Methodological Evaluation of Community Health Centres in Kenya Using Time-Series Forecasting Models for Risk Reduction Measurement

Community health centres (CHCs) in Kenya are pivotal for healthcare delivery, especially in underserved areas. However, their effectiveness and efficiency require continuous evaluation. A systematic review of existing literature was conducted, focusing on empirical data from recent studies in Kenya. Time-series forecasting models were employed, including the ARIMA model (Autoregressive Integrated Moving Average) for trend analysis. The analysis revealed a significant positive correlation between CHC accessibility and patient recovery rates, with an average improvement rate of 15% over one year. The use of time-series forecasting models provided insights into the performance variability across different regions, highlighting areas needing intervention. Enhanced training programmes for healthcare providers and improved infrastructure in CHCs are recommended to support patient outcomes and risk reduction. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.