African Applied Molecular Biology (Applied Science) | 04 December 2011
Multilevel Regression Analysis to Evaluate Clinical Outcomes in Emergency Care Units Across Tanzania
K, a, m, b, a, r, a, n, z, a, M, v, u, n, i, p, w, e, ,, K, a, t, u, n, a, M, a, g, o, g, o, ,, M, a, w, e, u, M, i, h, i, g, o, ,, S, e, m, b, e, r, e, k, e, C, h, i, t, u, w, o
Abstract
Background information on emergency care units in Tanzania is limited, with variability across different regions. A multilevel regression model was employed to analyse data from multiple emergency care units. The model accounts for both unit-level (e.g., staffing, infrastructure) and patient-level factors affecting clinical outcomes. The multilevel regression analysis revealed that the proportion of patients receiving timely interventions varied significantly by level of care within regions, with a notable difference in intervention rates between Level 1 and Level 4 units (60% vs. 35%, p < 0.05). The multilevel regression analysis provided insights into the effectiveness of emergency care systems across Tanzania. Recommendation for enhancing patient outcomes includes improving infrastructure in lower-level units and increasing training opportunities for healthcare providers. 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.