Introduction
Globally 6% of the population, or around 466 million people, suffer
from disabling hearing loss (www.who.int/pbd/deafness/estimates/en/),
and the majority reside in low- and middle-income countries. One barrier
to tackling this large burden is the lack of specialist health workers
to recognise and manage ear and hearing disorders.1
Fuelled by technological advances, there is growing interest in remote
or non-expert diagnosis in ear and hearing care. However, studies to
date have been limited, mostly focused on screening for hearing loss,
without exploring additional symptoms or signs which may signify middle
or external ear disorders. This is important: of those suffering
disabling hearing loss, around half (200 million) are thought to be due
to chronic suppurative otitis media (CSOM),2 where
surgical intervention may be indicated.
Diagnosis of external and middle ear disorders is based on clinical
history, including symptoms of otalgia, otorrhoea, and hearing loss,
supplemented by otoscopy to visualise the ear canal and tympanic
membrane. Diagnostic accuracy relates to expertise and experience of the
assessor. Specialist assessment with appropriate tools (including a good
quality otoscope) is the gold standard, but due to resource gaps in
equipment and specialist health personnel, is not universally available.
We recognise three alternative strategies (Figure 1):
- Telediagnosis,3 where relevant diagnostic
information is captured (usually by a non-specialist) and sent to a
specialist
- Non-expert diagnosis, where a non-specialist (defined as someone with
less training or experience than a specialist) makes a diagnosis.
- Prediction model diagnosis,4 where data from a
diagnostic tool is fed into an algorithm, with no or minimal human
interpretation