Exclusive Coverage of the GA Patient Population
High-quality, Image-derived Insights
Comprehensive View into Disease Progression & Severity
Only found here from the IRIS Registry (Intelligent Research in Sight)
Using novel machine learning and computer vision algorithms
From diagnosis to subfoveal involvement and more
By the Numbers
Total de-identified patients with GA*
GA patients confirmed through images
Clinicians contributing
*Defined as patients who are 50 years or older and who have an ICD-10 code for GA (H35.31x3,4) or ICD-code for age-related macular degeneration (AMD) and either an image or clinical note indicating geographic atrophy between January 2013 and July 2025.
Data current to July 2025.
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Key Variables in Geographic Atrophy Research
Qdata Geographic Atrophy gives insights into the entire patient journey, from diagnosis to subfoveal involvement and more. Verana Health provides curated variables extracted from EHR data and/or images to be utilized based on your research needs, including:
GA Diagnosis
Diagnosis of patients with geographic atrophy is determined by the ICD-10 code, as well as via notes and images.
Visual Acuity
This outcome measures how well the eye can distinguish objects and shapes from a distance.
Lesion Location
This variable indicates whether the lesion is nonsubfoveal or subfoveal and is derived from ICD-10 codes, images, and notes.
Lesion Growth Rate
To calculate lesion growth rate, there must be at least two imaging visits at least six months apart. Growth rate is faken from FAF images.
Lesion Size, Perimeter, and Count
This includes the specifics of the lesion, as well as how many lesions there are, and are currently derived from FAF images.
Unstructured GA EHR Data Provides a Deeper Understanding
Real-world evidence through analysis of quality real-world geographic atrophy data can change the way patients are treated for this condition. Computer vision (CV) and machine learning (ML) algorithms can transform clinical images into high-quality image data, providing quality, research-ready insights. Verana Health’s Qdata can provide the right clinical data to help researchers track disease progression, severity, and more.
As new treatments are coming to market, real-world data in geographic atrophy is a growing area of focus to support the drug lifecycle from clinical development through to commercialization. Using this data module, life sciences companies can more easily evaluate patient outcomes, identify clinical trial sites, and generate market insights.
0%
of Medical Data Remains Unstructured
Read More About Qdata Geographic Atrophy
Check out publications, blogs, and news related to our work in geographic atrophy research.
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