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arXiv · 2502.05603

AI-Driven Electronic Health Records System for Enhancing Patient Data Management and Diagnostic Support in Egypt

Arwa Alorbany·Mariam Sheta·Ahmed Hagag·Mohamed Elshaarawy·Youssef Elharty·Ahmed Fares
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Abstract

Digital healthcare infrastructure is crucial for global medical service delivery. Egypt faces EHR adoption barriers: only 314 hospitals had such systems as of Oct 2024. This limits data management and decision-making. This project introduces an EHR system for Egypt's Universal Health Insurance and healthcare ecosystem. It simplifies data management by centralizing medical histories with a scalable micro-services architecture and polyglot persistence for real-time access and provider communication. Clinical workflows are enhanced via patient examination and history tracking. The system uses the Llama3-OpenBioLLM-70B model to generate summaries of medical histories, provide chatbot features, and generate AI-based medical reports, enabling efficient searches during consultations. A Vision Transformer (ViT) aids in pneumonia classification. Evaluations show the AI excels in capturing details (high recall) but needs improvement in concise narratives. With optimization (retrieval-augmented generation, local data fine-tuning, interoperability protocols), this AI-driven EHR could enhance diagnostic support, decision-making, and healthcare delivery in Egypt.

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Arwa Alorbany, Mariam Sheta, Ahmed Hagag, Mohamed Elshaarawy, Youssef Elharty, Ahmed Fares. 2025-02-08. AI-Driven Electronic Health Records System for Enhancing Patient Data Management and Diagnostic Support in Egypt. https://arxiv.org/abs/2502.05603

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