Medication Supports at Transitions Between Hospital and Other Care Settings: A Rapid Scoping Review
Notice bibliographique
Résumé
PURPOSE: Transitions in care (TiC) often involves managing medication changes and can be vulnerable moments for patients. Medication support, where medication changes are reviewed with patients and caregivers to increase knowledge and confidence about taking medications, is key to successful transitions. Little is known about the optimal tools and processes for providing medication support. This study aimed to identify describe patient or caregiver-centered medication support processes or tools that have been studied within 3 months following TiC between hospitals and other care settings. METHODS: Rapid scoping review; English-language publications from OVID MEDLINE, OVID EMBASE, Cochrane Library and EBSCO CINAHL (2004-July 2019) that assessed medication support interventions delivered within 3 months following discharge were included. A subset of titles and abstracts were assessed by two reviewers to evaluate agreement and once reasonable agreement was achieved, the remainder were assessed by one reviewer. Eligibility assessment for full-text articles and data charting were completed by an experienced reviewer. RESULTS: A total of 7671 unique citations were assessed; 60 studies were included. Half of the studies (n = 30/60) were randomized controlled trials. Most studies (n = 45/60) did not discuss intervention development, particularly whether end users were involved in intervention design. Many studies (n = 37/60) assessed multi-component interventions with written/print and verbal education components. Few studies (n = 5/60) included an electronic component. Very few studies (n = 4/60) included study populations at high risk of adverse events at TiC (eg, people with physical or intellectual disabilities, low literacy or language barriers). CONCLUSION: The majority of studies were randomized controlled trials involving verbal counselling and/or physical document delivered to the patient before discharge. Few studies involved electronic components or considered patients at high-risk of adverse events. Future studies would benefit from improved reporting on development, consideration for electronic interventions, and improved reporting on patients with higher medication-related needs.
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 enseignantsNi 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.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,000 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».