{ "background": "Community health centres are a cornerstone of primary healthcare delivery, yet longitudinal assessments of their systemic performance, particularly regarding clinical outcomes, remain methodologically underdeveloped. Robust forecasting tools are needed to evaluate trends and inform resource allocation. ", "purpose and objectives": "This study aimed to develop and validate a novel time-series forecasting model to measure longitudinal clinical outcomes within the community health centre system, providing a methodological framework for systemic evaluation. ", "methodology": "A longitudinal study design was employed, utilising a national panel dataset of clinical indicators. The core methodological contribution is a Seasonal AutoRegressive Integrated Moving Average with eXogenous factors (SARIMAX) model, specified as \ (B) \ (Bˢ) \ᵈ\D yt = \ (B) \ (Bˢ) \ + \ Xt, where Xₜ represents exogenous health system covariates. Model fit was assessed using rolling-window cross-validation, with uncertainty quantified via 95% prediction intervals. ", "findings": "The forecasting model demonstrated robust predictive accuracy for key outcome trajectories. A principal finding was a forecasted gradual decline in the system-wide antenatal first visit coverage ratio, with a projected decrease of approximately 8. 5 percentage points over the forecast horizon (95% PI: 6. 2, 10. 7). Model diagnostics indicated non-stationarity in several outcome series, necessitating the integrated component. ", "conclusion": "The developed SARIMAX model provides a statistically rigorous tool for the longitudinal evaluation of clinical outcomes at a systemic level. It captures complex temporal dynamics and identifies concerning trajectories in preventative service coverage. ", "recommendations": "Health policy planners should adopt similar forecasting methodologies for proactive system management. The identified decline in antenatal coverage necessitates targeted interventions and further investigation into causative health system factors. ", "key words": "health systems evaluation, time-series analysis, forecasting, primary healthcare, clinical outcomes, SARIMAX", "contribution statement": "This paper provides a novel
Mokoena et al. (Thu,) studied this question.