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Enregistrement W6901996825 · doi:10.6084/m9.figshare.21710055.v2

Socioeconomic burden of schizophrenia: a targeted literature review of types of costs and associated drivers across 10 countries

2022· article· en· W6901996825 sur OpenAlexaboutno aff

Notice bibliographique

RevueFigshare · 2022
Typearticle
Langueen
DomaineMedicine
ThématiqueSchizophrenia research and treatment
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésIndirect costsTotal costEconomic costCost driverStakeholderCost–benefit analysisSocioeconomic statusCost databaseCost estimate

Résumé

récupéré en direct d'OpenAlex

Schizophrenia has the highest median societal cost per patient of all mental disorders. This review summarizes the different costs/cost drivers (cost components) associated with schizophrenia in 10 countries, including all cost types and stakeholder perspectives, and highlights aspects of disease associated with greatest costs. Targeted literature review based on a search of published research from 2006 to 2021 in the United States (US), United Kingdom (UK), France, Germany, Italy, Spain, Canada, Japan, Brazil, and China. Sixty-four published articles (primary studies and literature reviews) were included. Comprehensive data were available on costs in schizophrenia overall, with very limited data for individual countries except the US. Most data is related to direct and not indirect costs, with extremely scarce data for several key cost components (adverse events, suicide, long-term care). Total schizophrenia-related per person per year (PPPY) costs were $2,004–94,229, with considerable variability among countries. Indirect costs were the main cost driver (50–90% of all costs), ranging from $1,852 to $62,431 PPPY. However, indirect costs are not collected systematically or incorporated in health technology assessments. Total schizophrenia-related PPPY direct costs were $4,394–31,798, with inpatient cost as the main cost driver (∼20–99% of direct costs). Intangible costs were not reported. Despite limited evidence, total schizophrenia-related costs were higher in patients with than without negative symptoms, largely due to increased costs of medication and medical visits. As this was not a systematic review, prioritization of studies may have resulted in exclusion of potentially relevant data. All costs were converted to USD but not corrected for inflation or subjected to a gross domestic product deflator. Direct costs are most commonly reported in schizophrenia. The substantial underreporting of indirect and intangible costs undervalues the true economic burden of schizophrenia from a payer, patient, and societal perspective. The true costs of diseases such as schizophrenia extend far beyond the obvious direct costs of hospital visits, outpatient appointments and medications to include indirect costs such as loss of productivity among patients and caregivers due to unemployment, early retirement and premature death. This review of literature published between 2006 and 2021 reveals that the indirect costs of schizophrenia actually account for between 50% and 90% of all costs, but are often not taken into account in healthcare planning. In addition, intangible costs, including the pain, suffering, stress, and anxiety experienced by patients and caregivers due to schizophrenia have not been reported in the literature. Costs were also higher for patients with negative symptoms of schizophrenia (where patients appear withdrawn and lacking in emotion, with few social relationships) compared with those with positive symptoms (including delusions or hallucinations). This is largely due to the greater costs for medications and medical visits among patients with negative symptoms. In summary, this review demonstrates that the true cost of schizophrenia, including direct, indirect, and intangible costs, is likely to be substantially higher than the values for the cost of disease currently reported.

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 machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,004
score de la tête « metaresearch » (Gemma)0,012
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Revue systématique · Signal consensuel: Revue systématique
GenreSignal candidat: Synthèse · Signal consensuel: Synthèse
Score de désaccord entre enseignants0,024
Score d'incertitude au seuil0,034

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0040,012
Méta-épidémiologie (sens strict)0,0010,001
Méta-épidémiologie (sens large)0,0030,005
Bibliométrie0,0240,025
Études des sciences et des technologies0,0010,000
Communication savante0,0020,002
Science ouverte0,0010,001
Intégrité de la recherche0,0010,001
Charge utile insuffisante (le modèle a refusé de juger)0,0030,000

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 Opus0,014
Tête enseignante GPT0,290
Écart entre enseignants0,276 · 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 source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeRevue systématique
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

Citations0
Publié2022
Routes d'admission1
Résumé présentoui

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