African Neurology and Neurosurgery | 10 December 2011
Time-Series Forecasting Model for Evaluating Community Health Centre Systems in Uganda,
O, t, o, m, b, e, O, t, i, m, ,, K, i, z, z, a, O, k, e, l, l, o, ,, N, a, k, i, j, i, n, y, a, K, a, k, o, o, z, a, ,, S, s, e, k, a, n, y, a, n, k, w, e, K, i, z, z, a
Abstract
Community health centres in Uganda have faced challenges in meeting service demands over time. A comprehensive time-series analysis was conducted using statistical software, incorporating historical data from -. The study employed an ARIMA (AutoRegressive Integrated Moving Average) model for forecasting future trends in service utilization and system performance. The ARIMA model indicated a significant increase of 5% in patient consultations per month, suggesting improved service capacity over the year. The time-series forecasting approach demonstrated promising results in evaluating community health centre systems' reliability, with substantial improvements observed in patient consultation rates. Further research should focus on scalability and cost-effectiveness of the model to ensure widespread application across Ugandan healthcare settings. Treatment effect was estimated with $\text{logit}(p<em>i)=\beta</em>0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.