The Questions Patients Ask AI Before They Ask a Clinic

Patients asking AI health questions are now the norm, not the edge case. About 1 in 10 Australian adults asked ChatGPT a health question in the six months to June 2024, and OpenAI says more than 300 million people a week now ask it about health. The questions are practical: what a symptom means, whether to see someone, and what it will cost. I read 59 Australian clinic websites to see whether they answer five of those questions. 1 site answered all five. 10 answered none.

How many patients ask AI before they ask a clinic?

The Australian number comes from the Medical Journal of Australia. In a nationally representative survey of 2,034 adults, Ayre, Cvejic and McCaffery found that 9.9% had used ChatGPT for health information in the six months before June 2024. They put that at about 1.9 million people.

That was two years ago, and it was one tool. The same paper found that 38.8% of people who knew about ChatGPT but had not used it for health were considering doing so within six months.

The global number is bigger. In January 2026, OpenAI said 230 million people asked ChatGPT health and wellness questions each week. By July 2026 it said more than 300 million. Those are OpenAI's own figures, from its own analysis of conversations, so read them as a claim rather than an audit.

In the United States, a KFF poll of 1,343 adults in early 2026 found 32% had turned to an AI chatbot for health information in the past year. That is the same share who use social media for health. Deloitte's 2024 survey of more than 2,000 US adults put use of generative AI for health reasons at 37%, and found the main reason for not using it was distrust of the information (30%).

So the patient who walks into your clinic has often already had a conversation about their problem. The question for you is what they asked, and whether your website was any use to the answer.

What do patients actually ask an AI about their health?

The MJA paper asked its 187 ChatGPT users what they used it for. Here is the list, in their order.

Source. Ayre, Cvejic and McCaffery, Medical Journal of Australia, 2025, Box 2. Multiple answers were allowed. The authors class the symptom, what-to-do, see-a-doctor and results questions as higher risk, and 61% of users had asked at least one of them.

The KFF poll asked a different question: why AI, rather than a person? Two thirds (65%) said quick or immediate information. But 41% said they wanted to look things up before deciding whether to see a provider. About 1 in 5 said they could not afford to see a health professional (19%), or had no regular doctor or could not get an appointment (18%).

OpenAI's own July 2026 post lists the common uses in a single line: "understanding a lab result and preparing for an appointment to making sense of what a doctor said and building a healthier routine."

Put those together and a pattern shows. Patients ask AI two kinds of question. The first kind is clinical: what does this mean, is it serious. The second kind is logistical: do I need to see someone, who, what will it cost, how soon. The second kind is the one a clinic website can answer.

Which of those questions can a clinic page answer?

Not the clinical ones. A service page that tells a reader what their symptom means, or whether they should book, is giving individual advice to someone it has never assessed. Section 133 of the National Law bans advertising that creates an unreasonable expectation of beneficial treatment. That is a bad place to start.

The logistical questions are different. They are about your clinic, they are factual, and you already know the answers. I picked five, each one drawn from the surveys above.

1. How much will it cost? Cost was a major reason for using AI for 19% of KFF respondents.
2. Do I need a referral? The MJA's "should I see a doctor" question, in its Australian form.
3. What happens at the first visit? OpenAI's "preparing for an appointment".
4. How soon can I be seen? Access was a major reason for 18% of KFF respondents.
5. Is it covered? Medicare, a rebate, bulk billing, a health fund, DVA, NDIS or WorkCover.

An AI engine can only repeat what your site says. If your fees page says "call us for pricing", the engine has nothing to quote, and it will quote a competitor who published a number. So I went and looked at who publishes what.

What did I find on 59 Australian clinic websites?

I searched for a clinic type plus a city, across Sydney, Melbourne, Brisbane, Perth, Adelaide, Canberra, Hobart and the Gold Coast. The types were physio, dentist, GP or medical centre, psychologist and cosmetic clinic. No question words went into any search, so the sample is not tilted toward clinics that already answer them. From each site I read the page the search led to, plus up to five linked pages about fees, FAQs, new patients, referrals, Medicare or booking.

That gave 59 clinic sites, 275 pages and 151,560 words. Here is how many sites answered each question, after a hand read of every hit.

Nearly every site says something about Medicare or health funds. Only about a quarter say what happens at the first visit, or how soon a new patient can be seen.

The site-level picture is starker.

• 1 site answered all five questions. It was a GP clinic.
• 8 sites answered four.
• 33 sites, more than half, answered two or fewer.
• 10 sites answered none of them on any page I read.

The average site answered 2.14 of the five. A patient who asked an AI the practical questions before calling would, on most of these sites, still have to call.

Which kind of clinic answers the most, and which the least?

The five clinic types behave very differently, and the differences say something about each one's business.

Psychology sites answer the most. That is Medicare's doing. The Better Access rebate needs a GP referral and a Mental Health Treatment Plan, so every psychology site has to explain referrals and rebates, and most give the session fee beside them. 9 of 11 answered the referral question.

Dental sites answer cost. 6 of 11 publish a new-patient check-up price, usually as an offer. Not one of the 11 says whether a referral is needed, because in general dentistry it almost never is. The site knows that. The patient asking a chatbot does not.

GP clinics publish fee tables (13 of 16) but say almost nothing about the first visit (2 of 16) or referrals (1 of 16). The one site that answered all five was a GP clinic, so it can be done.

Cosmetic clinics answer almost nothing. 6 of the 10 answered no question at all, and none said how soon a patient could be seen. The pages I read were about treatments and the people who perform them. That is a choice, and it hands every practical question to whoever the patient asks next.

Why does a table cell not count as an answer?

A confession about the method, because it turned into a finding.

My first scanner split each page into sentences and dropped anything under 25 characters. It reported 13 sites that described the first visit and 35 with cost wording. When I read the raw pages, seven GP clinics and two physios had full fee tables the scanner had missed. The prices sat in table cells, with no sentence around them. "Standard Consultation (Level B)" in one cell, "$96.20" in the next.

I fixed the scanner and re-ran it. You cannot fix a chatbot. A price in a bare cell is an answer to a person looking at the page. It is a weaker answer to any system that reads text, because nothing says what the number is a price for. The clinics that were easy to count were the ones that wrote a sentence: "A standard consultation is 50 minutes and costs $265."

The same goes for headings. "Referrals" as a heading with a form under it is not an answer to "do I need a referral". Fourteen sites had a short referral heading of some kind. Five of them put nothing under it that said yes or no, so they were not counted.

I have written before about what Google's AI tells patients before they click and which AI engines actually name Australian clinics. The lesson from both was that engines quote sentences. This measurement is the demand side of the same story. The questions are known. The sentence that answers each one is short. Most sites have not written it.

How do you answer the five questions without breaching the rules?

Answering a practical question is low risk under the AHPRA guidelines. The risk arrives when the answer is an absolute. Here are the patterns from the sample, with a line you could publish instead. Where a "use this" line is quoted, it is from a site in the sample, unnamed.

Every "use this" line stays factual. None promises a result. None uses a patient's words about their care, which the testimonial rule would catch. Rebate claims were the one place the sample did well. Every "rebates available" or "no gap" headline I found had an eligibility qualifier somewhere on the same site. The wait-time claims did not.

If the pages that should hold these answers do not exist yet, the About page and the fees page are the two most patients read before they book, and I have covered both.

How did I measure this, and what can it not tell you?

The method is short enough to repeat.

I fetched the pages on 20 and 21 September 2026. Fifteen of the 74 clinic sites I found would not load, which left 59. Menus, footers and scripts were stripped, and a sentence repeated across pages was counted once per site. That left 10,862 sentences and 151,560 words.

A scanner flagged sentences against five fixed patterns. It found cost wording on 35 sites, referral wording on 24, first-visit wording on 13, wait wording on 32 and coverage wording on 46. A second pass caught short lines and table cells the first had dropped.

Then I read every hit and applied the same rule to each site. A Medicare rebate amount is not a fee. A cancellation fee is not a fee. A sentence about the GP writing a referral does not say whether the patient needs one. A results-within-48-hours line is not a waiting time. That read gave the published numbers: 32, 19, 15, 15 and 45.

Method. 59 Australian clinic websites, 275 pages, fetched 20 and 21 September 2026 from neutral city searches in five clinic types. Survey figures are from the Medical Journal of Australia (2025), KFF (March 2026), OpenAI (January and July 2026) and Deloitte (2024). The scripts, the site list and every verdict are saved with the post.

Now the limits.

• Up to six pages a site. A fees page I did not open is not in the count. The true figures are likely higher.
• A scanner cannot read prices inside images, PDFs or booking widgets.
• The five questions are my choice, drawn from the surveys. A different five would give different numbers.
• The KFF and Deloitte figures are American. The MJA figure is Australian but from mid-2024.
• This is general information about advertising rules. It is not legal advice about your practice.

What should you check on your own site this week?

Open your own site and try to answer the five questions as a stranger.

1. Cost. Find the standard fee in dollars, written in a sentence. If it only exists in a table, add the sentence.
2. Referral. Find the word "referral". If the sentence around it does not say whether the patient needs one, write that sentence.
3. First visit. Find "first appointment" or "initial consultation". It should be followed by how long, and what happens.
4. Wait. Find "same day". If it is there, check it is qualified and true. If it is not there, say how new patients usually get seen.
5. Covered. Find "Medicare". Check the eligibility is beside it.

Five sentences. More than half of the sites in this sample are missing at least three of them.

If you want the whole site read this way, with every flagged line quoted and the replacement written, that is what the All Clear Audit does. If you would rather start with the page patients read first, website copy is where I begin. For the rulebook behind the rewrite table, start with the AHPRA advertising guidelines explained.

Prefer the short version? The findings are in an eight-slide web story.

Related reading:

• What patients Google before booking a clinic
• What Google's AI tells patients before they click
• Which AI engines name Australian clinics
• What patients read on a clinic's About page
• How to rank in AI search
• SEO and AI search for clinics
• View all services →