Age, multimorbidity and dementia with health care costs in older people in Alberta: a population-based retrospective cohort study
Notice bibliographique
Résumé
BACKGROUND: The growing burden associated with population aging, dementia and multimorbidity poses potential challenges for the sustainability of health systems worldwide. We sought to examine how the intersection among age, dementia and greater multimorbidity is associated with health care costs. METHODS: We did a retrospective population-based cohort study in Alberta, Canada, with adults aged 65 years and older between April 2003 and March 2017. We identified 31 morbidities using algorithms (30 algorithms were validated), which were applied to administrative health data, and assessed costs associated with hospital admission, provider billing, ambulatory care, medications and long-term care (LTC). Actual costs were used for provider billing and medications; estimated costs for inpatient and ambulatory patients were based on the Canadian Institute for Health Information's resource intensive weights and Alberta's cost of a standard hospital stay. Costs for LTC were based on an estimated average daily cost. RESULTS: There were 827 947 people in the cohort. Dementia was associated with higher mean annual total costs and individual mean component costs for almost all age categories and number of comorbidities categories (differences in total costs ranged from $27 598 to $54 171). Similarly, increasing number of morbidities was associated with higher mean total costs and component costs (differences in total costs ranged from $4597 to $10 655 per morbidity). Increasing age was associated with higher total costs for people with and without dementia, driven by increasing LTC costs (differences in LTC costs ranged from $115 to $9304 per age category). However, there were no consistent trends between age and non-LTC costs among people with dementia. When costs attributable to LTC were excluded, older age tended to be associated with lower costs among people with dementia (differences in non-LTC costs ranged from -$857 to -$7365 per age category). INTERPRETATION: Multimorbidity, older age and dementia were all associated with increased use of LTC and thus health care costs, but some costs among people with dementia decreased at older ages. These findings illustrate the complexity of projecting the economic consequences of the aging population, which must account for the interplay between multimorbidity and dementia.
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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) | 0,000 | 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 | 0,000 |
| 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 ».