AI Initiative at Lebanese Hospital Enhances Care Capacity for Palestinian Refugees
At Al Hamshari Hospital in Lebanon, an innovative Artificial Intelligence (AI) pilot is underway, aiming to empower healthcare professionals to deliver improved care to a growing population of Palestinian refugees. Situated near Ein el Hilweh, Lebanon’s largest Palestinian refugee camp, this hospital faces immense demand and limited resources.
Developed by Rhazes AI, a health technology startup with operations in the UK and Qatar, the AI platform offers an end-to-end intelligent assistant designed to streamline clinical workflows. This natural language processing tool supports medical staff by facilitating clinical decision-making, automating documentation, and reducing administrative burdens.
Operated by the Palestine Red Crescent Society, Al Hamshari Hospital serves thousands of refugees who lack access to Lebanon’s national healthcare system. Despite having only 80 beds and 56 physicians, the hospital manages to treat approximately 4,000 patients monthly. During crisis periods, surgical teams perform over 400 operations each month. Notably, it is the sole facility in southern Lebanon equipped with a functioning dialysis unit, underscoring its critical role in the region.
Zaid Al-Fagih, CEO and co-founder of Rhazes AI, highlights the hospital’s unique challenges: “This institution supports a population with no alternative healthcare options and operates under significant pressure.” He explains that physicians typically spend twice as much time on paperwork as they do with patients, a disparity that AI technology aims to address.
Adapting AI for Low-Resource Healthcare Settings
Unlike most AI healthcare applications concentrated in affluent countries such as the UK and UAE, this pilot represents a rare deployment in a resource-constrained environment. Al-Fagih emphasizes that such settings offer the greatest potential for impactful improvements.
The Rhazes AI platform is designed to function effectively without reliance on extensive hospital infrastructure. The pilot program at Al Hamshari Hospital, funded by Rhazes AI, operates similarly to a clinical trial: half of the medical staff utilize the AI tool, while the other half continue with standard procedures, allowing for comparative analysis of outcomes.
The AI system assists clinicians throughout the patient encounter by transcribing consultations in real time, offering diagnostic support, and generating evidence-based treatment plans. It automates the creation of structured clinical notes, billing codes, and admission documentation, significantly reducing administrative workload and enabling physicians to focus more on patient care. This tailored approach replaces the hospital’s previous reliance on generic, open-source medical guidelines, which were difficult to adapt to the local context.
Measuring Success and Overcoming Challenges
While the pilot is still in its early stages, success metrics will include patient throughput, clinical outcomes such as mortality rates relative to admissions, improvements in record-keeping accuracy, and satisfaction levels among both staff and patients.
Rola Soboh, a Rhazes AI associate overseeing the implementation, shares a personal connection to the project: “Having supported numerous health and humanitarian initiatives for refugees in Lebanon, I see this hospital as more than a facility-it’s a vital lifeline for the community.” She adds, “The relief AI provides extends beyond administrative tasks; it alleviates emotional and physical strain on doctors who serve entire communities.”
Data collection remains a significant hurdle. Al-Fagih notes the difficulty of evaluating the program’s impact in an environment where paper records dominate and computer access is limited. To address this, the team has enabled compliant use of doctors’ personal devices for data entry and monitoring.
This pilot marks the first AI clinical trial conducted in a low-resource setting, building on prior deployments in the UAE and UK. Its outcomes could pave the way for broader adoption of AI solutions in underserved healthcare environments worldwide.
