Figure 1: Diagram showing gold standard assessment and three further strategies for diagnosis: tele-diagnosis, non-specialist diagnosis and prediction model diagnosis.
To date few studies have explored the validity or feasibility of such approaches for diagnosis of external and middle ear disease.
Tele-diagnosis using otoscopic images captured with an endoscope or smartphone has been shown to be successful if users are trained in image capture,5 but appears unsuccessful if users are given only instructions on use.6,7 The requirement for training may therefore limit the scalability of this approach.
Studies of non-expert diagnosis of outer and middle ear disorders are sparse, but results to date are not encouraging. In high income settings, medical students, audiology students and general practitioners report low self-confidence in diagnostic otoscopy.8 A recent study found poor reliability of nurse otoscopic diagnosis in Malawi.9 Validity of non-expert diagnosis therefore remains uncertain.
Prediction model diagnosis is largely unexplored in this field. For example (and to our knowledge) no study has explored if an algorithm using patient history is valid to diagnose or differentiate external or middle ear disorders.
Here we devised a novel study to directly compare the utility of tele-diagnosis, non-expert diagnosis, and prediction model diagnosis as a screening tool for common external and middle ear disorders. Our test bed was a cohort of patients presenting to an Ear, Nose and Throat (ENT) clinic in [removed for blind peer review] hospital in Cambodia (www.csc.org), a setting with high prevalence of otological disease.