A Quasi-Experimental Evaluation of Health Systems Optimisation and Yield in Ethiopian Community Health Centres

{ "background": "Community health centres in Ethiopia face systemic inefficiencies that constrain service delivery and agricultural health outreach, a critical nexus for food systems. Existing evaluations often lack rigorous counterfactual frameworks to isolate the impact of operational interventions.", "purpose and objectives": "This case study aimed to methodologically evaluate a systems optimisation intervention in a network of centres, with the primary objective of quantifying its causal effect on patient yield (a composite metric of consultations completed).", "methodology": "A quasi-experimental, difference-in-differences design was employed, comparing 12 intervention centres with 12 matched control centres over an observation period. The core impact was estimated using a linear panel model: Yit = \β0 + \β1 ( \× ) + \ + \ + \εit, where Yᵢₜ is the yield for centre i at time t, with centre and time fixed effects. Inference was based on cluster-robust standard errors.", "findings": "The optimisation protocol significantly increased average daily patient yield by 18.7% (95% CI: 12.3 to 25.1) in intervention centres relative to the control trend. Process mapping revealed that reductions in patient flow bottlenecks, particularly in pharmacy and triage, were the dominant mechanism for this improvement.", "conclusion": "Targeted systems optimisation, even without major capital investment, can substantially improve service capacity in resource-constrained community health settings, directly enhancing their role in agricultural health support.", "recommendations": "Programme planners should integrate rigorous quasi-experimental designs into routine operational research. Scaling the tested optimisation package requires adaptive management to address local staffing and supply chain contexts.", "key words": "health systems strengthening, difference-in-differences, operational research, primary healthcare, impact evaluation", "contribution statement": "This study provides a novel application of a quasi-experimental panel model