Cost of Utilising Maternal Health Services in Low- and Middle-Income Countries: A Systematic Review
Notice bibliographique
Résumé
BACKGROUND: Cost is a major barrier to maternal health service utilisation for many women in low- and middle-income countries (LMICs). However, comparable evidence of the available cost data in these countries is limited. We conducted a systematic review and comparative analysis of costs of utilising maternal health services in these settings. METHODS: We searched peer-reviewed and grey literature databases for articles reporting cost of utilising maternal health services in LMICs published post-2000. All retrieved records were screened and articles meeting the inclusion criteria selected. Quality assessment was performed using the relevant cost-specific criteria of the Consolidated Health Economic Evaluation Reporting Standards (CHEERS) checklist. To guarantee comparability, disaggregated costs data were inflated to 2019 US dollar equivalents. Total adjusted costs and cost drivers associated with utilising each service were systematically compared. Where heterogeneity in methods or non-disaggregated costs was observed, narrative synthesis was used to summarise findings. RESULTS: Thirty-six studies met our inclusion criteria. Many of the studies costed multiple services. However, the most frequently costed services were utilisation of normal vaginal delivery (22 studies), caesarean delivery (13), and antenatal care (ANC) (10). The least costed services were post-natal care (PNC) and post-abortion care (PAC) (5 each). Studies used varied methods for data collection and analysis and their quality ranged from low to high with most assessed as average or high. Generally, across all included studies, cost of utilisation progressively increased from ANC and PNC to delivery and PAC, and from public to private providers. Medicines and diagnostics were main cost drivers for ANC and PNC while cost drivers were variable for delivery. Women experienced financial burden of utilising maternal health services and also had to pay some unofficial costs to access care, even where formal exemptions existed. CONCLUSION: Consensus regarding approach for costing maternal health services will help to improve their relevance for supporting policy-making towards achieving universal health coverage. If indeed the post-2015 mission of the global community is to "leave no one behind," then we need to ensure that women and their families are not facing unnecessary and unaffordable costs that could potentially tip them into poverty.
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 | 0,002 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,003 | 0,000 |
| Bibliométrie | 0,001 | 0,000 |
| 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 | 0,000 |
| 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 ».