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| Asıl Yazarlar: | , , |
|---|---|
| Materyal Türü: | Recurso digital |
| Dil: | İngilizce |
| Baskı/Yayın Bilgisi: |
Zenodo
2007
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| Konular: | |
| Online Erişim: | https://doi.org/10.5281/zenodo.18952985 |
| Etiketler: |
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İçindekiler:
- <p>Urban primary care networks (PCNs) are a critical component of health system strengthening in sub-Saharan Africa, yet robust methodological frameworks for evaluating their clinical performance are lacking. This study aimed to methodologically evaluate the structure of urban PCNs and quantify their association with key clinical outcomes using a multilevel analytical approach. We conducted a cross-sectional analysis of patient-level data from a stratified random sample of 42 primary care facilities across three urban regions. The primary outcome was controlled hypertension (BP <140/90 mmHg). A three-level random intercepts logistic regression model was fitted: $\text{logit}(p_{ijk}) = \beta_0 + \beta X_{ijk} + u_{jk} + v_k$, where patients (i) were nested within facilities (j), nested within PCNs (k). Robust standard errors were used for inference. Facilities embedded within formal PCNs demonstrated a statistically significant improvement in hypertension control rates compared to non-networked facilities (adjusted odds ratio 1.82, 95% CI 1.31 to 2.53). The intra-class correlation coefficient indicated that 15% of the variation in outcomes was attributable to network-level factors. Formal network affiliation is positively associated with better clinical performance for chronic disease management in urban settings, highlighting the importance of inter-facility structures. Health policy should prioritise the formalisation and support of primary care networks with standardised governance and data-sharing protocols. Future research should employ longitudinal designs to assess causality. primary health care, health systems, multilevel analysis, urban health, non-communicable diseases, Nigeria This paper provides a novel application of multilevel regression to deconstruct the variance in clinical outcomes attributable to network-level structures in an African urban primary care context.</p>