In-Kind Drug Donations for Tanzania
Notice bibliographique
Résumé
Tanzania, a country with low access to essential drugs, receives substantial drug donations (DDs) as in-kind gifts. To support the ongoing health sector reform and to promote a good donation practice, stakeholders' and recipients' views on the appropriateness and acceptability of DDs are of particular interest. The objectives were to collect information on the situation of in-kind DDs in Tanzania, to assess the characteristics of the DD system in Tanzania and to collect stakeholders' and recipients' views on problematic areas in DD processes including all strategies of drug donation. Using a qualitative approach, data were collected through validated postal questionnaires in Swahili and English, which were sent out in June 2001 countrywide to stakeholders of all sectors and levels of decision-making involved in healthcare in Tanzania. Of 1,383 mailed questionnaires, 496 were returned, of which 411 (30%) were eligible for analysis. All respondents perceived in-kind DDs as an important resource to assure drug availability in a context of poverty. Half of the respondents were recipients of in-kind DDs. On average, an estimated 27% of the recipients' drug supply was covered through DDs. The main problem for recipients of all sectors involved in healthcare was the insufficient quantity of DDs for sustainable treatment. Representatives of the public sector asked for more transparency in the DD processes. NGOs and religious facilities with better developed structures raised problems such as shipment fees, insufficient infrastructure and training. Recipients suggested that optimizing communication would have the greatest impact on improving the DD processes. In Tanzania, DDs were highly accepted by recipients and stakeholders. The primary concern of DD recipients was less the quality of drugs, although quality assurance remained an ongoing concern, than the discrepancy between the recipients' needs and the donors' supply. DDs often failed to cover priority needs. Suggestions of recipients for DD process optimization corresponded fully with the principles of the Tanzanian and the World Health Organization (WHO) guidelines for DDs, with the call for better implementation of the guidelines among donors and recipients.
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 | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 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 ».