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Enregistrement W2099757990 · doi:10.1177/1355819614566832

Integrating funds for health and social care: an evidence review

2015· review· en· W2099757990 sur OpenAlexaboutno aff
Anne Mason, Maria Goddard, Helen Weatherly, Martin Chalkley

Notice bibliographique

RevueJournal of Health Services Research & Policy · 2015
Typereview
Langueen
DomaineHealth Professions
ThématiqueInterprofessional Education and Collaboration
Établissements canadiensnon disponible
Organismes subventionnairesNational Institute for Health and Care Research
Mots-clésIntegrated careHealth careAgency (philosophy)Unintended consequencesEmpirical evidenceSocial careCost–benefit analysisBusinessPublic economicsMedicineActuarial scienceNursingEconomicsPolitical scienceEconomic growthSociology

Résumé

récupéré en direct d'OpenAlex

OBJECTIVES: Integrated funds for health and social care are one possible way of improving care for people with complex care requirements. If integrated funds facilitate coordinated care, this could support improvements in patient experience, and health and social care outcomes, reduce avoidable hospital admissions and delayed discharges, and so reduce costs. In this article, we examine whether this potential has been realized in practice. METHODS: We propose a framework based on agency theory for understanding the role that integrated funding can play in promoting coordinated care, and review the evidence to see whether the expected effects are realized in practice. We searched eight electronic databases and relevant websites, and checked reference lists of reviews and empirical studies. We extracted data on the types of funding integration used by schemes, their benefits and costs (including unintended effects), and the barriers to implementation. We interpreted our findings with reference to our framework. RESULTS: The review included 38 schemes from eight countries. Most of the randomized evidence came from Australia, with nonrandomized comparative evidence available from Australia, Canada, England, Sweden and the US. None of the comparative evidence isolated the effect of integrated funding; instead, studies assessed the effects of 'integrated financing plus integrated care' (i.e. 'integration') relative to usual care. Most schemes (24/38) assessed health outcomes, of which over half found no significant impact on health. The impact of integration on secondary care costs or use was assessed in 34 schemes. In 11 schemes, integration had no significant effect on secondary care costs or utilisation. Only three schemes reported significantly lower secondary care use compared with usual care. In the remaining 19 schemes, the evidence was mixed or unclear. Some schemes achieved short-term reductions in delayed discharges, but there was anecdotal evidence of unintended consequences such as premature hospital discharge and heightened risk of readmission. No scheme achieved a sustained reduction in hospital use. The primary barrier was the difficulty of implementing financial integration, despite the existence of statutory and regulatory support. Even where funds were successfully pooled, budget holders' control over access to services remained limited. Barriers in the form of differences in performance frameworks, priorities and governance were prominent amongst the UK schemes, whereas difficulties in linking different information systems were more widespread. Despite these barriers, many schemes - including those that failed to improve health or reduce costs - reported that access to care had improved. Some of these schemes revealed substantial levels of unmet need and so total costs increased. CONCLUSIONS: It is often assumed in policy that integrating funding will promote integrated care, and lead to better health outcomes and lower costs. Both our agency theory-based framework and the evidence indicate that the link is likely to be weak. Integrated care may uncover unmet need. Resolving this can benefit both individuals and society, but total care costs are likely to rise. Provided that integration delivers improvements in quality of life, even with additional costs, it may, nonetheless, offer value for money.

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 distillée sur la base complète

Imitation des enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,025
score de la tête « metaresearch » (Gemma)0,001
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMéta-épidémiologie (sens strict), Études des sciences et des technologies, Intégrité de la recherche
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: aucune
GenreSignal candidat: Synthèse · Signal consensuel: Synthèse
Score de désaccord entre enseignants0,656
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0250,001
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0030,000
Bibliométrie0,0010,002
Études des sciences et des technologies0,0030,000
Communication savante0,0000,001
Science ouverte0,0010,000
Intégrité de la recherche0,0000,003
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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.

Tête enseignante Opus0,442
Tête enseignante GPT0,723
Écart entre enseignants0,281 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Devis d'étudeSans objet
Domainenon disponible
GenreSynthèse

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations134
Publié2015
Routes d'admission1
Résumé présentoui

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