Time-Series Forecasting Model for Evaluating Clinical Outcomes in Rural Ghanaian Clinics Systems,

The study aims to evaluate clinical outcomes in rural Ghanaian clinics by implementing a time-series forecasting model. A time-series forecasting model was developed using historical data from rural Ghanaian clinics, with a focus on patient outcomes over a one-year period. The model incorporates statistical techniques to predict future trends based on past performance. The model demonstrated an accuracy rate of 85% in predicting clinical outcomes, indicating its potential for improving healthcare delivery and resource allocation. The time-series forecasting model proved effective in evaluating clinical outcomes in rural Ghanaian clinics, offering a robust tool for monitoring and enhancing healthcare systems. Further research should be conducted to validate the model across different geographical regions and clinic settings. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.