Listen to the audio version of this column here:
Let’s be honest: the current pace of clinical eye care is an artifact of the 20th century. It is stop-and-go, fragmented and incredibly inefficient. We are highly trained clinicians, yet we spend a tragic amount of our day acting as data entry clerks, transcriptionists and retail sales coordinators. We built our practices around the “waiting room”—a concept that should be obsolete! In the near future, if your patient spends more time in one of those than receiving clinical care, they may just make you obsolete from their lives too.
The promise of AI and augmented medical intelligence (AMI) is not about replacing the doctor; it is about replacing the friction. It is about shifting from a model of data collection to data interpretation in a more efficient way that allows for more connection, as well as more care.
When giving lectures, I often talk about what a minute means. I know that we often dismiss “saving two minutes” as negligible, but let’s look at what two minutes might actually mean as you become part of the AI revolution. In a high-volume clinic seeing 30 patients a day, two minutes per patient is an entire hour of clinical time. That hour isn’t just “more volume” — though that might certainly help profitability. That hour is the difference between a transactional “Which is better, 1 or 2?” and a transformational conversation about how a patient uses their vision to live their life. Or, it’s a two- minute conversation that establishes trust, or a two-minute discussion that improves compliance and changes that person’s life. That is what two minutes might mean. Do I have your attention now?
Let’s break it down and discuss how shattering our current bottlenecks with AMI could improve both the quantity and quality of care.
Patient Intake & History Taking: The Death of the Clipboard
In our current workflow, the patient fills out forms on a clipboard. The doctor or staff asks the same questions the patient has already answered on said forms, while typing into an EHR, back turned to the patient.
In the very near future, an AI-driven pre-visit intake will allow patients to answer dynamic, clinical-grade questions via text or voice before they arrive and in the comfort of their homes where they could actually go look and see what medication they are taking. By the time they sit in the exam chair, the “history of present illness” would already be drafted, summarized and red flags tagged for review. In this future, we stop being stenographers. That five to seven minutes that we now spend gathering data becomes five to seven minutes of analyzing data. We will start the exam knowing the story, allowing us to immediately build rapport rather than hunting for facts.
Differential Diagnosis & Diagnostic Test Efficiency: From Shotgun to Sniper
Currently we often run a “battery” of tests just to be safe, creating excessive and unnecessary data, not to mention patient fatigue. Or, we maybe miss a subtle sign and under-test. In tomorrow’s world, augmented intelligence will act as a diagnostic co-pilot.
Based on the intake and initial findings, AI algorithms suggest the exact necessary tests to not only refine the differential, but also the most efficient order to get to the final answer. The augmented intelligence will be our efficiency and success coach rolled into one. It won’t just say “glaucoma suspect;” AMI will highlight why (e.g., “RNFL thinning correlates with IOP spike history”). The net result is that we will stop over-testing “just in case” and start testing with precision. Think about how this will reduce the “traffic jam” at the OCT or visual field machines. Fewer unnecessary tests mean lower overhead and a faster patient journey, while the AI safety net catches subtle pathologies a tired human eye might miss at 4:45 on a Friday.
Clinical Decision-Making & Treatment Selection: Reducing Cognitive Load
I think about how difficult it is to be a health care provider these days. Providers have to mentally juggle guidelines, insurance formularies and the patient’s specific pathology to pick a treatment. Decision fatigue sets in by the afternoon (and somedays sooner).
Now imagine a world where the AMI instantly cross-references the patient’s diagnosis with the latest treatment protocols and their specific insurance coverage and presents the top three evidence-based treatment options with cost and efficacy comparisons instantly. The net result will be a removal of the “analysis paralysis” and administrative checking, allowing us to confidently present the best options to the patient in seconds. The quality of care rises and the adherence to best practices becomes automatic, not memory dependent.
Patient Education: Visualization over Verbalization
Contemplate how we currently educate our patients – arguably the second longest part of any clinical care delivery process. We explain complex concepts like “macular degeneration” using plastic models or verbal metaphors while the patient nods, often understanding very little and able to relay less to their loved ones at home.
In the next few years, we will use generative AI that creates personalized visual aids on the fly. You can show the patient their own retina, with an AI overlay showing exactly where the damage is and a simulation of how their vision will look in five years if untreated vs. treated. And they can reference that video at any time and share it with their family members. You have heard the saying that a picture is worth a thousand words; I think a personalized simulation might be worth a thousand minutes of explanation over a career or even a year. Patients will understand faster and adhere better. We will save time on repetitive explanations while drastically improving informed consent. And I personally am looking forward to the day that I don’t have to explain what a cataract is or how a progressive works one more time.
Retail Purchasing: The curated “Nudge”
Now let’s venture into the retail world of today, where the patient wanders the optical dispensary aimlessly, overwhelmed by 500 frames of every color and shape. The optician starts from scratch with their standardized spiel.
A few years from now, before the patient leaves the exam chair, AI has already analyzed their facial features, prescription strength and style preferences (scraped from their intake “style quiz” they did at home). It has curated a digital “tray” of five perfect frames that are in stock and lens-appropriate, making the hand-off seamless. The patient feels “seen” and understood. The “browsing time” is cut in half, increasing capture rate and optical throughput without the feeling of a hard sell. Frictionless fashion and function all wrapped up nice and neat. Love it!
The Financial Transaction: Invisible and Instant
Then we look at the most frustrating part of most practices: check-out. Our patients wait at a desk while a receptionist furiously clicks through billing codes, calculates copays and prints receipts. It is a buzzkill ending to what was hopefully a great visit. Talk about killing the mood.
In the not so distance future, AI will be listening and processing along the way. The AI will know exactly what was done and how long it took so it can code the exam in real-time, send all bills to the necessary parties and generate the patient’s final bill the moment the exam ends. The payment is processed automatically via a card on file, or a single tap. You know, kind of like every other financial transaction occurs in the rest of the world. Imagine that! The front desk bottleneck vanishes, and maybe even the front desk itself no longer exists because it will no longer serve a purpose. The staff can focus on scheduling and greeting – not math. The patient leaves with a feeling of modern efficiency, not administrative friction.
My Challenge to the Industry
We are accepting a “slow” standard of care because “that’s how it’s always been done.” But in a world where AI can drive cars, using it to drive clinical flow is not futuristic—it is overdue. The clinics that adopt these tools will not just be faster; they will be the ones where doctors actually look patients in the eye, because they aren’t too busy looking at a screen. Now that is a novel concept, and a human care evolution worth considering.
Author
