Case management for individuals with complex care needs: Factors assisting and hindering implementation
Notice bibliographique
Résumé
Introduction: Case management (CM) is an effective integrated model of care for patients with chronic conditions and complex care needs, given the focus on improving patient engagement in healthcare and improving self-management skills. While CM often leads to positive outcomes, little is known about the factors which promote or hinder implementation. Objective: This study seeks to examine factors which facilitated and hindered the implementation of a 12-month CM intervention in primary care clinics for individuals with chronic conditions and complex care needs, and report outcomes from the perspective of patients, nurse case managers, clinic managers, and providers. Intervention: A CM intervention was delivered by a nurse case manager (NCM), which included four activities: patient needs assessment, care planning, coordination of services, and self-management support. Design: We employed a qualitative descriptive design, using a participatory approach. The implementation was co-designed and co-led by researchers, clinicians, and patient partners, in collaboration with primary care clinics in five Canadian provinces. Participatory approach: This study involved various stakeholders, including patient partners, clinicians, researchers, and decision-makers. Patient partners were active members of the research team and played a major role in the development and governance of the larger study. Data collection: Semi-structured interviews or focus groups were conducted with patients (n= 44) and care providers (n=23), including case managers, clinic managers and primary care providers. Data analysis: Analysis of interview data was conducted using inductive thematic analysis to identify factors which facilitated or hindered implementation and outcomes. Results: Facilitators of the implementation included a holistic collaborative team-based clinic, an engaged and supportive clinic manager, the active involvement of care providers, dedicated and protected time for NCMs to complete CM tasks, and patient readiness. The implementation was hindered at clinics where staff were not engaged, leading to low recruitment numbers and difficulties carrying out the intervention. NCMs who did not have set time in their schedules or did not integrate the CM duties into their regular role struggled to carry out the program. Difficulty coordinating with specialists and external services also acted as a barrier. A final barrier to implementation was lack of access to appropriate services for patients with complex mental health needs. Outcomes included improved patient health and wellbeing, enhanced professional collaboration, expanded professional practice, more appropriate and efficient use of health services, and increased patient satisfaction. Learnings: CM is increasingly being used internationally as a way to better integrate people centered care for patients with complex care needs. The findings from this study provide insight into what worked well in implementing a 12-month CM intervention, as well as areas for improvement. Next steps: The findings from this study will be used to spread and scale CM in primary care within various provinces and First Nations, Métis, and Inuit communities in Canada over the next five years
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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 | 0,021 | 0,131 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,005 | 0,003 |
| Communication savante | 0,004 | 0,002 |
| Science ouverte | 0,002 | 0,004 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,005 | 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 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 ».