The Inherited Retinal Disease Pathway in the United Kingdom: a Patient Perspective and the Potential of AI
Wong, W.; Sumodhee, D.; Morris, T. A.; Tailor, B.; Hollyhead, C.; Woof, W. A.; Archer, S.; Veal, C.; Lobo, L.; Daich Varela, M.; Cabral De Guimaraes, T. A.; Gomes, M.; Shah, M.; Downes, S. M.; Madhusudhan, S.; Mahroo, O. A.; Webster, A. R.; Michaelides, M.; Pontikos, N.
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BackgroundInherited Retinal Diseases (IRDs) are the leading cause of blindness in young people in the UK. Despite significant improvements in genomics medicine, diagnosis of these conditions remains challenging, with many patients enduring lengthy diagnostic odysseys and even after genetic testing around 40% of them do not receive a definite genetic diagnosis. This survey aims to explore the experience of individuals affected with IRDs, their relatives, friends and caregivers, and the potential acceptability of an AI technology, such as Eye2Gene. MethodsThis cross-sectional survey was distributed electronically using the Qualtrics-encrypted platform between April to August 2024. The mixed-methods survey included Likert-scale and open-ended queries. Analysis was performed using descriptive statistics and content methods. ResultsThe survey was answered by 247 respondents of which 79.8% were patients and the remainder were relatives, friends and caregivers. There was substantial variability in patient diagnostic journeys in terms of waiting times to see a specialist (IQR 1 to 4 years), commute required (IQR 10 to 74 miles) and number of visits to reach a diagnosis (IQR 2 to 4). A substantial proportion of patients had a change in diagnosis had a change in diagnosis (35.8%). The majority of respondents were overwhelmingly in favour of the integration of AI into the IRD pathway to accelerate genetic diagnosis care (>90%). ConclusionThis survey identifies several key gaps and disparities in the IRD pathway which can be addressed in part by the integration of AI for more equitable care. Survey also revealed a favourable attitude towards incorporating AI into the diagnostic testing of IRDs. SynopsisA survey by 247 people directly or indirectly affected by inherited retinal diseases in the UK reports substantial gaps and disparities in the patient diagnostic pathway which could in part be addressed by Artificial Intelligence.
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