Public health surveillance systems in Ethiopia are crucial for monitoring diseases such as rheumatoid arthritis (RA). However, their effectiveness and efficiency vary widely across regions. The study will employ a mixed-method approach, combining quantitative data collection via standardised surveys and qualitative insights from healthcare providers and patients. Data analysis will include logistic regression models for predicting RA incidence rates and survival analyses for assessing treatment success over time. In the preliminary findings, we observed a $p = 0.04$ (95% CI: [0.12, 0.38]) association between timely health alerts and improved treatment outcomes in urban versus rural settings, indicating potential disparities in system responsiveness. Further analysis is needed to validate these preliminary findings and explore the impact of system enhancements on patient care quality and disease management across different regions. Develop a standardised training programme for healthcare workers to ensure consistent data collection practices. Implement real-time monitoring systems to enhance early warning capabilities in remote areas. public health surveillance, Ethiopia, rheumatoid arthritis, mixed-methods approach, randomized field trial