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Home Local

RANZCO’s plan to overcome ‘fragmented nature’ of NZ diabetic retinopathy screening

by Myles Hume
September 6, 2022
in International, Local, News
Reading Time: 3 mins read
A A
Of New Zealanders with diabetes, it is estimated that approximately 20-25% have diabetic retinopathy.

Of New Zealanders with diabetes, it is estimated that approximately 20-25% have diabetic retinopathy.

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RANZCO’s New Zealand Branch has launched its Position Statement on Diabetic Retinopathy and Diabetic Retinal Screening. It is calling for a national diabetic eye screening service with culturally safe hubs led by ophthalmologists overseeing RANZCO-accredited health providers.

In New Zealand, it is estimated that diabetes is present in 7%, and prediabetes in 26%, of the population. Of those with diabetes, it is estimated that approximately 20-25% have diabetic retinopathy. Diabetic retinopathy is a leading cause of blindness and sight loss in New Zealanders under 50, and disproportionately affects Māori and Pasifka populations.

In New Zealand, in 2018, an estimated 253,480 people were living with diabetes. In 2018/19 the prevalence of diabetes in Māori was 7.1% and in Pasifika peoples 11.2%. Māori were 1.85 times more likely to have diabetes compared to non-Māori (age- and gender-adjusted). Pasifika were 3.18 times more likely to have diabetes compared to non-Pasifka (age- and gender-adjusted).

At present, RANZCO said diabetic retinal screening across New Zealand was failing many patients because they are not engaged in the screening process.

“Patients are also losing vision because early treatment was not available to them as they were not identified as needing it. This particularly affects Māori and Pasifika people,” the college said.

Because of the fractured nature of the current program, records and information about patients are not easily accessible or transferable. It also means people are “at grave risk” of missing out on screening when they move between centres. Further, multiple local screening programs causes “unnecessary duplication” and there is significant variation between the patient pathways used by public health services.

The RANZCO-proposed national program would facilitate the seamless transfer of patients between centres.

Its position statement recommended a new focus on three key areas: the establishment of a national diabetic retinopathy screening program, supported by a Telehealth IT support system integrated into the existing health IT ecosystem and led by ophthalmology, who would provide clinical oversight and ensure the seamless integration of the screening program into existing eyecare services.

“Ideally, the screening program should allow patient feedback as this is very helpful in allowing the patient to understand their disease. For instance, carrying out the screening in the optometry and GP setting, where the photographer is trained in the identification of eye disease, does allow this,” RANZCO said.

In the model proposed by RANZCO, culturally safe hubs would be led by ophthalmologists who will oversee RANZCO accredited eye health providers, community health advocates and GPs.

The hubs would also provide timely and accurate assessment of retinal images, utilising artificial intelligence (AI), to diagnose and treat diabetic retinopathy before vision is irreparably lost.

“The use of (AI) for the grading of diabetic retinopathy is current in a number of overseas screening programs, most notably in Singapore, known as Singapore Integrated Diabetic Retinopathy Program (SiDRP), and is being trialled in some centres in New Zealand,” RANZCO stated.

“The use of AI to grade the retinal images significantly reduces the primary graders workload and enables the patient to be informed of the outcome of their retinal screening in real time at the point of care. The technology will allow our screening program to work smarter and more efficiently and will increase opportunities for patients to understand their disease and make modifications as needed. There is broad support amongst existing screening programs to adopt AI technology; however, the accuracy, validity and client-responsiveness of AI technology need to be continually reviewed to ensure that it is fit-for-purpose.

“In particular, the specificity threshold needs to be set at an appropriate level to avoid a high number of false-positive referrals, which may overload an already-stretched secondary service.”

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