Navigating Dementia Care: An Integrated Program for People with Dementia, Care Partners, and the Care Team
Notice bibliographique
Résumé
Dementia care is often fragmented and difficult to navigate. Patient navigation (PN) is one solution to address the care needs of people with dementia (PWD) and their care partners. Navigating Dementia NB/ Naviguer la démence NB was a research project that piloted a patient navigation (PN) program in a small semi-rural province in Canada for PWD, their care partners, and the care team. The intervention was co-designed with multiple stakeholders, including clinicians, researchers, patient partners, and representatives from Regional Health Authorities. For example, the research team collaborated with representatives from the Regional Health Authorities (e.g., directors, clinic managers) to select the most appropriate clinical sites for this intervention and to manage day-to-day operations of the intervention. A Patient and Family Advisory Committee (PFAC) assisted with program oversight and a member of PFAC also sat on the project organizational committee. The PN program aimed to guide and support patients and their families through health and social care systems, matching client needs to appropriate services/resources. Six patient navigators (4 anglophone and 2 francophone) were embedded in preexisting primary care clinics/health centres in urban and rural settings across the province. The role of the patient navigator was to increase participants’ knowledge of health and social services/resources related to dementia care, to improve access to these services/resources through in person and online patient navigation, and to improve communication pathways that promote the integration and coordination of care. A mixed methods approach was used to evaluate the program, which was piloted for 12 months (July 2022-July 2023). Data for this evaluation was collected from patient navigator charts, satisfaction surveys, and semi-structured interviews with participants and stakeholders involved in creating and implementing the program. Across sites, 150 participants took part in the study. Reasons for contacting the navigators included: connecting with social services, dementia specific information and resources, advance care planning, community resources, and home health care. Fifty-six participants returned post-intervention satisfaction surveys. The survey data indicated that 85% of participants were generally satisfied with services from the program. Seventy-eight percent of participants reported having greater knowledge of health and/or social services and resources because of the patient navigator and 76% of participants reported having greater access to health and/or social services and resources. Thirty-seven participants completed post-intervention interviews about their experiences with the program, and qualitative content analysis of this data is underway. Preliminary analysis identified the following themes: overall satisfaction with the program, supportive tasks, systemic barriers, and recommendations for program improvement. These results suggest that PN, embedded in existing primary care clinics/health centers, is beneficial for PWD and their care partners. Furthermore, patient navigation is a flexible model of care and can be easily adapted to different populations and regions. These findings support our aim to promote positive experiences with health and social care systems for this population and promote person-centred, integrated care.
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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 | 0,004 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,005 | 0,001 |
| Communication savante | 0,001 | 0,002 |
| Science ouverte | 0,002 | 0,008 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,005 | 0,001 |
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 ».