African Biomedical Research Journal | 14 November 2002
Time-Series Forecasting Model Evaluation of Community Health Centre Systems in Rwanda
G, a, t, e, r, e, m, a, r, o, N, d, a, y, i, s, h, i, m, i, y, e, ,, N, s, h, u, t, i, R, u, z, i, n, d, a, n, a, ,, K, a, j, z, e, r, M, u, g, y, e, n, y, i
Abstract
This report evaluates the effectiveness of community health centre (CHC) systems in Rwanda's public healthcare sector through a time-series forecasting model. A time-series forecasting model was employed using ARIMA (AutoRegressive Integrated Moving Average) methodology to predict future healthcare needs based on historical data from to . Confidence intervals were used to quantify the uncertainty around these predictions. The analysis revealed consistent monthly fluctuations in patient visits, with a significant upward trend identified over the study period (p<0.05). The time-series forecasting model demonstrated potential for predicting CHC performance and resource requirements more accurately than previous static assessments. Further research should explore the impact of these predictions on policy-making and service delivery improvements in Rwanda's healthcare system. 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.