{ "background": "District hospitals are critical nodes in the South African healthcare system, yet systematic evaluations of their operational systems for patient safety and risk reduction are methodologically underdeveloped. Existing assessments often lack the statistical rigour to account for hierarchical data structures inherent in hospital networks.", "purpose and objectives": "This short report aims to methodologically evaluate a novel analytical framework for assessing systemic risk in district hospitals. The objective is to demonstrate the application of multilevel regression modelling to quantify risk reduction potential across different hospital system domains.", "methodology": "We conducted a secondary analysis of anonymised, cross-sectional audit data from a national sample of district hospitals. A two-level random intercepts model was specified: $y{ij} = \\beta{0} + \\beta{1}X{ij} + u{j} + e{ij}$, where $i$ denotes wards and $j$ denotes hospitals. Risk indices were modelled against system performance scores for infrastructure, clinical processes, and administration. Inference was based on 95% confidence intervals derived from robust standard errors.", "findings": "The multilevel model revealed significant variation in risk indices attributable to hospital-level system performance (intra-class correlation coefficient = 0.31). A one-standard-deviation improvement in clinical process scores was associated with a 17.2% reduction in the composite risk index (95% CI: 12.5% to 21.9%). Infrastructure scores showed a weaker, non-significant association.", "conclusion": "The methodological approach successfully disentangles ward-level from hospital-level system effects, providing a more precise tool for targeting risk reduction interventions. Clinical process systems emerge as the most leverageable domain for systemic improvement.", "recommendations": "Health authorities should adopt hierarchical modelling in routine hospital audits to identify priority hospitals and system domains for quality improvement investments. Future research should apply this method longitudinally to assess intervention impact.", "key words": "health systems evaluation, multilevel modelling, patient safety, health services research, quality improvement",