Associations between patient characteristics and delayed acute care discharge post-hip fracture surgery: a cohort study using linked health administrative data in Ontario, Canada
Notice bibliographique
Résumé
BACKGROUND: Older patients frequently experience delays in discharge post-hip fracture surgery. Our study aimed to describe the sociodemographic and clinical characteristics of patients who had a surgical repair for a hip fracture and to examine the associations between these characteristics and delayed discharge (> 6 days post-surgery) for frail vs. non frail patients. METHODS: We conducted a retrospective population-based cohort study using routinely collected health administrative data housed at ICES. The study population included all individuals aged 50 to 105 years with a hip fracture who had a surgical repair in Ontario, Canada between January 1, 2015, and December 31, 2021. We used descriptive statistics and multivariable logistic regression models to characterize the association of patient socio-demographics, baseline health, and characteristics of the acute care episode with delayed discharge between non-frail and frail groups. RESULTS: We included 74,838 patients, with a mean age of 80.9 (SD 10.7) years, among which 37,234 (49.8%) had a delayed discharge. Some factors increased the odds of delayed discharge in both non-frail and frail groups included prior location in complex continuing care (non-frail OR 1.64, 95% CI 1.14,2.35, P = 0.007; frail OR 2.33, 95% CI 1.70,3.21, P < 0.0001), as well as prior residence in the community with home care (non-frail OR 9.71, 95% CI 8.89,10.6, P < 0.0001; frail OR 13.8, 95% CI 12.0,15.8, P < 0.0001), or without home care (non-frail OR 5.81, 95% CI 5.35,6.32, P < 0.0001; frail OR 4.60, 95% CI 4.14,5.11, P < 0.0001) compared to long-term care as well as residing in a neighbourhood with a higher Racialized and Newcomer Populations Index quintile (non-frail OR 1.45, 95% CI 1.37,1.55, P < 0.0001; frail OR 1.90, 95% CI 1.68,2.16, P < 0.0001). Factors that reduced the odds of delayed discharge in both non-frail and frail groups included individuals living in rural areas (non-frail OR 0.44, 95% CI 0.42,0.47, P < 0.0001; frail OR 0.41, 95% CI 0.36,0.46, P < 0.0001), or having previous fragility fractures (non-frail OR 0.44, 95% CI 0.40,0.49, P < 0.0001; frail OR 0.56, 95% CI 0.51,0.62, P < 0.0001). However, patients in the non-frail group were more likely to be delayed for the presence of comorbidities including mood or mental health conditions (OR 1.22, 95% CI 1.16,1.28, P < 0.0001), stroke (OR 1.46, 95% CI 1.28,1.67, P < 0.0001), chronic obstructive pulmonary disease (OR 1.35, 95% CI 1.24,1.47, P < 0.0001), dementia (OR 1.41, 95% CI 1.34,1.48, P < 0.0001), or diabetes (OR 1.26, 95% CI 1.20,1.32, P < 0.0001). Factors that reduced the odds of delayed discharge in the non-frail group were female sex (OR 0.87, 95% CI 0.83,0.90, P < 0.0001), or having cancer (OR 0.94, 95% CI 0.90,0.98, P = 0.0089). CONCLUSION: Delayed discharge was common after hip fracture surgery in both the non-frail and frail groups. Preoperative residential status, comorbidities and sociodemographic factors are associated with delayed discharge. These data can help to inform strategies to improve timely discharge from acute care and the overall outcomes of the older adult hip fracture population.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 tête enseignante, 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 ».