"background": "District hospitals in Nigeria face systemic challenges affecting service delivery, yet robust methodological frameworks for evaluating the reliability of their operational systems are lacking. Existing assessments often rely on cross-sectional data, which cannot establish causal relationships between interventions and system performance. ", "purpose and objectives": "This study aimed to develop and methodologically evaluate a quasi-experimental design for measuring and improving system reliability within the clinical and logistical operations of district hospitals. The primary objective was to test the feasibility of this design in a resource-constrained setting. ", "methodology": "A quasi-experimental, pre-post intervention study was conducted across a matched pair of district hospitals. The intervention comprised a structured systems engineering protocol targeting medication supply and patient triage pathways. Reliability was quantified using a composite metric of failure rates. The impact was assessed using a difference-in-differences model: Y{it = \0 + \1 + \2 + \3 (\) +, with inference based on cluster-robust standard errors. ", "findings": "The methodological evaluation demonstrated the design's feasibility, though implementation fidelity varied. The intervention hospital showed a marked reduction in system failure rates post-intervention compared to the control. The adjusted difference-in-differences estimate indicated a 22 percentage point improvement in the composite reliability score (95% CI: 15 to 29). Key logistical challenges in data capture were identified as a major theme affecting measurement consistency. ", "conclusion": "The proposed quasi-experimental design is a viable method for assessing hospital system reliability in similar contexts. It provides a stronger causal framework than observational studies, but requires careful management of field logistics to ensure data quality. ", "recommendations": "Future applications should incorporate longer lead-in periods for staff training and integrate real-time data auditing. The methodology should be validated across a broader range of hospital systems and geographical regions
Hassan et al. (Wed,) studied this question.