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Enregistrement W6963863150 · doi:10.22034/smsj.2023.173203

Comparative study of care expenditures for private and public health

2023· article· en· W6963863150 sur OpenAlexaboutno aff

Notice bibliographique

RevueDOAJ (DOAJ: Directory of Open Access Journals) · 2023
Typearticle
Langueen
DomaineHealth Professions
ThématiqueGlobal Health Care Issues
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésHealth carePublic healthWorkforceHuman capitalDeveloping countryOrder (exchange)Panel dataHealth policyHealth promotion

Résumé

récupéré en direct d'OpenAlex

Introduction: Health is one of the most important factors of human capital. Health affects labor supply both qualitatively (higher productivity) and quantitatively (not missing working days due to illness). Most countries have experienced a rapid growth in their health care costs in the past years. But nfortunately, some countries still think that any activity in the field of improving health will increase costs It should be noted that the skilled workforce can be the focus of development and increase production when it has physical health and a cheerful spirit. Although health expenses and then human capital play a significant role in the development of societies, however, the factors affecting health expenses and the impact of each of its constituent factors have not been well investigated and analyzed.Therefore, according to the increasing growth of the expenses of this sector, it seems important to identify the components that affect the health expenses.Therefore, in order to properly plan in the health-economic fields, one should have a precise and accurate understanding of the factors affecting health expenditures.The same subject led the current research to investigate the comparative-comparative factors affecting private and public health care expenditures in selected developed and developing countries.Methodology: This research used time series data for the period 2000-2019 and based on the panel data method, the variables affecting health expenditure for the private and public sectors of 15 selected developed countries including: Switzerland, Australia , Canada, Netherlands, Singapore, Germany, Sweden, Italy, USA, Norway, France, Japan, Denmark, Austria and Belgium; And also 15 selected developing countries including: Islamic Republic of Iran, Turkey, Georgia, Azerbaijan, China, Serbia, Ukraine, Peru, Lebanon, Panama, Albania, Armenia, Cuba, Mexico and Costa Rica will be analyzed and investigated. Variables of gross domestic product (GDP), life expectancy (EXP), population over 65 years old (POP), population under 14 years old (age), urbanization rate (URB), literacy rate (EDU), out-of-pocket payments (OOP) And foreign aid (ODA) is one of the influencing factors on health care expenses in this research. Also, the statistics and figures used in this research were extracted from the World Bank and the World Atlas (Knoema).Results and Discussion: The variable coefficient of GDP, which is one of the effective variables in private and public health care expenditures in developed and developing countries, is positive and significant; the estimated coefficient of life expectancy variable is positive and significant.The impact of the variable population over 65 years old in developed and developing countries in both private and public sectors has been positive and significant.Also, the population under 14 years of age in both groups of developed and developing countries had a negative and significant relationship with health care expenditures in both private and public sectors; Also, the variable impact of urbanization rate in developed and developing countries has been positive and significant in both private and public sectors;The effect of the out-of-pocket variable has been negative and significant in developed countries and positive and significant in developing countries .And the variable coefficient of foreign aid in developing countries is negative and significant. And finally, the results of this study showed that there is no significant statistical relationship between the literacy rate and health costs.Conclusion: Considering the share of public and private sectors in health expenditures in developing countries, governments, as the largest public institution, should take the necessary measures to increase the share of public sector in health expenditures.

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)0,001
score de la tête « metaresearch » (Gemma)0,004
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,036
Score d'incertitude au seuil0,071

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0010,004
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,001
Bibliométrie0,0020,005
Études des sciences et des technologies0,0000,000
Communication savante0,0010,000
Science ouverte0,0000,001
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0040,000

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 Opus0,622
Tête enseignante GPT0,709
Écart entre enseignants0,087 · 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'étudeObservationnel
Domainenon disponible
GenreEmpirique

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
Publié2023
Routes d'admission1
Résumé présentoui

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