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Enregistrement W4289223117 · doi:10.1016/j.annemergmed.2022.06.001

A Systematic Review of Interventions to Reduce Computed Tomography Usage in the Emergency Department

2022· review· en· W4289223117 sur OpenAlex

Pourquoi ce travail est dans la base

Une base qui oublie comment elle a trouvé un travail ne peut pas être vérifiée. Voici les voies qui ont admis celui-ci.

affAu moins un auteur déclare une institution canadienne dans l'instantané OpenAlex épinglé.
fundUn bailleur canadien est enregistré sur le travail.

Notice bibliographique

RevueAnnals of Emergency Medicine · 2022
Typereview
Langueen
DomaineMedicine
ThématiqueRadiology practices and education
Établissements canadiensUniversity of Calgary
Organismes subventionnairesCumming School of Medicine, University of CalgaryAlberta Health Services
Mots-clésMedicineEmergency departmentComputed tomographyPsychological interventionMedical emergencyMedical physicsEmergency medicineRadiologyNursing

Résumé

récupéré en direct d'OpenAlex

Study objectiveUnnecessary computed tomography (CT) scans burden the health care system, leading to increased emergency department (ED) wait times and lengths of stay, costing almost a billion dollars annually. This study aimed to describe ED-based interventions that are most effective at reducing CT imaging while maintaining diagnostic accuracy and patient safety.MethodsAdhering to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, MEDLINE, Embase, CINAHL, Cochrane Central Register of Controlled Trials, and Google Scholar were searched until December 31, 2020. Randomized and nonrandomized studies that assessed the effect of an ED-based intervention on CT scan usage were included. Abstract screening, data extraction, and quality assessment were conducted in duplicate. The Grading of Recommendation Assessment, Development and Evaluation framework, with the Risk of Bias 2 and Risk of Bias in Nonrandomized Studies - of Interventions tools, was used to determine the certainty of evidence. Significant clinical and statistical heterogeneity precluded meta-analysis; hence, a narrative synthesis was conducted.ResultsA total of 149 studies were included of 5,667 screened abstracts, with substantial interrater reliability among reviewers (Cohen’s κ>0.60). The CT reduction strategies were categorized into 15 single and 11 multimodal interventions by consensus review. Interventions that consistently reduced CT usage included diagnostic pathways, alternative test availability, specialist involvement, and provider feedback. Family/patient education, clinical decision support tools, or passive guideline dissemination did not consistently reduce usage. Only 44% of studies reported unintended consequences of reduction strategies; however, these showed no increase in missed diagnoses or patient harm. The interventions that engaged multiple specialties during planning/implementation had a greater reduction effect than ED only. The certainty of evidence for the primary outcome was very low.ConclusionMultidisciplinary-led interventions that provided an alternative to CT imaging were the most effective at reducing usage and did so without compromising patient safety. Unnecessary computed tomography (CT) scans burden the health care system, leading to increased emergency department (ED) wait times and lengths of stay, costing almost a billion dollars annually. This study aimed to describe ED-based interventions that are most effective at reducing CT imaging while maintaining diagnostic accuracy and patient safety. Adhering to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, MEDLINE, Embase, CINAHL, Cochrane Central Register of Controlled Trials, and Google Scholar were searched until December 31, 2020. Randomized and nonrandomized studies that assessed the effect of an ED-based intervention on CT scan usage were included. Abstract screening, data extraction, and quality assessment were conducted in duplicate. The Grading of Recommendation Assessment, Development and Evaluation framework, with the Risk of Bias 2 and Risk of Bias in Nonrandomized Studies - of Interventions tools, was used to determine the certainty of evidence. Significant clinical and statistical heterogeneity precluded meta-analysis; hence, a narrative synthesis was conducted. A total of 149 studies were included of 5,667 screened abstracts, with substantial interrater reliability among reviewers (Cohen’s κ>0.60). The CT reduction strategies were categorized into 15 single and 11 multimodal interventions by consensus review. Interventions that consistently reduced CT usage included diagnostic pathways, alternative test availability, specialist involvement, and provider feedback. Family/patient education, clinical decision support tools, or passive guideline dissemination did not consistently reduce usage. Only 44% of studies reported unintended consequences of reduction strategies; however, these showed no increase in missed diagnoses or patient harm. The interventions that engaged multiple specialties during planning/implementation had a greater reduction effect than ED only. The certainty of evidence for the primary outcome was very low. Multidisciplinary-led interventions that provided an alternative to CT imaging were the most effective at reducing usage and did so without compromising patient safety.

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.

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)0,005
score de la tête « metaresearch » (Gemma)0,003
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesCharge utile insuffisante (le modèle a refusé de juger)
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 enseignants0,289
Score d'incertitude au seuil0,994

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0050,003
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0040,001
Bibliométrie0,0010,003
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0010,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0070,000

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 Opus0,343
Tête enseignante GPT0,523
Écart entre enseignants0,180 · 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