So the cost-effectiveness is likely to vary greatly.
Bilal Mateen, the chief AI officer at the health NGO PATH, says that the cost-effectiveness data around AI tools to preserve eyesight has been fairly strong in rich countries like the UK, or a few middle-income countries like China. But that isn’t the case for the rest of the world.
“With the rapid advances in what AI is capable of doing, we need to ask less if it’s possible, but more and more whether we’re building for everyone or just the privileged few. We need more than just effectiveness data for effective decision-making,” Dr Mateen urges.
Dr Channa points to the health equity gap even within the US, which she hopes that this tech can help bridge. “We do need to expand it to places that have even more limited access to eye care.”
She also stresses that older people and people with vision problems should see eye doctors, and the convenience of AI for routinely detecting diabetic eye disease should not deter attention to all the other eye diseases. Other eye conditions, like myopia and glaucoma, have proven tougher for AI algorithms to detect.
But even with those caveats, “the technology is very exciting,” says Dr Channa.
“I would love to see all our patients with diabetes screened in a timely fashion. And I think given the burden of diabetes, this is a really potentially great solution.”
