Enhancing Physicians' Adherence to the 2023 Sudan Malaria Case Management Protocol Using AI as an Intervention Tool

利用人工智能作为干预工具,提高医生对2023年苏丹疟疾病例管理方案的依从性

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Abstract

BACKGROUND AND OBJECTIVE: Malaria remains a major health issue in Sudan, and physicians' non-adherence to treatment protocols has negatively impacted patient outcomes. The 2023 Sudan Malaria Case Management Protocol advocated new developments per the national and globally WHO-recommended levels, but there are still gaps in clinical practices. To improve physician compliance and standardize malaria care, decision-support tools can be based on artificial intelligence (AI). This study aims to examine the effect of the introduction of an AI-based clinical decision-support system (CDSS) on the adherence of physicians to the 2023 Sudan Malaria Case Management Protocol at Al-Managil Teaching Hospital (Managil, GZ, SDN). METHODS: A two-cycle clinical audit was conducted between July and September 2025 (baseline audit followed by AI intervention and then re-audit after AI intervention). The current practice and pre-intervention knowledge (n=50 physicians) were evaluated through questionnaires. An AI-CDSS was implemented together with training, incorporating diagnostics, treatment recommendations, and special group advice (pregnancy, neonatal, and G6PD). Compliance rates before and after the intervention were compared, with statistical testing including effect sizes and 95% confidence intervals. RESULTS: Recognition of the 2023 protocol increased from 38% to 100% (risk difference +62%, 95% CI: 48-76; p<0.001), and awareness of intravenous (IV)/intramuscular (IM) artesunate as first-line treatment rose from 53% to 98% (risk difference +45%, 95% CI: 32-58; p<0.001). Attitudes towards severe malaria improved from 15% to 91% (risk difference +76%, 95% CI: 61-91; p<0.001). The timely initiation of treatment within 24 to 48 hours improved to 100% (p < 0.001). Mean compliance increased from 50.7% (95% CI: 42-59) to 96.8% (95% CI: 92-100, p<0.001). Residual deficiencies persisted in microscopy reporting and G6PD testing. CONCLUSION: A combination of an AI-driven CDSS and focused training demonstrated a substantial improvement in physician compliance with the 2023 Sudan Malaria Case Management Protocol, particularly in critical care aspects. However, a possible Hawthorne effect and the absence of clinical outcome data (e.g., morbidity, mortality) should be acknowledged as limitations. Greater scale-up of this approach, while addressing infrastructural and digital literacy challenges, could have a major impact on malaria case management and disease burden in Sudan.

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