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Enregistrement W2596460571 · doi:10.1093/cid/cix220

Time Efficiency Assessment of Antimicrobial Stewardship Strategies

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

Notice bibliographique

RevueClinical Infectious Diseases · 2017
Typeletter
Langueen
DomaineImmunology and Microbiology
ThématiqueAntibiotic Use and Resistance
Établissements canadiensInstitute of Infection and Immunity
Organismes subventionnairesNational Institute for Health and Care ResearchWellcome Trust
Mots-clésAntimicrobial stewardshipMedicineAntimicrobialStewardship (theology)Intensive care medicineAnti-Infective AgentsMicrobiologyAntibioticsAntibiotic resistance

Résumé

récupéré en direct d'OpenAlex

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.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,009
score de la tête « metaresearch » (Gemma)0,056
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,009
Score d'incertitude au seuil0,047

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0090,056
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0010,001
Études des sciences et des technologies0,0000,000
Communication savante0,0020,002
Science ouverte0,0010,001
Intégrité de la recherche0,0020,002
Charge utile insuffisante (le modèle a refusé de juger)0,0040,001

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,025
Tête enseignante GPT0,348
Écart entre enseignants0,323 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations9
Publié2017
Routes d'admission1
Résumé présentnon

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