Conceptualizing and implementing a health workforce registry in Nigeria
Notice bibliographique
Résumé
BACKGROUND: Nigeria's health sector aims to ensure that the right number of health workers that are qualified, skilled, and distributed equitably, are available for quality health service provision at all levels. Achieving this requires accurate and timely health workforce information. This informed the development of the Nigeria Health Workforce Registry (NHWR) based on the global, regional, and national strategies for strengthening the HRH towards achieving universal health coverage. This case study describes the process of conceptualizing and establishing the NHWR, and discusses the strategies for developing sustainable and scalable health workforce registries. CASE PRESENTATION: In designing the NHWR, a review of existing national HRH policies and guidelines, as well as reports of previous endeavors was done to learn what had been done previously and obtain the views of stakeholders on how to develop a scalable and sustainable registry. The findings indicated the need to review the architecture of the registry to align with other health information systems, develop a standardized data set and guidance documents for the registry including a standard operating procedure to ensure that a holistic process is adopted in data collection, management and use nationally. Learning from the findings, a conceptual framework was developed, a registry managed centrally by the Federal Ministry of Health was developed and decentralized, a standardized tool based on a national minimum data was developed and adopted nationally, a registry prototype was developed using iHRIS Manage and the registry governance functions were integrated into the health information system governance structures. To sustain the functionality of the NHWR, the handbook of the NHWR that comprised of an implementation guide, the standard operating procedure, and the basic user training manual was developed and the capacity of government staff was built on the operations of the registry. CONCLUSION: In establishing a functional and sustainable registry, learning from experiences is essential in shaping acceptable, sustainable, and scalable approaches. Instituting governance structures that include and involve policymakers, health managers and users is of great importance in the design, planning, implementation, and decentralization stages. In addition, developing standardized tools based on the health system's needs and instituting supportable mechanisms for data flow and use for policy, planning, development, and management is essential.
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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 | 0,001 | 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 ».