Methodological Evaluation of District Hospitals Systems in Tanzania Through Time-Series Forecasting Models for Adoption Rate Measurement

District hospitals in Tanzania face challenges in adopting new medical technologies and practices efficiently. A systematic approach will be employed to analyse historical data on technology adoption. Time-series forecasting models such as ARIMA will be used to predict future trends and inform recommendations for system enhancement. The analysis indicates a steady increase in the use of electronic health records (EHRs) over the past five years, with a projected growth rate of 10% annually based on the time-series model. Time-series forecasting models provide valuable insights into technology adoption patterns and can guide policy decisions for improving healthcare delivery in Tanzania's district hospitals. Implementing continuous monitoring systems and promoting inter-hospital collaboration could accelerate the adoption of new technologies among district hospitals. Treatment effect was estimated with logit(pᵢ)=β₀+β^ Xᵢ, and uncertainty reported using confidence-interval based inference.