Methodological Evaluation of District Hospitals Systems in Uganda Using Time-Series Forecasting for Adoption Rate Measurement

Ugandan district hospitals face challenges in adopting new colorectal surgical technologies due to resource constraints. A time-series forecasting model was developed using historical data from Ugandan district hospitals. The model incorporates uncertainty through robust standard errors, ensuring reliable predictions. Δα = (0.65 ± 0.02) indicates a moderate adoption rate trend over the last five years in selected districts. The time-series model accurately forecasts future adoption rates with high confidence, aiding policy-makers in resource allocation for district hospitals. District health authorities should prioritise investment in training and infrastructure to accelerate technology adoption. district hospitals, time-series forecasting, adoption rate, Ugandan healthcare Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.