{ "background": "Public health surveillance systems are critical for monitoring clinical outcomes and informing policy in sub-Saharan Africa. In Kenya, numerous surveillance initiatives have been implemented, yet a comprehensive methodological evaluation of their designs and the statistical robustness of their panel-data estimations is lacking.", "purpose and objectives": "This meta-analysis aims to methodologically evaluate surveillance systems used for clinical outcomes in Kenya and to assess the statistical properties and consistency of panel-data estimation techniques employed within these studies.", "methodology": "A systematic search identified relevant studies. Methodological quality was appraised using a modified framework. Quantitative synthesis employed random-effects meta-regression to pool effect estimates. The core panel-data model evaluated was $Y{it} = \\beta0 + \\beta1 X{it} + \\alphai + \\epsilon{it}$, where $\\alpha_i$ represents entity-specific fixed effects. Inference was based on 95% confidence intervals and robust standard errors clustered at the study level.", "findings": "Methodological quality was highly heterogeneous, with 42% of systems lacking documented data validation protocols. The meta-regression indicated a positive pooled association between integrated surveillance system design and improved outcome measurement (standardised coefficient: 0.31, 95% CI: 0.18 to 0.44), though with significant study variance (I² = 67%).", "conclusion": "While panel-data methods are widely applied, their implementation in Kenyan surveillance contexts often suffers from methodological limitations that may affect the validity of inferences about clinical outcomes.", "recommendations": "Future surveillance systems should adopt standardised methodological reporting frameworks and prioritise the use of fixed-effects models with robust error estimation to control for unobserved heterogeneity. Capacity building in advanced longitudinal data analysis is required.", "key words": "public health surveillance, panel data, meta-regression, clinical outcomes, methodological evaluation, Kenya", "contribution statement": "This study provides the first quantitative synthesis of methodological designs and estimation practices across Kenyan public health surveillance systems,