Uveitic Macular Edema Real-World Data

UME is the most common cause of permanent vision loss in uveitis. Qdata® can change the future of managing this condition.

Qdata UME (Uveitic Macular Edema) unlocks real-world insights on this difficult to identify population by linking structured codes and unstructured EHR notes to confirm diagnosis and understand outcomes.

About Qdata UME

Uveitic macular edema (UME) is the leakage of fluid within retinal layers, and is a common complication of uveitis. UME can lead to changes in vision, damage to the eye, or even permanent vision loss. There is no single ICD-10 code to identify UME, so it is important to mine clinical notes within EHRs and use UME real-world data to see when clinicians have noted findings from ophthalmic images to capture a larger patient cohort for real-world UME research.

Verana Health is the exclusive real-world data curation and analytics partner of the American Academy of Ophthalmology IRIS® Registry (Intelligent Research in Sight). Qdata UME is curated data from the IRIS Registry that offers life sciences companies a real-world understanding of treatment patterns and outcomes of this difficult to identify patient population.

 

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Exclusive Coverage of the UME Patient Population

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Confirmed Diagnosis of UME Patients

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Detailed Understanding of Treatments and Outcomes

Only found here from the IRIS Registry (Intelligent Research in Sight)

Using ICD-10 codes and clinical notes

Including key variables such as VA, CST, and IOP

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By the Numbers

K+

Total de-identified patients with UME*

Years

Average follow up time

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*Includes patients with a diagnosis of UME based on ICD-10 codes or clinical notes from the IRIS Registry who are 18+ years old between January 2016 and July 2025.

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Key Variables in UME Research

Qdata UME offers insights into the entire patient journey, from diagnosis to visual acuity and more. Verana Health provides UME real-world data with curated variables, which are extracted from EHR data, to be utilized based on your research needs. These key variables include:

Visual Acuity

Measures how well the eye can distinguish objects and shapes from a distance

Central Subfield Thickness

Measurement of the thickness of the central part of the retina, typically determined using optical coherence tomographic imaging

Intraocular Pressure

The pressure inside the eye. An increase in IOP is a common adverse effect of UME steroid treatment

Unstructured UME Real-World Data With Patient Outcomes

Real-world evidence through analysis of quality uveitic macular edema real-world data can help advance treatments for this condition. Artificial intelligence (AI) techniques, such as machine learning and natural language processing, enable Verana Health to identify UME patients based on data within the EHR clinical notes. These techniques are also applied to extract key UME patient outcomes, such as visual acuity and central subfield thickness, as well as intraocular pressure, which can be a common side effect of UME steroid medication. These variables are key in furthering UME research. 

 

Qdata UME can provide insights to help support clinical development teams looking to identify UME patients for their next study, HEOR and medical affairs teams looking to understand real-world therapy utilization or commercialization teams looking to gain market insights on their UME therapies.

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of Medical Data Remains Unstructured

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