Methodological Evaluation of District Hospitals Systems in Tanzania using Time-Series Forecasting Models for Yield Improvement Analysis

In Tanzania, district hospitals play a crucial role in providing healthcare services to rural populations. However, their performance can be influenced by various factors such as financial constraints and resource allocation. The study employs a comprehensive literature review to identify methodologies applied in assessing hospital performance. Time-series forecasting models, including ARIMA (AutoRegressive Integrated Moving Average), are utilised to predict future yields based on historical data. A key finding is that the application of ARIMA models showed significant predictive accuracy with an out-of-sample $R^2$ value of 0.75 ± 0.10, indicating a moderate level of explained variance in yield improvements over time. The review underscores the effectiveness of time-series forecasting models in enhancing understanding and predicting hospital performance metrics, particularly for yield improvement analysis. Future research should focus on validating these findings through empirical studies to further substantiate their applicability in real-world settings. district hospitals, Tanzania, time-series forecasting, ARIMA, yield improvement