"background": "Community health centres are critical nodes in sub-Saharan African food and health systems, yet longitudinal assessments of their operational efficiency are scarce. Existing evaluations often lack the statistical rigour to account for hierarchical data structures and temporal dependencies inherent in such systems. ", "purpose and objectives": "This study aimed to develop and apply a novel Bayesian hierarchical model to quantify longitudinal efficiency gains within a national network of community health centres, providing a robust methodological framework for performance evaluation. ", "methodology": "We conducted a longitudinal analysis of panel data from a nationally representative sample of community health centres. Efficiency was modelled using a Bayesian hierarchical structure: y{it \ (\ + \ + Xit\, \²), with \ \ (\\, \\²) for centre-level random intercepts and \ modelling temporal trends. Posterior distributions were estimated using Markov chain Monte Carlo sampling. ", "findings": "The model identified a positive temporal trend in technical efficiency, with a posterior probability of 0. 97 that the annual rate of gain exceeded 1. 2%. Centre-level heterogeneity was substantial, with the centre standard deviation in baseline efficiency, \_\, estimated at 0. 31 (95% credible interval: 0. 26, 0. 37). ", "conclusion": "The Bayesian hierarchical approach provides a statistically coherent framework for analysing efficiency in complex, multi-level health systems, revealing significant systemic improvement alongside persistent inter-centre variation. ", "recommendations": "Policy evaluations should adopt similar hierarchical modelling techniques to accurately attribute performance changes. Resource allocation mechanisms should account for the identified baseline heterogeneity to ensure equitable system development. ", "key words": "Bayesian hierarchical model, health systems efficiency, longitudinal analysis, sub-Saharan Africa, technical efficiency, health policy evaluation", "contribution statement": "This paper introduces a novel application of Bayesian hierarchical
Wanjiku Mwangi (Sun,) studied this question.