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Enregistrement W3143029697 · doi:10.1093/ijpp/riab015.061

A systematic review to investigate the effect of digital antimicrobial stewardship tools on antimicrobial usage, length of stay, mortality and cost

2021· review· en· W3143029697 sur OpenAlexaboutno aff
Nicole E. Trotter, Radin Karimi, Clare Tolley, Sarah P. Slight

Notice bibliographique

RevueInternational Journal of Pharmacy Practice · 2021
Typereview
Langueen
DomaineImmunology and Microbiology
ThématiqueAntibiotic Use and Resistance
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésCINAHLMedicineAntimicrobial stewardshipMEDLINEAntimicrobialStewardship (theology)Intensive care medicineAntibiotic resistanceFamily medicineNursingPsychological interventionAntibiotics

Résumé

récupéré en direct d'OpenAlex

Abstract Introduction Antimicrobial drug resistance has been recognised by the World Health Organisation as ‘One of the biggest threats to global health today’.1 As the use of digital systems in the NHS increases, there is huge potential to use systems such as electronic prescribing and clinical decision support as part of Antimicrobial Stewardship Programmes (ASPs) i.e., initiatives to change prescribing practices to promote and monitor use of antimicrobials and preserve their future effectiveness. However, there is a lack of research that has investigated the impact of digital tools as part of ASPs. Aim We aimed to review the literature available on the use of digital antimicrobial stewardship tools on individual outcomes such as antimicrobial usage, length of stay, mortality and cost. Methods A systematic search was performed across three databases (Embase, MEDLINE and CINAHL) using MESH terms and key words relating to antimicrobial stewardship, hospitals, length of stay (LOS), clinical outcomes, cost and mortality. Duplicates were removed and articles screened at the title, abstract and full text stage by two authors (NT and RK) according to our inclusion and exclusion criteria. We included primary research articles that: had implemented an ASPs in an adult hospital setting for at least 6 months, reported antimicrobial usage as defined daily dose per 1000 patient days (DDD/1000) and at least one of the following outcomes: LOS, mortality or cost and discussed an ASP that included a digital component. Risk of bias assessment was performed using the Newcastle-Ottawa scale. We calculated the percentage change to determine the impact of digital ASPs across all outcomes using the formula (After - Before)/Before x 100 = % Change. Before=pre-implementation results; after= results post-implementation Results We identified 3997 papers across all databases, and included 14 full texts that explored the impact of ASPs including a digital component (Figure 1). Of these, 14 papers reported the DDD/1000, 7 on mortality, 8 on LoS and 6 reported on cost. All studies evaluating DDD/1000 reported a decrease in antimicrobial usage ranging from -8.42% to -61.30%. Reductions in mortality (0 to -79%), LoS (25 to -27%) and costs (-8.42% to -69.19%) were also found. All ASPs utilised a digital component alongside a range of other interventions, such as the creation of formularies, guidelines and education emphasising the importance of using a combined approach in antimicrobial stewardship. Different interventions were found to have their own advantages, for example, education was key to sustainability and feedback was essential to improve prescribing practices. Users of the digital tools found that the tools were generally simple and user friendly, which facilitated their acceptance. Conclusion Our found that ASPs including a digital component were associated with reductions in antimicrobial usage, mortality, length of stay and cost. The positive effects were seen when such tools were combined with other approaches such as education and feedback approaches. We were unable to perform a meta-analysis due to the absence of confidence intervals and odds ratios in many of the included studies. Further research is needed to evaluate the cost-benefit associated with digital ASPs and whether sharing ASPs across multiple sites could reduce the maintenance burden for individual organisations. References 1. World Health Organisation (2020), Antibiotic Resistance Factsheet, https://www.who.int/news-room/fact-sheets/detail/antibiotic-resistance [accessed on 18th October 2020]

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 distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,003
score de la tête « metaresearch » (Gemma)0,007
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Revue systématique · Signal consensuel: Revue systématique
GenreSignal candidat: Synthèse · Signal consensuel: Synthèse
Score de désaccord entre enseignants0,398
Score d'incertitude au seuil0,925

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0030,007
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0030,001
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0010,000
Intégrité de la recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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 Opus0,075
Tête enseignante GPT0,418
Écart entre enseignants0,343 · 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 tête enseignante, pas un consensus.

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

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

En bref

Citations2
Publié2021
Routes d'admission1
Résumé présentoui

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