Abstract
{ "background": "Community health centres (CHCs) are critical nodes in Ghana's primary healthcare system, yet robust methodologies for quantifying the yield improvement of interventions within these systems are underdeveloped. Existing evaluations often lack longitudinal rigour, limiting causal inference.", "purpose and objectives": "This study aimed to methodologically evaluate a multi-component intervention in Ghanaian CHCs and to estimate its causal effect on service yield using a panel-data econometric framework. The primary objective was to establish a replicable model for measuring health system productivity gains.", "methodology": "We conducted a quasi-experimental intervention study across a panel of CHCs. The intervention comprised targeted health worker training, streamlined logistics protocols, and community engagement modules. Yield was operationalised as the number of key outpatient services delivered per full-time equivalent clinical staff per month. We estimated a two-way fixed effects model: $Y{it} = \\beta0 + \\beta1 \\text{Intervention}{it} + \\alphai + \\gammat + \\epsilon{it}$, where $\\alphai$ and $\\gammat$ are unit and time fixed effects. Inference was based on cluster-robust standard errors.", "findings": "The intervention was associated with a statistically significant increase in service yield. The coefficient $\\beta1$ was estimated at 8.7 services per staff member per month (95% CI: 5.2, 12.1; p<0.001). The most pronounced improvements were observed in postnatal care and chronic disease management services.", "conclusion": "The panel-data approach provides a rigorous methodological framework for evaluating health system interventions, isolating the treatment effect from time-invariant heterogeneity and common temporal trends. The intervention demonstrably improved service yield within the studied CHCs.", "recommendations": "Health policymakers should integrate panel-data evaluation designs into routine health system monitoring. The specific intervention components, particularly the logistics protocols, warrant scaling with continuous impact assessment using the described methodology.", "key words":