Exploring how different modes of governance act across health system levels to influence primary healthcare facility managers’ use of information in decision-making: experience from Cape Town, South Africa
Notice bibliographique
Résumé
BACKGROUND: Governance, which includes decision-making at all levels of the health system, and information have been identified as key, interacting levers of health system strengthening. However there is an extensive literature detailing the challenges of supporting health managers to use formal information from health information systems (HISs) in their decision-making. While health information needs differ across levels of the health system there has been surprisingly little empirical work considering what information is actually used by primary healthcare facility managers in managing, and making decisions about, service delivery. This paper, therefore, specifically examines experience from Cape Town, South Africa, asking the question: How is primary healthcare facility managers' use of information for decision-making influenced by governance across levels of the health system? The research is novel in that it both explores what information these facility managers actually use in decision-making, and considers how wider governance processes influence this information use. METHODS: An academic researcher and four facility managers worked as co-researchers in a multi-case study in which three areas of management were served as the cases. There were iterative cycles of data collection and collaborative analysis with individual and peer reflective learning over a period of three years. RESULTS: Central governance shaped what information and knowledge was valued - and, therefore, generated and used at lower system levels. The central level valued formal health information generated in the district-based HIS which therefore attracted management attention across the levels of the health system in terms of design, funding and implementation. This information was useful in the top-down practices of planning and management of the public health system. However, in facilities at the frontline of service delivery, there was a strong requirement for local, disaggregated information and experiential knowledge to make locally-appropriate and responsive decisions, and to perform the people management tasks required. Despite central level influences, modes of governance operating at the subdistrict level had influence over what information was valued, generated and used locally. CONCLUSIONS: Strengthening local level managers' ability to create enabling environments is an important leverage point in supporting informed local decision-making, and, in turn, translating national policies and priorities, including equity goals, into appropriate service delivery practices.
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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 | 0,005 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,003 |
| Science ouverte | 0,002 | 0,001 |
| 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 ».