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 $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.