Willingness to pay for Social Health Insurance and associated factors among Public Civil Servants in Ethiopia: A systematic review and meta-analysis
Notice bibliographique
Résumé
BACKGROUND: The provision of equitable and accessible healthcare is one of the goals of universal health coverage. However, due to high out-of-pocket payments, people in the world lack sufficient health services, especially in developing countries. Thus, many low and middle-income countries introduced different prepayment mechanisms to reduce large out-of-pocket payments and overcome financial barriers to accessing health care. Though many studies were conducted on willingness to pay for social health insurance in Ethiopia, there is no aggregated data at the national level. Therefore, this systematic review and meta-analysis aimed to estimate the pooled magnitude of willingness to pay for social health insurance and its associated factors among public servants in Ethiopia. METHOD: Studies conducted before June 1, 2022, were retrieved from electronic databases (PubMed/Medline, Science Direct, African Journals Online, Google Scholar, and Web of Science) as well as from Universities' digital repositories. Data were extracted using a data extraction format prepared in Microsoft Excel and the analysis was performed using STATA 16 statistical software. The quality of the included studies was assessed using the Newcastle-Ottawa Scale for cross-sectional studies. To evaluate publication bias, a funnel plot, and Egger's regression test were utilized. The study's heterogeneity was determined using Cochrane Q test statistics and the I2 test. To determine the pooled effect size, odds ratio, and 95% confidence intervals across studies, the DerSimonian and Laird random-effects model was used. Subgroup analysis was conducted by region, sample size, and publication year. The influence of a single study on the whole estimate was determined via sensitivity analysis. RESULT: To estimate the pooled magnitude of willingness to pay for the Social Health insurance scheme in Ethiopia, twenty articles with a total of 8744 participants were included in the review. The pooled magnitude of willingness to pay for Social Health Insurance in Ethiopia was 49.62% (95% CI: 36.41-62.82). Monthly salary (OR = 6.52; 95% CI:3.67,11.58), having the degree and above educational status (OR = 5.52; 95%CI:4.42,7.17), large family size(OR = 3.69; 95% CI:1.10,12.36), having the difficulty of paying the bill(OR = 3.24; 95%CI: 1.51, 6.96), good quality of services(OR = 4.20; 95%CI:1.97, 8.95), having favourable attitude (OR = 5.28; 95%CI:1.45, 19.18) and awareness of social health insurance scheme (OR = 3.09;95% CI:2.12,4.48) were statistically associated with willingness to pay for Social health insurance scheme. CONCLUSIONS: In this review, the magnitude of willingness to pay for Social Health insurance was low among public Civil servants in Ethiopia. Willingness to pay for Social Health Insurance was significantly associated with monthly salary, educational status, family size, the difficulty of paying medical bills, quality of healthcare services, awareness, and attitude towards the Social Health Insurance program. Hence, it's recommended to conduct awareness creation through on-the-job training about Social Health Insurance benefit packages and principles to improve the willingness to pay among public servants.
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 enseignantsNi 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.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,004 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,015 | 0,001 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 tête enseignante, 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 ».