Understanding the scope of preventable acute care spending among patients with eating disorders
Notice bibliographique
Résumé
OBJECTIVE: The economic burden of eating disorders is substantial. One potential way to reduce costs, without sacrificing care, may be to target preventable (i.e., potentially unnecessary) acute care. This study sought to determine the amount and proportion of preventable and non-preventable acute care spending among individuals with eating disorders. METHOD: We undertook a population-based, cross-sectional study of all individuals over the age of 17 with eating disorders (diagnosed through hospitalization) in Ontario, Canada, to determine potentially preventable and non-preventable acute care spending. Preventable acute care (i.e., preventable emergency department visits and hospitalizations) was defined using previously validated algorithms. We undertook analyses for the full sample, by sex and by eating disorder diagnosis (anorexia nervosa, bulimia nervosa, eating disorder not otherwise specified, multiple). RESULTS: Among 7547 individuals with eating disorders, 15% of all acute care spending (i.e., $1.33 million) was considered preventable; this figure was higher for females (14%) and those with bulimia nervosa (21%). Among emergency department visits, 25% of visits were considered preventable; the largest proportions were for non-emergent (11%) and primary care treatable (10%) conditions. Among hospitalizations, 9% were considered preventable; the highest proportions of preventable care spending were for short-term diabetes complications (1.8%) and urinary tract infections (1.8%). DISCUSSION: Although the economic burden of eating disorders is substantial, there is some scope to decrease acute care spending among this patient population. Care coordination and improved access to primary care and disease prevention, particularly related to diabetes, may help prevent the occurrence of some acute care episodes. PUBLIC SIGNIFICANCE: Many jurisdictions have implemented strategies to reduce costs and improve the quality of care among patients with high health care needs, such as those with eating disorders; however, it is unclear whether any costs can be reduced and, if so, which costs. Cost-savings resulting from the reduction of unnecessary care could provide further economic justification for increased investment in outpatient care for individuals with eating disorders.
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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 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 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 ».