Emergency care units (ECUs) in Senegal are critical for patient management during medical emergencies. However, there is a need to evaluate and improve their systems to ensure optimal clinical outcomes. This study employed multilevel regression analysis to assess the impact of various factors on patient outcomes within ECUs. Data were collected from multiple health facilities across Senegal and analysed using advanced statistical techniques to account for both individual and contextual effects. The analysis revealed significant variations in clinical outcomes between different regions, with a coefficient estimate of -0. 54 (95% CI: -0. 72, -0. 36) indicating that regional disparities are substantial, suggesting the need for targeted interventions to improve care. Multilevel regression analysis provided valuable insights into the effectiveness and efficiency of ECUs in Senegal, highlighting the importance of addressing regional differences to enhance patient outcomes. Policy makers should prioritise resource allocation and training programmes tailored to specific regions with lower performance metrics identified through this study. Emergency Care Units, Clinical Outcomes, Multilevel Regression Analysis, SENEGAL Treatment effect was estimated with logit (pᵢ) =₀+^ Xᵢ, and uncertainty reported using confidence-interval based inference.
Mbaye et al. (Wed,) studied this question.