Lost to follow-up rate higher in pediatric patients with amblyopia on public insurance



Kim E, et al. Decrease in returning pediatric amblyopia patients and potential impact on visual outcomes. Presented at: Association for Research in Vision and Ophthalmology meeting; May 1-4, 2022; Denver.

Disclosures: Kim reports no relevant financial disclosures.

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DENVER — The rate of pediatric patients with amblyopia lost to follow-up is higher among those with public insurance, according to a presenter.

“By the ninth visit, you have over 50% of people that are lost to follow-up,” Earnest Kim told Healio/OSN at the Association for Research in Vision and Ophthalmology meeting. “The sad thing about it is that the interocular visual acuity, if you did have a completed visit, improves quite a bit through those nine visits. If you split these patients up into patients that have public or private insurance, then you see some different outcomes.”

Earnest Kim

Kim and colleagues conducted a retrospective study of 904 pediatric amblyopia patients from 0 to 9 years of age who started occlusion therapy between 2015 and 2018 at Oregon Health & Science University. They analyzed interocular visual acuity from office visits with optotype-based visual acuities grouped by insurance type.

There was an average of 4.1 completed appointments, 2.4 canceled appointments and 1.4 no-show appointments. A 46% decline occurred among returning patients by the fifth visit. Interocular visual acuity improved between the first and fifth visits from 0.277 ± 0.344 to 0.178 ± . 282 (P < .001).

There was a steeper decline in returning patients who had public insurance compared with patients who had private insurance (–23.4 vs. –15.3; P < .01). Approximately half of the patients who did not return for five visits may not have had an improvement in vision, the authors wrote, and further studies are needed to investigate factors that affect appointment adherence.

“Right now, what we’re trying to do is identify exactly which patients do better and which patients do not and what are those features that we can pull out through machine learning and then come up with an intervention or strategy to be able to identify those patients,” Kim said.

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