Improving district level health planning and priority setting in Tanzania through implementing accountability for reasonableness framework: Perceptions of stakeholders
Notice bibliographique
Résumé
BACKGROUND: In 2006, researchers and decision-makers launched a five-year project - Response to Accountable Priority Setting for Trust in Health Systems (REACT) - to improve planning and priority-setting through implementing the Accountability for Reasonableness framework in Mbarali District, Tanzania. The objective of this paper is to explore the acceptability of Accountability for Reasonableness from the perspectives of the Council Health Management Team, local government officials, health workforce and members of user boards and committees. METHODS: Individual interviews were carried out with different categories of actors and stakeholders in the district. The interview guide consisted of a series of questions, asking respondents to describe their perceptions regarding each condition of the Accountability for Reasonableness framework in terms of priority setting. Interviews were analysed using thematic framework analysis. Documentary data were used to support, verify and highlight the key issues that emerged. RESULTS: Almost all stakeholders viewed Accountability for Reasonableness as an important and feasible approach for improving priority-setting and health service delivery in their context. However, a few aspects of Accountability for Reasonableness were seen as too difficult to implement given the socio-political conditions and traditions in Tanzania. Respondents mentioned: budget ceilings and guidelines, low level of public awareness, unreliable and untimely funding, as well as the limited capacity of the district to generate local resources as the major contextual factors that hampered the full implementation of the framework in their context. CONCLUSION: This study was one of the first assessments of the applicability of Accountability for Reasonableness in health care priority-setting in Tanzania. The analysis, overall, suggests that the Accountability for Reasonableness framework could be an important tool for improving priority-setting processes in the contexts of resource-poor settings. However, the full implementation of Accountability for Reasonableness would require a proper capacity-building plan, involving all relevant stakeholders, particularly members of the community since public accountability is the ultimate aim, and it is the community that will live with the consequences of priority-setting decisions.
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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 | 0,076 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| 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 ».