The prevalence of off-grid energy systems in Ghana has increased significantly over recent years, necessitating rigorous methodological assessment to ensure their effectiveness and sustainability. The analysis employs rigorous statistical methods including multivariate regression models with uncertainty quantified via bootstrapping techniques. The study synthesizes data from multiple quasi-experiments conducted across various regions of Ghana. A key finding is that the use of propensity score matching significantly improved the comparability between intervention and control groups, reducing bias by approximately 30% in clinical outcomes evaluation. The adoption of robust quasi-experimental designs enhances the validity of clinical outcome assessments for off-grid energy systems in Ghana, providing a more accurate picture of system performance under real-world conditions. Future research should prioritise methodological consistency and data quality to ensure reliable results from quasi-experimental studies involving off-grid community energy systems. The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.