Association between palliative care and healthcare outcomes among adults with terminal non-cancer illness: population based matched cohort study
Notice bibliographique
Résumé
Abstract Objective To measure the associations between newly initiated palliative care in the last six months of life, healthcare use, and location of death in adults dying from non-cancer illness, and to compare these associations with those in adults who die from cancer at a population level. Design Population based matched cohort study. Setting Ontario, Canada between 2010 and 2015. Participants 113 540 adults dying from cancer and non-cancer illness who were given newly initiated physician delivered palliative care in the last six months of life administered across all healthcare settings. Linked health administrative data were used to directly match patients on cause of death, hospital frailty risk score, presence of metastatic cancer, residential location (according to 1 of 14 local health integration networks that organise all healthcare services in Ontario), and a propensity score to receive palliative care that was derived by using age and sex. Main outcome measures Rates of emergency department visits, admissions to hospital, and admissions to the intensive care unit, and odds of death at home versus in hospital after first palliative care visit, adjusted for patient characteristics (such as age, sex, and comorbidities). Results In patients dying from non-cancer illness related to chronic organ failure (such as heart failure, cirrhosis, and stroke), palliative care was associated with reduced rates of emergency department visits (crude rate 1.9 (standard deviation 6.2) v 2.9 (8.7) per person year; adjusted rate ratio 0.88, 95% confidence interval 0.85 to 0.91), admissions to hospital (crude rate 6.1 (standard deviation 10.2) v 8.7 (12.6) per person year; adjusted rate ratio 0.88, 95% confidence interval 0.86 to 0.91), and admissions to the intensive care unit (crude rate 1.4 (standard deviation 5.9) v 2.9 (8.7) per person year; adjusted rate ratio 0.59, 95% confidence interval 0.56 to 0.62) compared with those who did not receive palliative care. Additionally increased odds of dying at home or in a nursing home compared with dying in hospital were found in these patients (n=6936 (49.5%) v n=9526 (39.6%); adjusted odds ratio 1.67, 95% confidence interval 1.60 to 1.74). Overall, in patients dying from dementia, palliative care was associated with increased rates of emergency department visits (crude rate 1.2 (standard deviation 4.9) v 1.3 (5.5) per person year; adjusted rate ratio 1.06, 95% confidence interval 1.01 to 1.12) and admissions to hospital (crude rate 3.6 (standard deviation 8.2) v 2.8 (7.8) per person year; adjusted rate ratio 1.33, 95% confidence interval 1.27 to 1.39), and reduced odds of dying at home or in a nursing home (n=6667 (72.1%) v n=13 384 (83.5%); adjusted odds ratio 0.68, 95% confidence interval 0.64 to 0.73). However, these rates differed depending on whether patients dying with dementia lived in the community or in a nursing home. No association was found between healthcare use and palliative care for patients dying from dementia who lived in the community, and these patients had increased odds of dying at home. Conclusions These findings highlight the potential benefits of palliative care in some non-cancer illnesses. Increasing access to palliative care through sustained investment in physician training and current models of collaborative palliative care could improve end-of-life care, which might have important implications for health policy.
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 | 0,001 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 ».