Comprehensive Eye Evaluation Algorithm CEEvA

Summary The objective of this project is to develop the Comprehensive Eye Evaluation Algorithm CEEvA a system to achieve blindness prevention in a cost effective way CEEvA uses fundus images and available personal medical data in the electronic medical record medical history and laboratory tests to automatically screen not only for DR but also for POAG and AMD in populations at higher risks CEEvA targets screening for three eye diseases in the following populations DR screening annually for every diabetic POAG screening for those with diabetes or with family history of POAG who are African American over the age of or who are Hispanic American aged and older and AMD screening for Whites over years The motivation of this project is to increase the efficiency of eye disease screening by detecting the main causes of blindness in the US population Currently diabetic retinopathy DR age related macular degeneration AMD and primary open angle glaucoma POAG affect million million and million people respectively Direct medical costs in the United States due to these three eye diseases are $ billion per year The effectiveness of screening for DR has generated multiple successful screening programs Although screening for only AMD and POAG has not been demonstrated to be cost effective in the population at large various studies have demonstrated that by screening the populations at higher risk for these diseases vision loss is reduced by up to The objectives of this project will be accomplished through two specific aims In Aim we will incorporate medical data to complement and augment the prototype fundus based algorithms previously developed for DR AMD and glaucoma detection In Aim our goal is to validate CEEvA software in an accurate and reliable way by using cases of retrospective data At the end of Phase I we will have a system ready for validation in a Phase II prospective study in preparation for an FDA clinical trial Narrative In the United States diabetic retinopathy DR age related macular degeneration AMD and primary open angle glaucoma POAG are the main causes of blindness affecting over million people In this project we will develop a Comprehensive Eye Evaluation Algorithm CEEvA a system that uses fundus images personal information and available laboratory tests to automatically screen for DR POAG and AMD at PCP practices This project addresses the public health need of providing more extensive eye screening to the population at high risk of vision loss thus potentially preventing blindness