{ "background": "Maternal healthcare systems in sub-Saharan Africa require robust, data-driven tools for strategic planning. Existing evaluations often rely on retrospective analyses, lacking predictive capacity for future clinical outcomes under varying resource scenarios. ", "purpose and objectives": "This case study aims to methodologically evaluate the application of a time-series forecasting model to predict key maternal clinical outcomes within a national healthcare system, assessing its utility for facility-level resource planning. ", "methodology": "We developed and applied a Seasonal AutoRegressive Integrated Moving Average with eXogenous factors (SARIMAX) model, formalised as \ (B) \ (Bˢ) \ᵈ\D yt = \ (B) \ (Bˢ) \ + \ Xt, to historical facility-level data. The model incorporated exogenous variables including staffing ratios and drug supply metrics. Forecast accuracy was evaluated using rolling-origin cross-validation and 95% prediction intervals. ", "findings": "The model demonstrated strong predictive accuracy for facility-level maternal mortality ratios, with a mean absolute percentage error of 8. 7% in the validation period. Forecasts indicated a persistent, albeit decelerating, downward trend in the target ratio over the forecast horizon, contingent on the maintenance of current staffing inputs. Prediction intervals widened notably under simulated budget constraint scenarios. ", "conclusion": "The SARIMAX framework provides a statistically robust methodological tool for forecasting clinical outcomes, offering health system managers a quantifiable basis for anticipatory decision-making. ", "recommendations": "Integrate forecasting models into national health management information systems for routine outcome projection. Allocate training resources for analysts within health ministries to build in-house competency in time-series analysis. ", "key words": "health systems forecasting, maternal health, time-series analysis, SARIMAX, clinical outcomes, resource planning", "contribution statement": "This study provides a novel methodological application of a SARIMAX model to forecast facility-specific maternal clinical outcomes, demonstrating its operational value for proactive health system governance in a resource
Mukamana et al. (Sun,) studied this question.
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