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Record W2596460571 · doi:10.1093/cid/cix220

Time Efficiency Assessment of Antimicrobial Stewardship Strategies

2017· letter· en· W2596460571 on OpenAlexaff
Gabriele Pollara, Suparna Bali, Michael Marks, Ian Bates, Sophie Collier, Indran Balakrishnan

Bibliographic record

VenueClinical Infectious Diseases · 2017
Typeletter
Languageen
FieldImmunology and Microbiology
TopicAntibiotic Use and Resistance
Canadian institutionsInstitute of Infection and Immunity
FundersNational Institute for Health and Care ResearchWellcome Trust
KeywordsAntimicrobial stewardshipMedicineAntimicrobialStewardship (theology)Intensive care medicineAnti-Infective AgentsMicrobiologyAntibioticsAntibiotic resistance

Abstract

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To the Editor—We read with interest the recent article in Clinical Infectious Diseases by Tamma et al [1], which focused on the efficacy of different antimicrobial stewardship methods, demonstrating that post-prescription review with feedback (PPRF) was more effective at reducing antimicrobial consumption over time than pre-prescription authorization. The study was performed on medical inpatients, but hospitals contain many other cohorts, such as surgical inpatients, in whom antimicrobial use is also high and often inappropriate [2]. PPRF can take many forms but is invariably both human resource and time intensive. Many hospitals may lack the resources to initiate this level of stewardship universally [3, 4], and there is therefore a need to identify the form of PPRF that most efficiently impacts inappropriate antimicrobial prescribing [5, 6]. We performed a prospective, observational study that compared different forms of PPRF: ward round reviews on acute medical wards, ward round reviews on surgical recovery wards, and telephone reviews with clinical teams caring for patients receiving carbapenems, cephalosporines, or quinolones. Each stewardship review episode was performed by 2 microbiologists and a pharmacist, who collected no more data than needed for routine practice and were not aware that the data would be used comparatively in the study. The 3 stewardship modalities occurred daily for 45, 90, or 60 minutes—for medical rounds, surgical rounds, and telephone reviews, respectively—and there was no overlap in the patients reviewed. All antimicrobial prescriptions reviewed were quantified and any intervention was recorded, with an intervention defined as a change to antimicrobial prescription, including starting or stopping treatment with a medication or modifying the duration of treatment or mode of administration. For the purpose of comparison, we considered telephone stewardship to be the control group. We calculated both the proportion of reviews resulting in an intervention and the rate of intervention per hour of stewardship across the 3 stewardship modalities. A total of 1928 antimicrobial prescriptions were reviewed. Both surgical (37.24%) and medical (9.35%) stewardship ward rounds resulted in a significantly higher proportion of interventions than telephone reviews (4.34%) (Table 1). However, after controlling for time, the rate of interventions per hour was higher for medical stewardship rounds (2.26 interventions / hour) than for both surgical (1.70 interventions / hour) and telephone (0.48 interventions / hour) rounds (Table 1). Number, Proportion and Rate of Interventions by Stewardship Modality Abbreviation: CI, confidence interval. Number, Proportion and Rate of Interventions by Stewardship Modality Abbreviation: CI, confidence interval. In conclusion, our study supports the observations made by Tamma et al [1] that hospital ward–based PPRF, though resource intensive, is an effective form of antimicrobial stewardship. We extend their findings by raising the importance of time efficiency, demonstrating that although surgical patient stewardship rounds result in a high absolute number and proportion of interventions, they are labor intensive, and medical ward rounds resulted in a similar number of interventions per hour of stewardship time. Both approaches were significantly better than telephone stewardship in terms of both the proportion and rate of stewardship interventions. We propose that other hospitals looking to assess and prioritize the impact of their stewardship programs should also incorporate a standardized time-based measure of stewardship efficiency. Financial support. This work was supported by the Wellcome Trust (grant WT101766/Z/13/Z to G. P.). Potential conflicts of interest. Author certifies no potential conflicts of interest. All author has submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest. Conflicts that the editors consider relevant to the content of the manuscript have been disclosed.

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How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.009
metaresearch head score (Gemma)0.056
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.047

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.056
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.001

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 head0.025
GPT teacher head0.348
Teacher spread0.323 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations9
Published2017
Admission routes1
Has abstractno

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