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

BACKGROUND

Hearing loss affects approximately 11 million people in the UK, while tinnitus impacts around 7 million.1,2 Both conditions can significantly reduce quality of life and are linked to poorer mental health and employment challenges.3 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.4 This was exacerbated even further following the coronavirus (COVID-19) pandemic.5

To address this demand, the Royal Cornwall Hospitals NHS Trust has developed a virtual ENT clinic to manage patients with hearing loss and/or non-pulsatile tinnitus. 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. Inclusion criteria for the virtual clinic for hearing loss and non-pulsatile tinnitus were: ≥16 years of age; subjective bilateral hearing loss and/or tinnitus that did not fulfil the criteria for direct referral to audiology (they would see patients ≥50 years of age); subjective asymmetrical sensorineural hearing loss; and subjective unilateral non-pulsatile tinnitus. Exclusion criteria for the virtual clinic for hearing loss and non-pulsatile tinnitus were: cognitive, motor or visual impairment that may preclude use of an iPad®; patients who had been referred back to ENT having previously been fully medically assessed (redirected to audiology or hearing therapy where appropriate); and symptoms that required a face-to-face appointment (conductive hearing loss, pulsatile tinnitus, vertigo or dizziness, pain, discharge, infections, abnormal ear examination, and history of ear disease, surgery or ear injury).6

Published results demonstrated that most patients could be managed virtually, substantially reducing waiting times.6 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, as a clinical decision support system (CDSS). Using explainable AI methods, the system is trained to replicate clinician-level decision-making while providing transparent reasoning for its recommendations. This retrospective and prospective observational feasibility pilot study aims to evaluate how closely AI-generated outcomes align with clinician assessments, with all cases continuing to receive a clinician's final review. Clinicians will be blind to 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.