The logistics of voucher management: the underreported component in family planning voucher discussions
Notice bibliographique
Résumé
BACKGROUND: The purpose of health care vouchers or coupons is to receive a health service in exchange which is fully or partially subsidized, such as any treatment offered for communicable disease; for immunization; antenatal care-/postnatal care-related maternal health services; a family planning (FP) service; or to get a health commodity like a medicine. Vouchers are targeted for a group of people who can benefit the most such as on the basis of poverty ranking, marginalized or living in rural areas. According to the World Health Organization, voucher schemes in the area of sexual and reproductive health are considered of high value if they are implemented to address the issues of contraceptive commodity or service unavailability or to address the barriers to access such services through contracting out health services, for example, through social franchising (SF). FP vouchers can substantially expand contraceptive access and choice and empower the underserved populations. Literature cites voucher's effectiveness in better targeting, increasing use, and improving program outcomes in FP programs; however, there is little research or explanation of how voucher management is done in practice. DISCUSSION: The paper attempts to describe various components of voucher management system and its functioning using example of a voucher program in Pakistan. There are challenges such as high upfront cost, targeting the appropriate clients, validation of vouchers, and quality assurance, but these can be managed with better preparation at the planning and design stage. Strong monitoring and evaluation are integral to successful implementation of the voucher program. Also, voucher interventions that are targeted and adopt a pro-poor strategy have been found to improve access to care within poor and marginalized populations. Such programs have the capacity to bridge health inequities in developing nations. Targeted voucher schemes such as those which are designed as pro-poor or pro-rural are known to reduce barriers to access for those living with poverty or for the ones considered as marginalized population. Hence, such interventions have the capacity to fulfill the gaps in health inequities, especially, in low- and/or middle-income countries. CONCLUSION: Voucher programs should report the voucher logistics and management to build a larger evidence base of best practices. All voucher schemes must be designed, implemented, and evaluated on the basis of set objectives through addressing the local context. But any voucher implementing organization also conducting the in-house voucher management simultaneously may be considered as a weakness in program design, in turn providing rationale for either failure or success of that particular voucher intervention. Therefore, separating implementation and management of a voucher initiative can lead to enhanced transparency, improved accountability, allow for independent validation of services, and facilitate compliance for payments.
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 | 0,030 | 0,093 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,001 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,002 | 0,002 |
| Études des sciences et des technologies | 0,004 | 0,003 |
| Communication savante | 0,005 | 0,007 |
| Science ouverte | 0,003 | 0,004 |
| Intégrité de la recherche | 0,002 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,021 | 0,002 |
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 ».