Electronic Data Tracking Enhances Rapid Diagnostic Test Accuracy in Malaria Diagnosis in Rural Kenyan Communities,

Malaria remains a significant health issue in rural Kenyan communities, necessitating accurate diagnostic tools to guide treatment decisions. The study employed a mixed-method approach including field observations, RDT testing, and electronic data collection through mobile health applications. Data were analysed using statistical software to evaluate diagnostic performance. Electronic data tracking improved the consistency and timeliness of malaria diagnosis by reducing errors from manual record-keeping processes. The integration of electronic data systems significantly enhanced the reliability of RDTs in rural settings, particularly in diagnosing early-stage cases. Continued use of electronic health records is recommended to maintain and improve diagnostic accuracy across different healthcare facilities. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.