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Enregistrement W4230304840 · doi:10.1002/14651858.cd000125.pub5

Local opinion leaders: effects on professional practice and healthcare outcomes

2019· review· en· W4230304840 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.

Notice bibliographique

RevueCochrane Database of Systematic Reviews · 2019
Typereview
Langueen
DomaineHealth Professions
ThématiquePrimary Care and Health Outcomes
Établissements canadiensOttawa HospitalUniversity of Toronto
Organismes subventionnairesnon disponible
Mots-clésOpinion leadershipHealth careHealth professionalsPublic relationsPsychologyBusinessNursingMedicineMedical educationPolitical science

Résumé

récupéré en direct d'OpenAlex

Clinical practice is not always evidence-based and, therefore, may not optimise patient outcomes. Local opinion leaders (OLs) are individuals perceived as credible and trustworthy, who disseminate and implement best evidence, for instance through informal one-to-one teaching or community outreach education visits. The use of OLs is a promising strategy to bridge evidence-practice gaps. This is an update of a Cochrane review published in 2011.To assess the effectiveness of local opinion leaders to improve healthcare professionals' compliance with evidence-based practice and patient outcomes.We searched CENTRAL, MEDLINE, Embase, three other databases and two trials registers on 3 July 2018, together with searching reference lists of included studies and contacting experts in the field.We considered randomised studies comparing the effects of local opinion leaders, either alone or with a single or more intervention(s) to disseminate evidence-based practice, with no intervention, a single intervention, or the same single or more intervention(s). Eligible studies were those reporting objective measures of professional performance, for example, the percentage of patients being prescribed a specific drug or health outcomes, or both. We included all studies independently of the method used to identify OLs.We used standard Cochrane procedures in this review. The main comparison was (i) between any intervention involving OLs (OLs alone, OLs with a single or more intervention(s)) versus any comparison intervention (no intervention, a single intervention, or the same single or more intervention(s)). We also made four secondary comparisons: ii) OLs alone versus no intervention, iii) OLs alone versus a single intervention, iv) OLs, with a single or more intervention(s) versus the same single or more intervention(s), and v) OLs with a single or more intervention(s) versus no intervention.We included 24 studies, involving more than 337 hospitals, 350 primary care practices, 3005 healthcare professionals, and 29,167 patients (not all studies reported this information). A majority of studies were from North America, and all were conducted in high-income countries. Eighteen of these studies (21 comparisons, 71 compliance outcomes) contributed to the median adjusted risk difference (RD) for the main comparison. The median duration of follow-up was 12 months (range 2 to 30 months). The results suggested that the OL interventions probably improve healthcare professionals' compliance with evidence-based practice (10.8% absolute improvement in compliance, interquartile range (IQR): 3.5% to 14.6%; moderate-certainty evidence).Results for the secondary comparisons also suggested that OLs probably improve compliance with evidence-based practice (moderate-certainty evidence): i) OLs alone versus no intervention: RD (IQR): 9.15% (-0.3% to 15%); ii) OLs alone versus a single intervention: RD (range): 13.8% (12% to 15.5%); iii) OLs, with a single or more intervention(s) versus the same single or more intervention(s): RD (IQR): 7.1% (-1.4% to 19%); iv) OLs with a single or more intervention(s) versus no intervention: RD (IQR):10.25% (0.6% to 15.75%).It is uncertain if OLs alone, or in combination with other intervention(s), may lead to improved patient outcomes (3 studies; 5 dichotomous outcomes) since the certainty of evidence was very low. For two of the secondary comparisons, the IQR included the possibility of a small negative effect of the OL intervention. Possible explanations for the occasional negative effects are, for example, the possibility that the OLs may have prioritised some outcomes, at the expense of others, or that an unaccounted outcome difference at baseline, may have given a faulty impression of a negative effect of the intervention at follow-up. No study reported on costs or cost-effectiveness.We were unable to determine the comparative effectiveness of different approaches to identifying OLs, as most studies used the sociometric method. Nor could we determine which methods used by OLs to educate their peers were most effective, as the methods were poorly described in most studies. In addition, we could not determine whether OL teams were more effective than single OLs.Local opinion leaders alone, or in combination with other interventions, can be effective in promoting evidence-based practice, but the effectiveness varies both within and between studies.The effect on patient outcomes is uncertain. The costs and the cost-effectiveness of the intervention(s) is unknown. These results are based on heterogeneous studies differing in types of intervention, setting, and outcomes. In most studies, the role and actions of the OL were not clearly described, and we cannot, therefore, comment on strategies to enhance their effectiveness. It is also not clear whether the methods used to identify OLs are important for their effectiveness, or whether the effect differs if education is delivered by single OLs or by multidisciplinary OL teams. Further research may help us to understand how these factors affect the effectiveness of OLs.

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)0,010
score de la tête « metaresearch » (Gemma)0,011
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMétarecherche, Méta-épidémiologie (sens strict), Méta-épidémiologie (sens large), Intégrité de la recherche, Charge 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 enseignants0,430
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0100,011
Méta-épidémiologie (sens strict)0,0010,001
Méta-épidémiologie (sens large)0,0150,001
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0010,001
Intégrité de la recherche0,0010,002
Charge utile insuffisante (le modèle a refusé de juger)0,0000,003

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 Opus0,278
Tête enseignante GPT0,549
Écart entre enseignants0,271 · 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