Methodological Evaluation of Community Health Centre Systems in Kenya: A Panel-Data Protocol for Estimating Risk Reduction in Health Outcomes

"background": "Community health centres are a cornerstone of primary healthcare delivery in sub-Saharan Africa, yet robust methodological frameworks for evaluating their longitudinal impact on population health outcomes are lacking. Existing evaluations often rely on cross-sectional data, which cannot adequately account for unobserved heterogeneity or establish temporal precedence. ", "purpose and objectives": "This protocol details a methodological approach to estimate the causal effect of community health centre system functionality on the reduction of key health risks. The primary objective is to establish and validate a panel-data model for quantifying risk reduction in maternal and child health outcomes attributable to centre performance. ", "methodology": "We propose a longitudinal, facility-level panel study. Data will be collected through structured audits and routine health information systems across a representative sample of centres. The core analytical model is a two-way fixed effects regression: Y{it = \0 + \1 CHCit + \ + \ +, where Yit is a health outcome for centre i at time t, and CHCit is a composite functionality score. Inference will rely on cluster-robust standard errors to account for intra-facility correlation. ", "findings": "As a research protocol, this paper does not present empirical results. The anticipated analytical output will provide point estimates and 95% confidence intervals for 1, indicating the direction and magnitude of association. For example, we hypothesise that a one-standard-deviation increase in the functionality score will be associated with a measurable reduction in the risk of low birthweight. ", "conclusion": "This protocol provides a novel, rigorous methodological framework for evaluating community health systems. The adoption of this panel-data approach is expected to yield more credible estimates of programme impact than prior methods. ", "recommendations": "Researchers and policymakers should adopt longitudinal designs and fixed-effects models to strengthen causal inference in health systems evaluation. Investment in sustained panel data collection is critical for evidence-based decision-making. ", "key