COMPARATIVE STUDY OF FAIR FINANCING IN THE HEALTH INSURANCE
Notice bibliographique
Résumé
Introduction: Fair financing contribution is one of the main objectives the healthcare systems in the world. Insurance system is one of the most common methods of financial protection against the cost of healthy people is considered. This study aimed to evaluate the comparative insurance system in different countries were performed. Methods: This comparative study was conducted in 2017. First, a comprehensive literature search was conducted through relevant and valid databases and websites to extract scientific evidence. After the screening of findings, Data related to the fairness financing, including the out of pocket, catastrophic payment and fair financing contribution was extracted. Garden classification framework used to match the indicators with models of health insurance. Results: In countries studied, four model finance and insurance including: national health insurance (NHI), national medical system (NHS), social health insurance (SHI) and private insurance was used. France and Australia are the countries where the two models are used simultaneously. The lowest rate of pay out of pocket and catastrophic health expenditure for households in France (6 and 0.01 percent), which uses public and private health insurance model. Britain, Denmark, Canada and Germany, respectively, have the highest indices were fair participation in financing. Conclusion: According to the study it can be concluded that social insurance, national insurance and national health systems can have a good performance in financial protection of the population, So can say insurance system establishing a significant role in financial protection against the cost of people's health. Of course is to be mentioned for choose the model insurance countries should be based on infrastructure and resources available in every country so well able to play its role. Introduction: Fair financing contribution is one of the main objectives the healthcare systems in the world. Insurance system is one of the most common methods of financial protection against the cost of healthy people is considered. This study aimed to evaluate the comparative insurance system in different countries were performed.Method: This comparative study was conducted in 2017. First, a comprehensive literature search was conducted through relevant and valid databases and websites to extract scientific evidence. After the screening of findings, Data related to the fairness financing was extracted. Garden classification framework used to match the indicators with models of health insurance.Result:In countries studied, four model finance and insurance including: national health insurance (NHI), national medical system (NHS), social health insurance (SHI) and private insurance was used. The lowest rate of pay out of pocket and catastrophic health expenditure for households in France (6 and 0.01 percent), which uses public and private health insurance model. Britain, Denmark, Canada and Germany, respectively, have the highest indices were fair participation in financing.Conclusion: According to the study it can be concluded that social insurance, national insurance and national health systems can have a good performance in financial protection of the population, So can say insurance system establishing a significant role in financial protection against the cost of people's health. Of course is to be mentioned for choose the model insurance countries should be based on infrastructure and resources available in every country so well able to play its role.
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 | 0,015 | 0,045 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,007 | 0,006 |
| Études des sciences et des technologies | 0,001 | 0,002 |
| Communication savante | 0,003 | 0,003 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,008 | 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 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 ».