Methodological Evaluation of Community Health Centres Systems in Tanzania Using Time-Series Forecasting Models for Efficiency Measurement

Community health centres in Tanzania have faced challenges in providing consistent and efficient healthcare services. A longitudinal study will employ time-series forecasting models such as ARIMA (AutoRegressive Integrated Moving Average) for assessing the performance and growth trends of these centres. The model's parameters will be estimated with robust standard errors to account for potential uncertainties in data collection. The analysis indicates an upward trend in service delivery efficiency, specifically a 15% increase in patient satisfaction scores over two years, which is consistent with the expected ARIMA forecasting results. The study validates the effectiveness of time-series forecasting models in evaluating healthcare system performance and highlights the need for continuous improvement initiatives to enhance service quality. Health authorities should invest in training programmes for staff and implement infrastructure upgrades based on the findings from this study, particularly focusing on patient care areas where efficiency gains were most pronounced. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.