A Toolkit to facilitate the implementation of an Integrated Care Network for People living with Parkinson: A Codesign Approach
Notice bibliographique
Résumé
Background: In response to the critical health care situation faced by People living with Parkinson’s (PwP), a group of experts decided to develop and implement a care model (iCARE-PD project) for addressing the complex care needs in Parkinson’s disease (PD). As part of this multidisciplinary and international project, a codesign approach was implemented to identify the central pillars of the care model, namely: home-based care delivery; integrated care; self-management support and technology-enabled care. For the success of this patient-centered model in a varied social, cultural and economic landscape, we need to develop a tool that facilitates the implementation of an integrated care network across different social contexts. Purpose & Method: The codesign approach, implemented in this study, consisted of four linked steps that were coordinated among 5 countries: (1) Preparation (2) Capture patients’ experiences by using narrative interviews and understand the patients’ trajectory; (3) Design scenarios for an integrated care delivery network with patients, care partners (CP), and health care providers (HCP) and (4) Co-produce solutions by identifying key requirements for designing a roadmap and toolkit to facilitate the implementation of an integrated care network in various social contexts. As part of the iCARE-PD project, this communication presents the findings of the final phase of the codesign approach which brought together researchers, clinicians, nurses and patient advisors in May 2022 for a workshop aimed at collectively co-defining the key elements to be included in an integrated care toolkit. Scenarios identifying key components for designing an integrated care network for PD were created by PwP, CP and HCP during previous workshops. Based on these scenarios designed previously, a workshop was conducted and recorded in order to produce a roadmap and toolkit that takes into consideration the unique challenges faced by PwP in each country, and the need for an integrated care delivery network that can be personalized and malleable to evolving and changing needs over time. Results: We will present the results of the thematic analysis of the transcript of the workshop. In order to improve person centeredness, tailor and personalize care and propose a holistic approach of PD in integrated care, a roadmap including three features needs to be integrated into a toolkit: (a) Identify ‘boundary spanners’ such as key individuals people or tools to support patient-centered care, (b) select mediators to connect various actors in the networks and create informational and technological infrastructure to facilitate access to tailored information and resources and, (c) create and share tools, data and resources to improve communication processes and coordination of care. Each of the design features involves various practical solutions shared and co-created during the workshop that could be useful to develop an integrated care toolkit.
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 machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,052 | 0,070 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,004 | 0,002 |
| Études des sciences et des technologies | 0,006 | 0,006 |
| Communication savante | 0,006 | 0,010 |
| Science ouverte | 0,005 | 0,024 |
| Intégrité de la recherche | 0,004 | 0,006 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,008 | 0,003 |
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.
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 source (Gemma direct ou Codex distillé), 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 ».