ASP pharmacists with a focus on targeted antibiotics (fluoroquinolones, anti-pseudomonal penicilins, carbapenems, vancomycin, clindamycin, third-generation cephalosporins). Recommendations were made directly to the internist for each patient. High-intensity rounds-based PAF was introduced to 5 internal medicine wards sequentially. Rounds occurred twice weekly, reviewed internal medicine patients receiving any antimicrobial agent, and were interdisciplinary (ASP PharmD, internist, ward pharmacist, ASP MD). The primary outcome was antimicrobial use on internal medicine wards measured in defined daily doses (DDD) per 1000 patient-days (PD) 1–24 months prior compared with 1–24 months after the intervention. We performed interrupted time series analysis using linear regression to compare prescribing rates while accounting for autocorrelation within wards. Adjusted models included covariates to account for secular and seasonal trends. Following the intervention, there was a non-statistically significant drop in antimicrobial use from 469 to 435 DDD/1000 PD. See Table 1 and Figure 1 for analyses of antibiotic use. Although high-intensity PAF did not result in lower antibiotic use compared with low-intensity PAF overall, a delayed reduction (>12 months) in usage was seen. Prospective studies are needed to determine the optimal approach to PAF. Change in Antimicrobial Use After High-Intensity PAF (DDD/1000 PD) Antimicrobial Use on Internal Medicine Wards Before and After High-Intensity PAF All authors: No reported disclosures.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.072
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0070.001
Scholarly communication0.0000.001
Open science0.0000.002
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 head0.038
GPT teacher head0.397
Teacher spread0.359 · 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.

Study designObservational
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

Citations1
Published2017
Admission routes1
Has abstractyes

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