African Journal of Pathology | 22 October 2008
Bayesian Hierarchical Model for Measuring Adoption Rates in Nigerian District Hospitals Systems
F, e, l, i, x, O, s, i, t, a, U, d, o, h
Abstract
Adoption rates of new healthcare technologies in Nigerian district hospitals are often underreported and misinterpreted due to variability across different facilities. A Bayesian hierarchical model was constructed to account for both facility-specific and system-level factors influencing technology adoption. The model incorporates uncertainty through robust standard errors and credible intervals. The model estimated an average adoption rate of 45% across all district hospitals, with significant variability between urban and rural facilities (urban: 60%, rural: 30%). The Bayesian hierarchical model provides a nuanced understanding of technology adoption dynamics in Nigerian hospital systems. Policy makers should consider both facility-specific and system-level interventions to enhance technology uptake across different geographic regions. Treatment effect was estimated with $\text{logit}(p<em>i)=\beta</em>0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.