Public health surveillance systems are crucial for monitoring disease outbreaks and enhancing public health responses in Ghana. A systematic review approach was employed to identify, assess, and synthesize studies on public health surveillance systems. A time-series forecasting model incorporating ARIMA (AutoRegressive Integrated Moving Average) methodology will be applied to predict future adoption trends in Ghanaian public health surveillance systems. The analysis identified a significant increase in the proportion of healthcare facilities adopting electronic record-keeping systems from 20% in to 43% in , with robust standard errors indicating the reliability of these estimates. This study provides insights into the evolving landscape of public health surveillance systems in Ghana and offers a forecast model for future system adoption. Public health officials should prioritise investment in infrastructure upgrades to support more advanced electronic record-keeping systems, aligning with emerging trends identified in this analysis. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.