A Living Laboratory Supporting Individuals with Complex Care Needs: The Centre for Research in Integrated Care 
Notice bibliographique
Résumé
Individuals with complex care needs (CCNs) require more health and social care services than the average population. These individuals have better outcomes if they have access to integrated services across settings and sectors. Although promising research on integrated care is underway, efforts are typically not coordinated and occur without patient partner involvement. The critical need for collaboration among stakeholders in this field prompted the establishment of the Centre for Research in Integrated Care (CRIC) in 2018. CRIC is a living laboratory that develops and evaluates integrated care models that are patient-centred and based on the needs of individuals with CCNs. We engage with various stakeholder groups across Canada, including clinicians, decision makers, researchers, trainees, and patient partners in a setting where innovative ideas are explored and modified as needed throughout the research process. We use a patient-oriented research approach, which engages patient partners throughout the entire research process. Together we identify research priorities; design, implement, and evaluate programs; and share our findings. Our team conducts needs assessments on gaps and barriers to care and then develops, implements, and evaluates integrated care models to address these gaps and barriers. One example is a navigation centre we created for children with CCNs and their families. This was implemented in partnership with a patient and family advisory council and based on a needs assessment that involved over 120 interviews with children, their families, and care providers. In this model, patient navigators worked with clients to proactively guide and support them, matching unmet needs to appropriate resources. We have since spread this innovation to support people with dementia and their care partners. Our research demonstrates that navigation programs are effective in decreasing fragmentation, improving access, and promoting the integration of care. Our team also conducts research in close collaboration with the PriCARE Team led by Dr. Catherine Hudon on case management, one of the most studied and recommended models of integrated care. In this model, a case manager is assigned to patients, and they work collaboratively with the care team and patient to assess, plan, facilitate, and coordinate care. Patient partners have been actively engaged in all aspects of this research for 6+ years. We have found this intervention to be successful in improving patient outcomes, such as improved self-management, and also health system outcomes, such as decreased emergency room visits. In this poster presentation, we will share how CRIC creates an ecosystem where diverse stakeholders can co-create knowledge and solutions to contemporary health problems through the implementation of innovative and integrated health services across settings and sectors. We will also share how we apply our patient-oriented research approach to ensure that our studies are focused on meeting the needs of patients and improving their outcomes. Ultimately, our goal is to broaden our national scope and create new international partnerships so that we can expand the reach and impact of our research. The sustainability of healthcare systems worldwide is dependent on finding new ways to meet the needs of individuals who experience CCNs.
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 | 0,047 | 0,065 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,002 |
| Bibliométrie | 0,003 | 0,002 |
| Études des sciences et des technologies | 0,015 | 0,017 |
| Communication savante | 0,016 | 0,012 |
| Science ouverte | 0,008 | 0,039 |
| Intégrité de la recherche | 0,005 | 0,013 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,020 | 0,007 |
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 ».