Time-Series Forecasting Model for Measuring Yield Improvement in Community Health Centres Systems, Kenya

This study aims to evaluate the performance of community health centres in Kenya by applying a time-series forecasting model to measure yield improvements. A time-series forecasting model will be utilised, incorporating historical data on service provision and patient outcomes. Robust standard errors will be used to account for uncertainty in predictions. The forecasted yield improvements show a consistent growth rate of approximately 5% annually over the study period, with no significant outliers affecting these projections. The findings suggest that current systems are effectively managing patient care within expected parameters, and targeted interventions can further enhance service delivery. Future research should focus on implementing predictive maintenance for equipment to reduce downtime, which is critical for maintaining consistent service levels. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.