UK-Qatar health tech startup launches first-of-its-kind AI clinical assistant pilot at Al Hamshari Hospital, serving Palestinian refugees in southern Lebanon. The controlled trial evaluates artificial intelligence’s capacity to reduce administrative burden on frontline doctors managing extreme patient loads in under-resourced environments.
A pioneering deployment of artificial intelligence clinical scribes has commenced at Al Hamshari Hospital in southern Lebanon, marking the first structured implementation of AI assistance technology within a conflict-affected health system. The initiative, led by UK-Qatar startup Rhazes AI, represents a significant shift in how advanced medical technologies can be adapted for humanitarian healthcare settings.
Critical healthcare infrastructure under pressure
Al Hamshari Hospital, operated by the Palestine Red Crescent Society near Ein el Hilweh refugee camp, faces extraordinary operational demands. With 80 beds, 56 doctors, and 31 nurses, the facility serves over 4,000 patients monthly whilst performing more than 400 surgeries during crisis periods. The hospital remains the sole provider of dialysis services for southern Palestinian refugee camps in Lebanon.
Palestinian refugees in Lebanon are systematically excluded from the national healthcare system, creating an isolated medical ecosystem where facilities like Al Hamshari must provide comprehensive care with limited international support. This exclusion compounds the clinical workload, with doctors frequently managing upwards of 60 patients daily across multiple specialties.
The hospital’s medical staff, predominantly Palestinian doctors, function simultaneously as generalists, specialists, and emergency physicians due to the absence of referral pathways or tertiary care facilities. This multidisciplinary approach, whilst necessary, intensifies the administrative and clinical burden on individual practitioners.
AI technology adaptation for low-resource environments
Rhazes AI’s clinical assistant platform addresses these challenges through real-time consultation transcription, diagnostic reasoning support, and evidence-based management plan generation. The agentic system operates without requiring extensive hospital infrastructure, adapting to the resource constraints typical of humanitarian medical facilities.
The technology automates documentation processes, generating structured summaries, admission notes, billing codes, and patient record insights. This functionality directly targets the administrative burden that disproportionately affects overstretched clinical teams in under-resourced settings.
Dr Zaid Al-Fagih, co-founder and CEO of Rhazes AI, commented: “This collaboration is about bringing tools usually reserved for high-tech, high-resource hospitals into the hands of clinicians working on the frontlines. Advanced tools don’t need to wait for perfect conditions, they, and should, start where the need is greatest.”
Clinical evidence base and implementation methodology
The deployment builds upon previously published evidence in Emergency Medical Journal demonstrating the platform’s capacity to reduce documentation time by over 60 percent. The current pilot operates as a non-randomised, controlled implementation trial from August to November 2025, assessing impacts on documentation time, decision confidence, and patient flow.
Rola Soboh, a Rhazes AI associate implementing the pilot, highlighted the personal significance of the initiative: “Doctors here don’t just treat patients, they carry entire communities. So, when we talk about easing their load, it’s not just administrative, it’s emotional, physical, everything.”
The pilot represents a critical evaluation of AI technology’s applicability in humanitarian healthcare contexts, potentially establishing frameworks for similar implementations across under-resourced medical environments globally. The partnership between Rhazes AI and the Palestine Red Crescent Society demonstrates how private sector innovation can address systematic healthcare inequities in conflict-affected regions.
