Validation of a Virtual Model of Service Delivery for Choroidal Nevi

Choroidal Nevus

Choroidal nevomelanocytic lesions have a high prevalence affecting up to 7% of the entire population and are increasingly incidentally identified during routine eye check- ups in community optometry services. Given the tendency to err on the side of caution, there is evidence of excessive referrals challenging service delivery in both tertiary eye units and specialist ocular oncology services. Although previous studies have examined the natural history and risk factors for growth of choroidal nevomelanocytic lesions, optimal delivery of management remains uncertain. Management approaches display diversity with respect to the number and type of baseline investigations, the duration and frequency of monitoring of relevant patients. Utilisation of the skills of allied health professionals in appropriate cases would allow streamlining service delivery in a socialised healthcare system, maximise capacity, and allow community services to play an enhanced role. However, the evidence for this model of delivery is lacking. Within existing models of care for these lesions, patients are faced with delays, need for more than one attendances to the hospital and increased anxiety around prognosis. This project aims to answer the question of whether these low-risk, bland incidental findings might possibly be managed by allied health professionals with the use of clinical imaging and specific algorithms to make appropriate management decisions. We aim to validate a model of service delivery on a virtual basis that will accommodate for capacity pressures to accept all relevant referrals, while offering a safe service and optimising patient experience of care. We will thus validate the setting up of a virtual choroidal nevomelanocytic clinic in terms of safety and patient acceptability. More specifically, the degree of agreement between management decisions made by non-medical graders on the basis of imaging data alone as opposed to gold standard decisions (clinical and imaging tests combined) is examined. Health economics analysis of the proposed service delivery model will be undertaken to demonstrate cost-effectiveness.

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