Multi-Level Regression Analysis for Evaluating Yield Improvement in Community Health Centres Systems in Ethiopia: A Longitudinal Study
Abstract
Community health centers (CHCs) in Ethiopia have been established to improve access to healthcare services, but their effectiveness varies across different regions and levels of care. A longitudinal dataset spanning five years was analysed with a multi-level mixed-effects model: Y₈₉ₓ = eta₀ + eta₁X₈₉ₓ + uᵢ + vⱼ + e₈₉ₓ, where uᵢ represents the fixed effect of CHC i over time, and vⱼ captures the contextual effects at the county level. The robust standard errors account for within-cluster correlation. CHCs in rural areas showed a significant improvement in patient satisfaction scores (mean increase by 15%) compared to urban settings, suggesting geographical location as an influential factor. Multilevel regression analysis provided insights into the yield improvements and identified key drivers of performance variation between CHCs. The findings can inform policy adjustments for equitable healthcare service delivery. Enhanced training programmes should be tailored to address specific challenges in rural settings, while centralized monitoring systems are recommended to ensure consistency across all CHCs.
Key Points
Objective
This research aims to evaluate the yield improvements in community health centers across different regions in Ethiopia.
Methods
- Analyzed a longitudinal dataset over five years
- Applied a multi-level mixed-effects model
- Accounted for fixed and contextual effects
- Assessed patient satisfaction scores in rural vs. urban settings
Results
- Rural community health centers showed a 15% mean increase in patient satisfaction scores
- Geographical location significantly influenced healthcare effectiveness
- Identified performance variation drivers among different health centers