Time-Series Forecasting Model for Measuring Adoption Rates in District Hospitals Systems: A Methodological Evaluation of South African Context,

The adoption rates of new healthcare technologies in South African district hospitals are critical for improving patient outcomes and resource management. The study employed a time-series analysis using an ARIMA (AutoRegressive Integrated Moving Average) model. Data were collected through surveys and official records. Adoption rates of electronic health record systems showed a consistent upward trend, increasing by approximately 15% over the two-year period. The ARIMA model provided reliable forecasts for adoption trends in district hospitals, indicating potential improvements with sustained intervention strategies. Further research should explore longer-term projections and incorporate additional variables such as financial incentives to enhance technology uptake. ARIMA model, time-series forecasting, healthcare technology, South Africa, district hospitals Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.