Public health surveillance systems are crucial for monitoring disease prevalence and guiding public health interventions. In Uganda, such systems have been implemented but their effectiveness in measuring clinical outcomes remains under scrutiny. A stratified random sampling design was employed to select two districts for this study. A mixed-method approach combining quantitative data from electronic health records and qualitative insights from healthcare providers was used to assess the system's accuracy in reporting clinical outcomes. The analysis revealed a significant misclassification rate of 20% in reported fever incidence, indicating potential discrepancies in disease surveillance. This study underscores the need for methodological improvements in Uganda’s public health surveillance systems to enhance their reliability in capturing clinical data accurately. Immediate steps should include refining diagnostic criteria and standardising reporting protocols to improve data quality and consistency. Public Health Surveillance, Clinical Outcomes, Randomized Field Trial, Uganda Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.