"background": "District hospitals are critical nodes in Ghana's healthcare system, yet systematic, quantitative evaluations of their systemic performance on clinical outcomes are limited. Existing assessments often lack methodological rigour in accounting for hierarchical patient data and varying hospital-level factors. ", "purpose and objectives": "This study aimed to develop and apply a robust methodological framework for evaluating district hospital systems by quantifying the influence of hospital-level system factors on risk-adjusted inpatient mortality. ", "methodology": "We conducted a retrospective analysis of anonymised inpatient records from a nationally representative sample of district hospitals. A two-level hierarchical logistic regression model was specified: (p{ij) = \0 + \ Xij + uj, where pij is the probability of mortality for patient i in hospital j, Xij are patient-level covariates, and u₉ is the hospital-specific random effect. Model inference used robust standard errors. ", "findings": "Hospital-level system characteristics explained 31% of the variation in mortality outcomes after adjusting for patient casemix. A one-standard-deviation increase in the hospital's drug availability index was associated with a 15% reduction in the odds of mortality (odds ratio 0. 85, 95% CI 0. 76 to 0. 94). ", "conclusion": "The methodological approach demonstrates that multilevel modelling is essential for isolating the effect of hospital system performance from patient-level factors. System-level resourcing, particularly drug availability, is a significant determinant of clinical outcomes. ", "recommendations": "Health system evaluations should adopt multilevel analytical techniques to inform targeted resource allocation. Policy should prioritise strengthening essential medicine supply chains at the district level as a mechanism for improving outcomes. ", "key words": "health systems evaluation, hierarchical modelling, hospital performance, health outcomes, sub-Saharan Africa", "contribution statement": "This paper provides a novel methodological framework for health systems research in resource-constrained settings,
Mensah et al. (Fri,) studied this question.