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AI Trial Expands Patient Access with Multilingual Clinical Consultations

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Posted on Thursday 17 July 2025

A new collaboration is set to transform healthcare accessibility with the launch of a multilingual AI clinical assistant which will break down language barriers in healthcare, empowering patients to receive care in their preferred language.
A woman with a light brown skin tone holds a mobile horizontally close to her mouth. An overlaid graphic illustrates a conversation and a small chatbot

The initiative - A Multilingual, Telephone-Based AI Conversational Agent for Cataract Surgery Follow-Up, is led by UK artificial intelligence company Ufonia in partnership with Moorfields Eye Hospital, London, the Centre for Assuring Autonomy (CfAA) at the University of York, and Health Innovation Oxford and Thames Valley.

At the heart of this project is the first ever clinical trial of the multilingual capabilities of  an automated AI conversational system designed to conduct follow-up visits with patients over the phone in a safe and empathetic way.

Ufonia’s English language-based product, Dora, has already transformed cataract surgery care in the UK and has safely and effectively conducted over 60,000 NHS appointments. This new project aims to extend its reach to patients who speak one of ten other common non-English languages including Polish, Bengali and Spanish.

Bridging the Gap for Over a Million Patients

Language barriers affect more than a million people in the UK, which can lead to reduced access to care and poorer health outcomes. This trial will make it easier for Moorfields to reach a broader range of patients.

“Having AI-initiated contact will better serve our patients who come from many different ethnic backgrounds whilst minimising digital exclusion”, said Badrul Hussain consultant ophthalmologist and trial co-Primary Investigator at Moorfields Eye Hospital.

“In 2024, 9% of NHS e-referral service letters were in a language other than English, so there is a lot of need for cost-effective translation”  added Alex Day, consultant ophthalmologist and trial co-Primary Investigator at Moorfields Eye Hospital. 

This clinical trial involves 800 cataract surgery patients at NHS Moorfields Eye Hospital, which serves a highly diverse patient population. Each patient will receive a call from Dora in their preferred language before attending their standard in-person follow-up appointment.

Patient engagement work led by the Oxford Health Innovation Network will ensure that patients play an active role in shaping the technology. 

 “Using language that is easy to understand is essential in healthcare. Through working with people whose first language is not English, we hope to capture cultural nuances to facilitate Dora to undertake a culturally appropriate conversation.” - Sian Rees Director, Community Involvement and Workforce Innovation at Health Innovation Oxford and Thames Valley, and Public and Patient Involvement lead for the trial.

Looking Ahead: A Multilingual Future for AI Healthcare

The Centre for Assuring Autonomy (CfAA), under the leadership of Research Director Professor Ibrahim Habli, will support the development of a robust safety framework to ensure the responsible deployment of the technology.

“Safety is fundamental for deploying impactful and trustworthy AI technology that addresses urgent healthcare needs. We're excited to collaborate with such an outstanding multidisciplinary team and take a human-centric approach to assuring safety from the outset and throughout,” said Professor Habli.

Insights from this trial will pave the way for Dora to gain regulatory approval for multilingual operations and expand its language capabilities further. By demonstrating AI’s potential to reduce healthcare inequalities, Ufonia hopes to set a new standard for accessible, scalable, and patient-centered care.

“By combining cutting-edge AI with patient-centered innovation, we aim to create a system that truly works for everyone, regardless of the language they speak,” said the trial co-Chief Investigators Aisling Higham and Ernest Lim.

Notes to editors:

This initiative is made possible through funding from NIHR.