Artificial Intelligence for the Automated Diagnosis, Triage, and Assessment of Patients With Hearing Loss and Tinnitus: A Pilot Comparative Study With Clinical Evaluation by Otolaryngologists
Trial ID: NCT07586098
Status: NOT_YET_RECRUITING
Study type: OBSERVATIONAL
Start date: 2026-05-30
Completion date: 2027-08-31
Sponsor: Royal Cornwall Hospitals Trust
Collaborators: University of Exeter; University of Birmingham
Conditions: Hearing Loss, Adult-Onset; Tinnitus
Interventions: Artificial Intelligence (AI) Assisted Clinical Decision Support Tool for managing Hearing Loss and Tinnitus
Locations: Treliske Hospital
Countries: United Kingdom
Enrollment: 1500
Age range: 18 Years - None
Sex: ALL

Summary:
Hearing loss affects approximately 11 million people in the UK, while tinnitus impacts around 7 million. Both conditions can significantly reduce quality of life and are linked to poorer mental health and employment challenges. Each year, tinnitus alone accounts for more than one million GP appointments, and patients referred to hospital ear, nose and throat (ENT) services often face long delays, sometimes exceeding a year, before their first assessment.

To address this demand, the Royal Cornwall Hospitals NHS Trust has developed a virtual ENT clinic. Patients undergo a validated hearing test in person and complete online questionnaires. Clinicians then review these data to determine next steps, which may include discharge with advice, referral for imaging, or a face-to-face consultation. Initial trials demonstrated that the majority of patients could be managed virtually, substantially reducing waiting times. However, clinicians must still review every case, limiting capacity for patients who require direct care.

This project builds on the virtual clinic by introducing artificial intelligence (AI) to support the assessment process. Using explainable AI methods, the system will be trained to replicate clinician-level decision-making while providing transparent reasoning for its recommendations. The study will evaluate how closely AI-generated outcomes align with clinician assessments, with all cases continuing to receive a clinician's final review. Clinicians will not be aware of the recommendations produced by the AI tool, but the study aims to measure how concordant AI recommendations are with clinician assessments.

If the AI tool's clinical recommendations closely align with clinician recommendations (the gold standard for care), the AI tool could be introduced as a clinical recommendation assistant tool, streamlining the triage and management of hearing loss and tinnitus, enabling clinicians to focus on complex cases, accelerating access to care, and improving efficiency.

Eligibility criteria:
Inclusion Criteria:

* Patients assessed in the RCHT virtual hearing loss and tinnitus clinic.
* Presenting symptoms of hearing loss and/or tinnitus.
* Ability to provide informed consent to participate in the study.

Exclusion Criteria:

* Individuals under 18 years of age.
* Patients unable to provide informed consent.
* Patients without sufficient English proficiency where translation services cannot be arranged.
* Cases where data quality is insufficient for analysis.

Outcomes:
MRI internal auditory meatus (IAM) referral recommendation; Clinical triage outcome