SHA-Based National Health Accounts in Thirteen OECD Countries
Notice bibliographique
Résumé
Australia No data available for HF.2.4 (Non-profit institutions) Canada No data available for HF.2.4 and HF.2.5 (Corporations) Denmark No data available for HF.2.4 and HF.2.5. Long-term nursing care (LTC) is overestimated: includes accommodation costs in all residential care facilities. Germany Hungary LTC is underestimated: it includes only LTC services financed by compulsory health insurance and cost of health manpower employed in residential care facilities (financed by local governments). Home care provided by households is not included. Japan No data available for HF.2.4. Certain services (private room charges, massage, acupuncture, etc.) not covered by insurance cannot be estimated. Korea LTC provided outside the nationally defined health sector is not included. Mexico LTC provided outside the nationally defined health sector is not included. Netherlands No separate data presented for HF.2.4 and HF.2.5 due to quality of the separate items Poland LTC provided outside the nationally defined health sector is only partially included. Spain No data available for HF.2.5. LTC provided outside the nationally defined health sector is not included. Switzerland No data available for HF.2.5. LTC figure is in the upper range, partly because it includes overall costs of institutions where expenditure for nursing care, surveillance and ADL represents at least half of the total expenditure. Turkey No data available for long-term care (HC.3) and home care, furthermore providers outside the nationally defined health sector (HP.7 and HP.9) are not included. Box A1 Main departures from ICHA-HF Australia No data available for HF.2.4 (Non-profit institutions) Canada No data available for HF.2.4 and HF.2.5 (Corporations) Additional category is created for "Non-consumption expenditure" Denmark No data available for HF.2.4 and HF.2.5 Germany Hungary Japan No data available for HF.2.4 Under Private insurance (HF.2.2) only administration is reported. (Expenditure on benefits could not be separated from households.) Households' expenditure on some services (private room charges, massage, acupuncture, etc.) not covered by insurance are not included. Korea Central (HF.1.1.1) and local (HF.1.1.2) governments are not separately reported. Mexico Payments by municipal governments are not included No data available for HF.2.4 and HF.2.5 Netherlands No data presented for HF.2.4 and HF.2.5 due to quality of the separate items Poland Expenditure by corporation includes estimates for debts by health care providers to suppliers of medical and other goods used in producing health services. Spain No data available for HF.2.5 Switzerland No data available for HF.2.5 Turkey Note: This table presents information on whether all financing agents were taken into account. It does not, however, show whether all expenditure by a particular financing agent was accounted for. (This information is provided in Box A3.)
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 enseignantsNi 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.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,018 | 0,042 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,003 | 0,001 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,034 | 0,020 |
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 source (Gemma direct ou Codex distillé), 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 ».