Abstract
{ "background": "Community health centres are critical nodes in primary healthcare systems, yet their operational reliability is poorly quantified. Existing assessments often rely on cross-sectional data, failing to capture temporal dynamics and systemic performance under varying conditions.", "purpose and objectives": "This intervention study aimed to develop and apply a novel panel-data methodology for estimating the system reliability of community health centres, and to evaluate the impact of a targeted maintenance and training intervention on this metric.", "methodology": "We employed a longitudinal, difference-in-differences design with a treatment group of centres receiving a structured intervention and a matched control group. System reliability was modelled as a function of infrastructure, staffing, and supply chain variables. The core estimation used a two-way fixed effects model: $R{it} = \\alphai + \\lambdat + \\beta1 (Treati \\cdot Postt) + \\mathbf{X}{it}\\gamma + \\epsilon{it}$, where $R{it}$ is the reliability score. Inference was based on cluster-robust standard errors.", "findings": "The intervention yielded a statistically significant positive coefficient ($\\beta1 = 0.15$, 95% CI: 0.08 to 0.22), indicating a 15-percentage-point improvement in mean reliability scores within the treatment group relative to controls. The supply chain component of the intervention showed the strongest association with sustained performance.", "conclusion": "The proposed panel-data method provides a robust framework for measuring health system reliability dynamically. The intervention successfully enhanced the operational consistency of centres.", "recommendations": "Health policy should integrate longitudinal reliability metrics into routine monitoring. Scaling the tested intervention, particularly its supply chain module, is advised to strengthen systemic resilience.", "key words": "health systems, panel data, reliability engineering, primary healthcare, difference-in-differences, Ethiopia", "contribution statement": "This paper introduces a novel application of reliability engineering metrics within a panel-data econometric framework to assess health facility performance, generating a