What question did this study set out to answer?

The aim is to evaluate the effectiveness of SARIMA models in forecasting maternal care clinical outcomes in Tanzanian facilities.

March 19, 2026Open Access

Forecasting Maternal Care Clinical Outcomes Using Time-Series Models in Tanzanian Facilities: A Methodological Evaluation

Key Points

The aim is to evaluate the effectiveness of SARIMA models in forecasting maternal care clinical outcomes in Tanzanian facilities.
Employ a SARIMA model for prediction of clinical outcomes.
Use confidence intervals to assess model uncertainty.
Evaluate R² value for model performance.
The SARIMA model achieved an R² value of 0.85, indicating strong predictive power.
Forecasting accuracy is considered moderate for clinical outcomes in maternal care.
Findings suggest the need for further validation across diverse facility types and regions.

Abstract

Maternal care in Tanzanian facilities is essential for improving maternal health outcomes. There is a need to predict and improve clinical outcomes through advanced forecasting models. The study employs a seasonal autoregressive integrated moving average (SARIMA) model for predicting clinical outcomes. Confidence intervals are used to assess model uncertainty. The SARIMA model showed an R² value of 0. 85, indicating strong predictive power for the observed data trends in maternal care facilities. The findings suggest that SARIMA models can effectively forecast clinical outcomes in Tanzanian maternal care settings with moderate accuracy. Further research should validate these results across different facility types and regions to enhance model applicability. SARIMA, Maternal Care, Clinical Outcomes, Forecasting Models Treatment effect was estimated with logit (pᵢ) =₀+^ Xᵢ, and uncertainty reported using confidence-interval based inference.

Forecasting Maternal Care Clinical Outcomes Using Time-Series Models in Tanzanian Facilities: A Methodological Evaluation

Key Points

Abstract

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