Methodological Assessment and Time-Series Forecasting in District Hospital Systems of South Africa: A Review

District hospitals in South Africa play a crucial role in healthcare delivery, particularly in underserved areas. Despite their importance, there is limited research on methodological assessments and forecasting models for evaluating their performance. The study employs a systematic literature review approach, focusing on empirical studies that utilised methodological tools such as statistical models and time-series analysis. Specifically, ARIMA (AutoRegressive Integrated Moving Average) model will be used to forecast future trends in service adoption. A key finding is the significant variation in patient utilisation rates across different district hospitals, with some showing a 30% higher adoption rate for antenatal care services compared to others. The review highlights gaps in methodological consistency and recommends adopting standardised forecasting models to improve the reliability of service adoption predictions. Health policymakers should prioritise methodological standardization and encourage the use of robust time-series analysis tools like ARIMA for evaluating healthcare system performance. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.