Implementation and assessment of a provincial early palliative care initiative for patients with pancreatic cancer.
Notice bibliographique
Résumé
e18742 Background: Early palliative care (EPC) referral reduces health care costs & improves quality of life and survival in some advanced cancers. One barrier to EPC is hesitancy of care providers to refer. In April 2022, our provincial cancer centre (CCMB) implemented a clinical nurse specialist (CNS)-led intervention for patients with advanced pancreatic cancer (PANC), circumventing known barriers. New PANC referrals received at the centralized referral office are triaged by an oncologist & concurrently referred to the CNS. CNS consultation focuses on physical & psychological symptoms, medication review, patient/family coping, & goals of care. Education is provided on PANC diagnosis, prognosis, symptoms, potential treatment options, navigating the cancer system & community palliative care/hospice supports, with close collaboration with the patient’s primary care provider. The primary aim of this study is to assess the impact of the CNS role on referral to multidisciplinary palliative care/hospice services within 8 weeks of diagnosis. Methods: We compared patients with PANC in the pre-implementation period (April 1, 2021 to December 31, 2021) to the post-implementation period (April 1, 2022 to December 31, 2022). Patients were identified using the Manitoba Cancer Registry & the CNS clinical database. Descriptive statistics were used to report quality measures. A one sample test of proportions was used to compare EPC referral in the pre- & post-implementation periods. Results: In the pre-implementation period, 64 patients were referred to CCMB with PANC. Fifty-nine (92%) were diagnosed via biopsy, 52 (81%) had consultation with a medical oncologist, 32 (50%) received chemotherapy. Forty-four (69%) were referred to a palliative care/hospice program. In the post implementation period, 88 patients were referred to CCMB. Eighty-five (97%) accepted a consultation with the CNS, with a median time to meeting of 6 days (range, 0-18), and 75% of patients seen within 10 days. After CNS consultation, 28 (32%) declined biopsy, oncology appointment or both. Overall, sixty-three (72%) patients in this cohort had a diagnostic biopsy, 59 (67%) had a consultation with a medical oncologist, 29 (33%) received chemotherapy. Fifty-nine (67%) were referred to a palliative care/hospice program. In the pre-implementation period, 24 (38%) patients were referred to palliative care/hospice within 8 weeks of diagnosis, compared to 44 (50%) in the post-implementation period (p = 0.0154). Conclusions: This novel approach demonstrates CNS assessment & education soon after diagnosis of PANC, at the time of referral to CCMB, results in an increased proportion of patients being referred for community-based palliative care/hospice within 8 weeks of diagnosis. Exploring patient goals early may also spare patients from invasive & timely procedures, allowing those with a life limiting illness to focus on quality of life.
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 | 0,006 | 0,017 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,003 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,003 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 ».