Tag: AI

Why Online Practice Visibility Matters More Than Ever

Digital Marketing, Marketing

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Google, ChatGPT, AI

AI is not just changing how patients search. It is changing what shows up and what they actually see. Visibility today is about shaping the digital signals that AI platforms rely on to guide patient decisions.

Ask most practice owners what visibility means

You will hear a range of answers: being on Google, showing up in search, posting on social media. But all of those channels have evolved and so has the way patients engage with them. Visibility is not only about being found; it is about being chosen. In a post-AI landscape, how your practice is seen matters just as much as where it appears.

AI changed the optics, literally

Until recently, most patients searched for care using familiar tools like Google Maps, “near me” searches, or Instagram location tags. But with the rise of large language models such as ChatGPT, Google’s AI Overviews, and Perplexity, a new shift has taken place. AI is now interpreting your entire online presence for the patient.

Patients can ask a question like:
“What is the best eye doctor near me who takes time with patients?”

Instead of offering a list of websites, AI now delivers a direct response based on patterns pulled from reviews, business listings, social posts, and web content.

If your practice has the right signals in place, it can become the answer. If those signals are missing, if your reviews are generic, your Google Business Profile is outdated, or your website lacks specific content on common conditions, your practice may not be shown at all.

Your practice is a data source, whether you know it or not

Here is what many practices have not yet realized: you do not need to opt in for AI tools to pull your data. These systems are already scanning and summarizing the public web, including:

  • Your Google Business Profile (Get Started)
  • Patient reviews
  • Instagram captions and hashtags
  • Website content and FAQs
  • Online articles or directories

AI platforms like OpenAI’s models and Google’s new Overviews are not just scanning one post or listing. They are gathering information from dozens or even hundreds of sources and using those signals to generate a synthesized, direct answer to the patient’s question.

Your practice is not judged by a single listing or blog post. It is being interpreted based on the totality of your digital presence across platforms, formats, and third-party mentions.

The story AI tells about your practice is not based on what you say. It is based on what the internet says about you. And in many cases, that story is incomplete or outdated.

Discoverability has a new layer

Traditional local search focused on:

  • Proximity / Location
  • Keyword relevance
  • Website performance

These factors still matter, but AI has added a new layer of context. It now considers:

  • Does your content answer patient-specific questions?
  • Do your reviews speak to real outcomes?
  • Are you mentioned or referenced outside of your own website?

AI does not simply collect information. It summarizes it. This means surface-level SEO and generic descriptions are no longer enough. Your online presence must be specific, consistent, and rich with meaningful signals.

Today’s platforms:

  • Scan 30, 50, even 100 sources at once
  • Pull patterns, phrasing, and consensus from across the web
  • Deliver a single answer, often without showing the user where that answer came from

Instead of a potential patient clicking on your website or blog, the AI is summarizing what it already knows about your practice—based on everything else it can find.

Visibility is an ecosystem, not a checklist

Many practices still approach visibility as a list of tasks:

But in today’s search landscape, visibility depends on how those pieces connect.

When your Google profile is active, your reviews are recent and detailed, and your content reflects your expertise, it creates a trust signal that platforms recognize.

This kind of visibility is not a one-time marketing effort. It is a living system that supports long-term discoverability.

What this means for your practice

Every practice can improve visibility using tools it already has access to. Patient reviews are one of the most powerful and underutilized visibility signals. Reviews that mention the doctor’s name, the condition treated, and the city are especially effective. For example:

“Dr. Morris in Whitby helped me manage my dry eye, and now I can get through the workday without discomfort.”

This kind of review is not just about reputation. It gives search engines and AI platforms the information they need to understand your relevance and local connection.

Practices that start investing in this type of clarity and specificity now will be in a stronger position as AI-driven discovery continues to evolve.

Being seen no longer depends on just having a website or a few good keywords. Visibility today is about shaping the signals that patients and platforms rely on to make decisions.

Louise Courville

Louise Courville is a visibility strategist and founder of EYE Reputation, an agency built to help eye care practices increase visibility across Google, social, and AI platforms.

She brings decades of experience in the optical industry and over eight years in digital marketing. Louise writes about how search, AI, and trust signals are reshaping the way patients find eye care online.

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The Potential of Artificial Intelligence in Optometry

Practice, Technology, The Patient Journey

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Artificial intelligence is a branch of computer science that uses various techniques that aim to mirror human intelligence. One AI technique is machine learning, which relies on vast data sets to learn and predict results without human intervention.

Artificial intelligence has slowly made its way to optometry as well. It is unlikely that AI will ever replace an optometrist but it does have the potential to ease many aspects of their jobs.

This doesn’t mean that robots will be running around in our healthcare facilities; rather, AI focuses on a large amount of patient data to give insight into diagnosis and treatment methods.

Let’s look at how it has the potential to change an optometrist’s practice.

Streamline Management
Software is coming to the market that provides autonomous management of tasks related to patients. Repetitive tasks like scheduling, billing, and follow-ups can be done on the fly and updated in patient records as new information is received.

This improves organizational productivity for many optometry practices, making them more efficient leaving more time to focus on patient care.

Early Detection
One of AI’s advantages is that it can process vast amounts of data more quickly as a computer is doing most of the legwork.

This especially comes in handy when processing optical coherence tomography (OCT) images, retinal images and dry eye. It can look for patterns within these images that optometrists might miss because of the subjective nature by which these images are analyzed.

Diabetic Retinopathy
Machine learning can monitor these images over time and see if any changes are occurring that lead to eye diseases that manifest progressively.

FDA-approved AI systems are already appearing on the market that analyze fundus photography to detect elements of diabetic retinopathy such as hemorrhages, aneurysms, and other lesions.

It can detect these changes early on, leading optometrists to formulate a health plan with the patient. Additionally, this system requires minimal training and can outperform humans.

Glaucoma
Technology to detect other ocular diseases such as glaucoma by fundus photographs, optical coherence tomography (OCT), and visual fields is currently in its early stages.

AI is beneficial for open-angle glaucoma cases where symptoms don’t typically exhibit themselves. Since glaucoma can’t be cured, early detection may help manage the disease to prevent it from getting worse to the point of severe vision loss or blindness.

Dry Eye
There is also new AI technology emerging  in the dry eye arena.

When it comes to talking to patients about their dry eye disease, a picture is worth a thousand words. Conversations become easier when you can show a patient an image of their ocular surface. Suddenly it all clicks (pun intended).

AOS is one company that takes it a step further with innovative technology. The platform automatically grades an image for Bulbar Redness, Injection and Lid Redness. In Staining mode the software counts punctate of a fluorescein image. It can also convert a fluorescein image into 2D and 3D which brings a real wow factor.

The images show patients proof of their condition and the analysis provides context. It’s much like the difference between stating a fact and telling a story.

We can now give meaning to symptoms felt and seen in the eye. And it’s especially useful for assessing progress during follow up appointments. Lower redness numbers or lower punctate counts tell me and the patient we are on the right track.

AOS analysis improves patient education which helps boost compliance. Better compliance leads to better outcomes and that leads to happy, loyal patients.

Reduce False Positives
False positives occur when a test result shows that a disease is present when it is not in reality. Here AI can help as well.

By looking at vast amounts of medical data regarding symptoms that a patient presents, AI can predict the likelihood of a disease or condition being present.

As a result, patients can save time by avoiding unnecessary consultations with their optometrist or an ophthalmologist and save money on unnecessary medications.

In Optometry and Beyond
Artificial intelligence is showing its potential in many medical fields other than optometry, including oncology, dermatology, pharmacology, and genetics.

Though still in its infancy, improvements in this technology will help doctors verify their diagnoses and interpret data faster independently.

This does not mean that a doctor’s work will become redundant, as AI algorithms are not yet 100% accurate. There will cases when a doctor’s insight will be invaluable in diagnosing diseases.

Consider AI a tool to benefit the health care provider and the patient.

MARIA SAMPALIS

is the founder of Corporate Optometry, a peer-to-peer web resource for ODs interested to learn more about opportunities in corporate optometry. Canadian ODs and optometry students can visit www.corporateoptometry.com to learn more.

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How Will Artificial Intelligence Change Your Practice?

Differentiation | Business Strategy, Practice, Technology

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Artificial intelligence has a long way to go to become a fixture in healthcare, but there already are hints of what’s to come.

Harvard Business Review has summarized recent findings. “Consider three issues that get a lot of attention: the use of medical records, the “human touch” in medical care, and the future of jobs in the industry. On balance, are people more glass half-full or half-empty? Our research points to an optimism that may surprise expert observers,” H. James Wilson and Paul Daugherty write in HBR.

The Use Of Medical Information
Patients want their healthcare data protected – and we are required by HIPAA law to do that – but patients will voluntarily share their medical data when it’s in their best interest to do so. Consider the data produced by wearable devices as more people are utilizing wearable healthcare devices.

A recent Accenture survey gave these results showing people are willing to share their medical data with healthcare providers or even health insurers.

• Eighty-eight percent of people are willing to share data from their wearables with either their doctor, nurse, or other health care professional.

• Seventy-two percent are willing to share their data with health insurers.

• Only 38 percent are willing to share their data with employers.

It’s estimated that more than 75 million Americans would use an activity tracker by the year 2021. As we see an increase in wearable devices capable of transmitting medical data we need to consider how we can utilize this information in our patient management protocols. This is important because even though the use of wearables has more than doubled in the U.S. in the last two years, it’s estimated that only 15 percent of doctors say they’ve discussed wearables or health applications with patients.

Wearables give the ability to continuously capture data such as heart rate, sleep patterns and glucose levels. This produces vast amounts of data. Contrast this with a single reading taken on a single doctor visit. Comparing the data taken from wearables with readings taken at a doctor’s visit raises the issue of the accuracy of the data. Wearables do not yet have the accuracy of the gold standard measurements taken in the doctors’ office. This will improve over time. AI gives us the tools to sort through the mountain of data and extract pertinent trends.

The “Human Touch” vs AI In Medical Care
Anyone who’s been frustrated by an automated phone tree when calling a tech company for support, knows how much we desire to talk to a human, but research done by Wilson and Daugherty showed that convenience and efficiency often trumps “Human Touch” care. Their survey revealed:

• Seventy-five percent of people said that AI technological advances (including mobile apps, wearable monitoring devices and smart scales) were important to help them manage their health.

• Sixty-six percent of people said they would use AI-based after-hours services.

• Sixty-three percent of people said they would use AI agents to help them navigate the health-care system.

• Fifty percent-plus said they would use AI-based systems to diagnose their symptoms and to receive emergency advice.

Clearly, patients feel there is a place for the use of artificial intelligence when it provides convenience and efficiency.

The Future Of Jobs In The Industry
There are at least three ways that AI will impact our practices.

1) AI has the ability to analyze copious amounts of data. Consider these two uses of AI.

a. The ability of AI to read the patient record in real time and suggest differential diagnoses, as well as suggest additional tests to administer.

b. The ability of AI to analyze the new drug you want to prescribe and evaluate it for incompatibility against all other pharmaceutical agents the patient is taking, all nutraceuticals the patient is consuming, and all supplements the patient is using, plus considering the patient’s history of allergies.

2) AI has the ability to interact with people through novel types of interfaces such as voice, emotion, or gesture recognition. AI can be used to remind patients to take medication. Chatbots can used to triage patients calling into the office. Machine learning tools can used in the diagnosis and treatment of visual problems such as amblyopia, convergence insufficiency and low vision.

3) AI is able to extend people’s capabilities beyond their natural limits. Robot-assisted surgery is a good example of this in the eyecare world. AI can eliminate involuntary tremors while a surgeon utilizing robot-assisted surgery is operating on the retina.

Click HERE to watch a short video that shows the potential power of AI for conditions like autism, Parkinson’s and epilepsy.

AI is already here. The power of human-machine collaborations is amazing. AI is causing us to re-imagine our work processes. We are excited to see what the near future holds for AI and its use in health care.

 

MARK WRIGHT, OD, FCOVD

Dr. Wright is the founding partner of a nine-partner, three-location full-scope optometric practice. As CEO of Pathways to Success, an internet-based practice management firm, he works with practices of all sizes. He is faculty coordinator for Ohio State’s leading practice management program.

CAROLE BURNS, OD, FCOVD

Dr. Burns is the senior partner of a nine-doctor full-scope optometric practice that she built with her husband, Dr. Wright. She is also the COO of a state-wide nursing care optometry practice. Dr. Burns lectures nationally on practice management and staffing issues. Dr. Burns authored the Specialty Practice section of the textbook, Business Aspects of Optometry.

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