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Cet article a été analysé le 23/04/2026 — score rapide ⚡
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Ce score couvre ~53% des critères (métadonnées publiques). Les rétractations et signaux d'intégrité sont détectés à 100%. En savoir plus sur les modes de scoring
Résumé (abstract PubMed)
Discharge from hospital is a critical part of the patient journey, particularly for older patients with multimorbidity and polypharmacy. General practice has a key role in managing the post-discharge course of patients. A communication intervention for use in general practice in the immediate post-discharge period has great potential to improve shared decision making, enhancing patient experiences of post-discharge care.
General Practice Management After Transition Events (GP-MATE) aims to produce a tool for older patients and their carers (GP-MATE), which will assist better communication with their general practice about their care after discharge, thereby improving patient safety outcomes.
Experience-based co-design (EBCD) study involving general practices across the West Midlands.
A slightly modified approach to EBCD will be followed to create GP-MATE. A focused ethnography undertaken at general practices will provide an understanding of practices' systems for post-discharge management of older patients. Semi-structured video interviews with recently discharged older patients or their carers will be edited into a trigger film. Finally, co-design workshops with older people, carers, and healthcare staff working in general practices will take place with participants from three regions across England.
EBCD will be used to take a patient-centric approach towards creating GP-MATE; patients' and carers' priorities will be directly reflected within the tool. GP-MATE will be a low-cost intervention that improves health literacy, empowering patients to fill the emerging gap in continuity in the post-discharge period and enhancing patient experiences of post-discharge care.
Coeff. auteurs = moyenne(0.50, 0.70) = 0.60
Coeff. éditorial = moyenne(0.70, 0.70) = 0.70
min(0.60, 0.70) = 0.60← le plus faible domine
Coefficient final : 0.60
Score final = 35 × 0.60 = 21/100
Métadonnées uniquement — score calculé sur les données PubMed/APIs.
9/26 critères évalués (35%)
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