What if legendary ophthalmologist Don Gass, MD, had access to both optical coherence tomography (OCT) and artificial intelligence? One can only imagine the breakthroughs.

Alex Walsh, MD, CEO of Envision Diagnostics and a retina specialist at Retina-Vitreous Associates in Los Angeles and vicinity, wants to bring Gassian interpretive capabilities to everyone in eye care.

His company’s product, a binocular OCT with the potential to image the entire eye, could enable physicians and technicians to get objective, comprehensive data in six minutes. No waiting, no moving from room to room. The device performs many of the functions of a routine eye exam, including slit lamp and dilated fundus exams, reducing the visit time from hours to minutes.

Dr. Walsh says the device brings clinical trial–level data to every exam, which is something eye-care professionals should be demanding. “We spend three times as much on labor as we do on devices, and we accept it as the cost of doing business,” he tells OIS podcast host, Retina-Vitreous Associates’ colleague and OIS Podcast host Firas Rahhal, MD. “The linear model of a routine workflow is clearly inefficient.”

Listen to the full podcast today to hear Dr. Walsh and Dr. Rahhal discuss how automation can transform the eye exam and how a binocular OCT can bring objective, quality data to eye-care professionals everywhere. Here’s what they cover:

The advantages of an all-in-one diagnostic device for optometrists and ophthalmologists.
The intellectual property and funding challenges that prompted Dr. Walsh to launch his product outside the academic environment.
Early concepts of the Envision device and how it evolved into its current iteration.
The proposed regulatory pathway for Envision’s OCT and what preliminary tests show.
How lean manufacturing processes inform the Envision diagnostics philosophy.
Whether entire-eye binocular OCT could influence a wave of new, more effective treatment options.
The potential of automated diagnostics to improve the quality of data used for analysis, and what needs to change to make Big Data work for eye care.
What’s next: AI as a diagnostic tool.

Click “play” to listen.

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