Abstract
{ "background": "Community health centres are a cornerstone of primary care delivery in Tanzania, yet systematic evidence on their cost-effectiveness remains limited. Existing evaluations often fail to account for the hierarchical structure of health system data, where patient outcomes are nested within facilities and districts, potentially biasing estimates.", "purpose and objectives": "This protocol details a methodological approach for a multilevel regression analysis to evaluate the cost-effectiveness of community health centre systems. The primary objective is to estimate the incremental cost per disability-adjusted life year (DALY) averted, while accounting for clustering at facility and district levels. Secondary objectives include identifying facility-level determinants of cost-effectiveness.", "methodology": "A retrospective, cross-sectional analysis will be conducted using routine health management information system data, linked with expenditure tracking surveys from a representative sample of centres. The core statistical model is a three-level hierarchical linear model: $CostEffectiveness{ijk} = \\beta0 + \\beta X{ijk} + u{k} + v{jk} + e{ijk}$, where $i$, $j$, and $k$ index patients, facilities, and districts respectively, with random intercepts $uk$ and $v{jk}$. Cost-effectiveness will be expressed as an incremental cost-effectiveness ratio. Uncertainty will be quantified using 95% confidence intervals derived from non-parametric bootstrapping.", "findings": "As this is a protocol, no empirical findings are presented. The analysis is designed to produce estimates of cost per DALY averted, with anticipated directions of effect including a hypothesised inverse relationship between facility staffing ratios and unit costs. Specific proportions, such as the expected distribution of costs across personnel, medicines, and infrastructure, will be a key descriptive output.", "conclusion": "The application of this multilevel modelling protocol is expected to yield more accurate and generalisable estimates of cost-effectiveness by properly accounting for data hierarchy, thereby informing more efficient resource allocation within the health system.", "recommendations": "Future economic evaluations of decentralised health systems should