Healthcare providers
How does AI describe your clinic?
Patients now ask AI which doctor to see and who takes their insurance. AI answers cite PubMed and Healthline, not your website. We show how three engines describe your clinic, with a compliance-safe fix list: get recommended, and get described correctly.
Patients moved, and the answers cite someone else
When a patient asks an AI engine which doctor to see, the answer is assembled from sources the engine trusts: authoritative health publishers and academic sources of the PubMed, Mayo Clinic, and Healthline type. Individual clinic websites are rarely cited in health answers.
The answers also filter. Questions arrive with constraints attached: accepts Blue Cross, taking new patients, near me. If your specialty, insurance networks, and availability are not stated consistently across the profiles engines read, the filters pass you by regardless of how good your site looks.
Both halves matter in healthcare. Being absent loses the patient to the clinics the engine does name. Being described wrongly (wrong specialty, wrong networks) is worse in a YMYL context: it sends the wrong patients or none at all.
Source for the patient-behavior figures: rater8 2026 Patient Choice Report (vendor study; rater8 sells healthcare reputation management).
Patients who used AI in their last provider search
up from 31% nine months earlier
AI as first touchpoint
ahead of Google at 34%
Switched providers after an AI search
the decision is already AI-shaped
Abandoned a provider over thin online info
visibility and accuracy decide
All figures: rater8 2026 Patient Choice Report, surveying more than 1,000 patients. Vendor study, labeled as such.
What the research shows
Every figure on this page comes from one source: rater8's 2026 Patient Choice Report, a survey of more than 1,000 patients. It is vendor-published (rater8 sells healthcare reputation management), labeled as such, and used directionally.
47%
of patients used AI in their last search for a provider, up from 31% nine months earlier. A 16-point move in under a year.
36% vs 34%
AI now leads Google as the first touchpoint in provider choice, 36% to 34%. The front door to your practice is changing.
39%
of patients who switched providers did so after an AI search. What the answer says about you is already part of patient flow.
55%
of patients abandoned a provider because online information was insufficient. Thin, inconsistent profiles cost you patients who were already looking.
Scope note (YMYL): health is a "your money or your life" category. This page stays inside a fixed scope: how AI engines describe your clinic, and whether structural signals are consistent. No medical content is written on your behalf, and nothing here promises patient outcomes or volume. Fix recommendations are structural: structured data, third-party profile consistency.
What patients ask AI
Example questions, illustrative"Best orthopedic clinic near me that accepts Blue Cross"
"Who should I see for chronic knee pain, a podiatrist or an orthopedist?"
"Is [clinic name] a good provider for LASIK?"
"Urgent care or ER for a sprained ankle?"
"Which cardiologists in [city] are taking new patients?"
Constructed examples based on common patient questions, not captured from real sessions. The Written Diagnosis replaces them with the questions your actual patients ask.
How the answer looks when it gets you wrong
"[Competitor clinic] accepts most major insurance plans and is taking new patients. I don't have reliable information about whether [your clinic] accepts Blue Cross, so you may want to call ahead."
Pattern we see repeatedly: clinics aren't criticized, they're hedged out of the answer. When the facts an engine needs (networks, availability, specialty) are missing or inconsistent across profiles, uncertainty reads as exclusion.
Six checks you can run today
No tools needed beyond the engines themselves. Write down what you see each time; the pattern across answers is the finding.
Open a fresh ChatGPT session and ask: "Is [clinic name] a good provider for [service]?" Note exactly how the engine describes your specialty and location, and what it hedges on.
Ask a filtered question a patient would: "[specialty] near me that accepts [insurer]". Note whether you appear, and which competitors the answer names instead.
Compare the engine's description against your facts: specialty, insurance networks, locations, hours. Every mismatch is a patient-steering error, not a cosmetic one.
Check your profiles say the same thing everywhere: Google Business Profile, Healthgrades, WebMD Connect, your site, directory listings. Engines reconcile across sources; contradictions read as uncertainty.
Ask "which [specialty] practices publish good patient education on [condition]". Publisher and academic sources dominate health answers; knowing what they cite shows you the citation bar.
Repeat the same question a week later. Single runs mislead; the pattern across engines and time is the real signal.
From free check to written diagnosis
The free check runs against your homepage and reports seven technical aspects that decide whether AI engines can read your site at all. It is not healthcare-specific, and it says so on the result.
The Written Diagnosis ($490) answers the provider question for your specialty and area: 30 patient-style questions across ChatGPT, Perplexity, and Gemini, run twice over two days, written up as a report of how each engine describes your clinic, where you're missing, and which facts they get wrong. The Fix Sprint ($1,250) executes the structural fixes: structured data, profile consistency, third-party signals. Monthly monitoring tracks how the descriptions evolve. No medical content is written on your behalf.
Keep reading
Questions providers ask
Do patients really use AI to choose providers?
rater8's 2026 Patient Choice Report surveyed more than 1,000 patients: 47% used AI in their last search for a provider, up from 31% nine months earlier. AI has become a first touchpoint in provider choice, and the shift is fast.
Why doesn't AI mention my clinic when our website is good?
AI answers for health questions draw heavily on authoritative publishers and academic sources (PubMed, Mayo Clinic, Healthline types). Individual clinic websites are rarely cited, so a good website alone does not enter the answer. The engines also apply filters (insurance accepted, taking new patients), and a clinic whose profiles don't state those facts gets filtered out regardless of quality.
What does compliance-safe mean here?
Health is a YMYL (your money or your life) category, so the scope stays fixed: we diagnose how AI engines describe your clinic and whether structural signals are consistent. We do not write medical content for you, and we make no promises about patient volume. Recommendations are structural: structured data, profile consistency across third-party sources.
AI described our services wrongly. Is that fixable?
Wrong descriptions (wrong specialty, wrong insurance networks, out-of-date locations) usually trace to inconsistent or missing facts across the sources engines read, not to the engines themselves. The written diagnosis maps what each engine says against your actual facts, and the fix list targets the inconsistencies. In YMYL contexts a wrong description sends patients elsewhere, so accuracy is treated as seriously as visibility.
What does the free check cover?
The free check examines seven technical aspects of your homepage instantly and shows the result of each. It is not healthcare-specific: it tells you whether AI engines can read your site at all, a precondition for being cited or described correctly. No signup required.
See how the engines describe your clinic
The free check runs instantly against your homepage. No signup, no cost.
Run the free check