Exclusive Diabetic Retinopathy Insights
Comprehensive View into the Patient Journey
Detailed View of Anti-VEGF Treatment
Only found here from the IRIS® Registry (Intelligent Research in Sight)
Key variables including visual acuity and CST
Across diabetic retinopathy and DME patients
By the Numbers
Total de-identified patients with diabetic retinopathy (without DME)*
Total de-identified patients with diabetic retinopathy with DME**
Median length of follow-up for diabetic retinopathy patients
*Defined as patients >=18 with >=1 ICD-10 code for Diabetic Retinopathy from January 2016 to July 2025, with a corresponding CPT or HCPCS code on the same date as the diagnosis.
**Patients are not mutually exclusive
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Key Variables in Qdata Diabetic Retinopathy
Curated variables extracted from EHR data and/or images to be utilized based on your research needs.
Visual Acuity
Central Subfield Thickness (CST)
Unstructured Data Enables Deeper Understanding
Qdata modules consist of carefully curated datasets that are readily available for research purposes, enabling the generation of real-world evidence (RWE).
Verana Health applies clinician-informed algorithms to unstructured EHR data at scale to help extract key information on visual acuity, CST, anti-VEGF procedure details and more, which can then be analyzed across large populations in a reliable manner.
This can give life sciences companies unprecedented insights to better understand treatment patterns and outcomes, run comparative effectiveness studies, monitor market uptake, and more.
0%
of Medical Data Remains Unstructured
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