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A Clinical Trial Will Test if AI Can Speed Up Hearing and Tinnitus Care

In the UK, tinnitus alone drives more than one million primary care appointments each year. For patients sent to hospital ear, nose, and throat (ENT) specialists, the wait for a first assessment can stretch beyond 12 months. A new clinical trial led by the Royal Cornwall Hospitals NHS Trust will test a potential solution: an artificial intelligence assistant designed to help clinicians triage and manage hearing loss and tinnitus more efficiently.

The Virtual Clinic Foundation and Its Next Step

To manage overwhelming demand, the Royal Cornwall Hospitals NHS Trust already runs a virtual ENT clinic for hearing loss and non-pulsatile tinnitus. Patients complete an in-person hearing test and online questionnaires. A clinician reviews the data and decides on next steps, which could be discharge with advice, a request for imaging, or an in-person consultation.

Initial results showed this virtual model could manage most patients remotely, reducing waiting times. However, the requirement for a clinician to review every single case remains a bottleneck. It limits capacity and takes time away from patients with more complex needs. This trial aims to address that constraint by introducing an AI system to act as a clinical recommendation assistant.

How the AI Hearing Health Trial Works

This is an observational study. The intervention is the AI tool itself, which will process the same patient data that clinicians see. Patients will undergo the standard virtual clinic pathway: they take a validated hearing test and complete questionnaires about their symptoms and impact on life. All participants must be 18 or older, have symptoms of hearing loss or tinnitus, and be able to provide informed consent.

The core of the study is a blind comparison. The AI system, trained using explainable AI methods to mirror clinical reasoning, will analyze each case and generate a management recommendation. Separately, a hospital clinician will review the case and make their own standard decision, unaware of the AI’s suggestion. Researchers will then measure how closely the AI’s outputs align with the clinicians’ assessments, which serve as the gold standard.

The goal is not to replace clinicians but to assist them. If the AI’s recommendations show strong concordance with expert judgment, it could be integrated as a support tool. This would allow clinicians to confirm AI-assisted recommendations quickly, focusing their expertise on complex or ambiguous cases that require deeper investigation.

The Scale of the Problem and the Potential of AI

Hearing loss affects an estimated 11 million people in the UK, and tinnitus affects around 7 million. Both conditions are strongly associated with reduced quality of life, poorer mental health, and challenges in employment. The backlog for specialist care, worsened by the COVID-19 pandemic, makes finding efficient management pathways urgent.

The AI system in this trial is built to be transparent. “Explainable AI” means the tool is designed to show its working, providing clinicians with the reasoning behind each recommendation. This transparency is essential for clinical trust and safety, ensuring the AI is a collaborative tool rather than a black box.

Current Status and What Success Would Mean

The trial is currently listed as NOT_YET_RECRUITING. It aims to enroll 1,500 participants from the pool of patients already being assessed through the Royal Cornwall Hospitals’ virtual hearing loss and tinnitus clinic.

For patients, a successful outcome could mean significantly faster access to care. An effective AI assistant could streamline the triage process, ensuring those who need urgent or face-to-face care are identified quickly, while others receive appropriate advice and management without a long wait. For clinicians, it could reduce administrative burden, freeing up time for direct patient care and complex decision-making. For healthcare systems, it offers a model to manage high-volume conditions more sustainably, potentially improving outcomes for millions living with hearing loss and tinnitus.

Source:
AI-assisted Diagnosis, Triage and Assessment of Hearing Loss and Tinnitus (ClinicalTrials.gov: NCT07586098)

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