Alternative community-based models of care for young people with anorexia nervosa: the CostED national surveillance study
Notice bibliographique
Résumé
Background Evidence suggests that investing in specialist eating disorders services for young people with anorexia nervosa could have important implications for the NHS, with the potential to improve health outcomes and reduce costs through reductions in the number and length of hospital admissions. Objectives The primary objectives were to evaluate the costs and cost-effectiveness of alternative community-based models of service provision for young people with anorexia nervosa and to model the impact of potential changes to the provision of specialist services. Design Observational surveillance study using the Child and Adolescent Psychiatry Surveillance System. Setting Community-based secondary or tertiary child and adolescent mental health services (CAMHS) in the UK and the Republic of Ireland. Participants A total of 298 young people aged 8–17 years in contact with CAMHS for a first episode of anorexia nervosa in accordance with Diagnostic and Statistical Manual of Mental Disorders , Fifth Edition, diagnostic criteria. Interventions Community-based specialist eating disorders services and generic CAMHS. Main outcome measures Children’s Global Assessment Scale (CGAS) score (primary outcome) and percentage of median expected body mass index (BMI) for age and sex (%mBMI) (secondary outcome) were assessed at baseline and at 6 and 12 months. Data sources Data were collected by clinicians from clinical records. Results Total costs incurred by young people initially assessed in specialist eating disorders services were not significantly different from those incurred by young people initially assessed in generic CAMHS. However, adjustment for baseline covariates resulted in observed differences favouring specialist services (costs were lower, on average) because of the significantly poorer clinical status of the specialist group at baseline. At the 6-month follow-up, mean %mBMI was significantly higher in the specialist group, but no other significant differences in outcomes were evident. Cost-effectiveness analyses suggest that initial assessment in a specialist service has a higher probability of being cost-effective than initial assessment in generic CAMHS, as determined by CGAS score and %mBMI. However, no firm conclusion can be drawn without knowledge of society’s willingness to pay for improvements in these outcomes. Decision modelling did not support the hypothesis that changes to the provision of specialist services would generate savings for the NHS, with results suggesting that cost per 10-point improvement in CGAS score (improvement from one CGAS category to the next) varies little as the percentage of participants taking the specialist or generic pathway is varied. Limitations Follow-up rates were lower than expected, but the sample was still larger than has been achieved to date in RCTs carried out in this population in the UK, and an exploration of the impact of missing cost and outcome data produced very similar results to those of the main analyses. Conclusions The results of this study suggest that initial assessment in a specialist eating disorders service for young people with anorexia nervosa may have a higher probability of being cost-effective than initial assessment in generic CAMHS, although the associated uncertainty makes it hard to draw firm conclusions. Although costs and outcomes were similar, young people in specialist services were more severely ill at baseline, suggesting that specialist services were achieving larger clinical effectiveness gains without the need for additional expenditure. The results did not suggest that providing more specialist services would save money for the NHS, given similar costs and outcomes, so decisions about which service type to fund could be made with reference to other factors, such as the preferences of patients and carers. Future work Data on measures of quality of life capable of generating quality-adjusted life-years are needed to confirm the cost-effectiveness of specialist services. Trial registration Current Controlled Trials ISRCTN12676087. Funding This project was funded by the National Institute for Health Research (NIHR) Health Services and Delivery Research programme and will be published in full in Health Services and Delivery Research ; Vol. 7, No. 37. See the NIHR Journals Library website for further project information.
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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 | 0,005 | 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 | 0,003 | 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 ».