Family physicians supporting patients with palliative care needs within the Patient Medical Home in the community: An Appreciative Inquiry qualitative study
Notice bibliographique
Résumé
ABSTRACT Objectives Canadians want to live and die in their home communities. Unfortunately, Canada has the highest proportion of deaths in acute care facilities as compared to other developed nations. This study aims to identify the essential components required to best support patients and families with palliative care needs in their communities to inform system changes and empower family physicians (FPs) in providing community-based palliative care for patients. Design Appreciative Inquiry (AI) methodology with individual interviews. Interview transcripts were analyzed iteratively for emerging themes and used to develop “possibility statements” to frame discussion in subsequent focus groups. A conceptual framework emerged to describe the “destiny” state as per AI methods. Setting Family physicians, palliative home care providers, patients and bereaved caregivers were recruited in the urban and surrounding rural health authority zones of Calgary, Canada. Participants 9 females and 9 males FPs (range of practice years 2-42) in interviews; 8 bereaved caregivers, 1 patient, 26 Palliative Home Care team members in focus groups. Interviews and focus groups were recorded digitally and transcribed with consent. Results The identified themes that transcended all three groups created the foundation for the conceptual framework. Enhanced communication and fostering team relationships between all care providers with the focus on the patient and caregivers was the cornerstone concept. The family physician/patient relationship must be protected and encouraged by all care providers, while more system flexibility is needed to respond more effectively to patients. These concepts must exist in the context that patients and caregivers need more education regarding the benefits of palliative care, while increasing public discourse about mortality. Conclusions Key areas were identified for how the patient’s team can work together effectively to improve the patient and caregiver palliative care journey in the community with the cornerstone element of building on the trusting FP-patient longitudinal relationship. Strengths and limitations of this study This study uses Appreciative Inquiry qualitative methods to identify the essential components required to best support patients and families with palliative care needs in their communities. Multiple perspectives recruited including: community-based family physicians, palliative home care clinicians, patients, and bereaved caregivers. Analysis was focused on the family physicians’ interviews to derive “possibility statements” and used to frame the focus groups with the other groups of participants. Generalisability may be limited due to the lack of diversity in participants recruited for the patients and bereaved caregivers in terms of ethnicity, age, and gender. Patients and caregivers may have been reluctant to volunteer for this study as it involved discussing palliative care.
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 | 0,012 | 0,019 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,002 | 0,002 |
| Études des sciences et des technologies | 0,015 | 0,009 |
| Communication savante | 0,004 | 0,003 |
| Science ouverte | 0,002 | 0,005 |
| Intégrité de la recherche | 0,002 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 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 ».