Each AI engine builds a telehealth recommendation from a different mix of sources. Temso's July to September 2026 study of online healthcare provider prompts found the top-20 cited domains of any two engines overlap by only 13 percent on average, so a brand named by ChatGPT can be absent from Gemini on the same patient question.
AEO, GEO, AI visibility, and AI SEO are four names for the same work: getting a telehealth brand named and cited inside AI answers. This post uses AEO. The ClinicAds post on Google rank versus ChatGPT cited the same Temso study for a different finding, and the med spa version of this post covers local treatment prompts. This one covers national condition and brand-comparison prompts, where the sources are review sites, clinician pages, and health authorities rather than directories.
- The engines do not share one source list: Temso's July to September 2026 study of 15,769 online healthcare provider responses found an average top-20 domain overlap of just 13 percent between engine pairs, and 0 percent between Gemini and Microsoft Copilot.
- Temso found 72 percent of Gemini's cited sources were commercial sites against 46 percent for ChatGPT, while 20 percent of ChatGPT's were institutional, so a brand's own pages weigh differently by engine.
- On generic US health questions, LLM Pulse's October 2026 rankings show nih.gov first in Perplexity (19.75 percent of answers) but second to google.com in Gemini (6.0 percent against 10.97 percent), and youtube.com first in Google AI Overviews (36.56 percent).
- No independent study found for this post measures which engine cites a specific named telehealth brand most, so a brand should log its own sources per engine before choosing a first fix.
Do ChatGPT, Perplexity, Gemini, and Google AI Overviews cite the same sources for telehealth?
No. The engines cite largely different domains for the same kind of patient question. Temso measured the overlap between each pair of five engines on online healthcare provider prompts and found it averaged 13 percent, ranging from 43 percent between Google AI Mode and Google AI Overviews to 0 percent between Gemini and Microsoft Copilot.
The practical consequence for a telehealth brand is that one source audit is not enough. A brand with strong clinician pages and thin third-party reviews can be cited in one engine and invisible in another. The table below separates what each public dataset measured, because the two datasets here use different prompts and different windows.
| Engine | What the data shows | Dataset | First fix for a telehealth brand |
|---|---|---|---|
| ChatGPT | 46 percent commercial and 20 percent institutional sources on telehealth provider prompts | Temso, Jul to Sep 2026, 12 countries | Make clinician, safety, and licensure facts quotable on owned pages and on the third-party pages ChatGPT reads |
| Gemini | 72 percent commercial sources on telehealth provider prompts; google.com first on US health questions at 10.97 percent | Temso (same study); LLM Pulse, 7-day window to Oct 18, 2026 | One page per condition and treatment with price, prescriber, and state coverage stated in plain sentences |
| Perplexity | nih.gov first on US health questions at 19.75 percent, then linkedin.com at 8.76 percent and reddit.com at 7.49 percent; not covered by Temso | LLM Pulse, same window | Log the numbered sources under each answer; publish clinician profiles that LinkedIn and health authorities can corroborate |
| Google AI Overviews | youtube.com first on US health questions at 36.56 percent, then nih.gov at 17.13 percent | LLM Pulse, same window | Video explainers from named clinicians on the condition and treatment pages |
What does the data say about ChatGPT and telehealth recommendations?
ChatGPT splits its telehealth sources between commercial and institutional sites. Temso found 46 percent of ChatGPT's cited sources were commercial and 20 percent institutional, the highest institutional share among the engines where the study reported one, and Reddit appeared among its top five domains.
For a telehealth brand, institutional weight means the claims ChatGPT repeats about a prescription program tend to trace to health authorities, regulators, and clinical references. A brand that states its prescriber credentials, pharmacy partner, and safety information in plain sentences, and cites the clinical source behind each treatment claim, gives that pipeline something it can corroborate.
- State the prescriber type, the licensure states, and the pharmacy source on every condition page
- Link each treatment claim to the clinical or regulatory source behind it
- Check what Reddit threads say about the brand, since ChatGPT draws on them as well
Which sources does Gemini use when it recommends a telehealth brand?
Gemini leans on commercial sites. Temso found 72 percent of Gemini's cited sources on online healthcare provider prompts were commercial, against 46 percent for ChatGPT. That points to provider pages, comparison publishers, and platform listings as the sources Gemini reads most.
That makes the brand's own condition pages the highest-value owned asset for Gemini, provided each one states the treatment, the price or range, the prescriber, and the states served. A page that says get started to see pricing gives Gemini nothing to quote, and the answer gets built from a competitor's page or a comparison site instead.
What about Perplexity and Google AI Overviews?
The public data here comes from a different source and a different question type. LLM Pulse tracked non-branded US health questions, not provider shortlists, over a 7-day window ending October 18, 2026. In that window nih.gov led Perplexity at 19.75 percent of answers, with linkedin.com at 8.76 percent and reddit.com at 7.49 percent, while youtube.com led Google AI Overviews at 36.56 percent.
LLM Pulse is an AI-visibility vendor, its windows roll daily, and these are informational health questions, so the figures show direction rather than a telehealth benchmark. Temso did not include Perplexity. Neither dataset says which engine names a specific brand most often, so ClinicAds treats the figures as a map of where to look in a brand's own logs.
How should a telehealth brand audit sources engine by engine?
A telehealth brand should log sources per engine for the same set of patient prompts, because a combined list hides which engine each fix helps. Twenty-five prompts across the top three conditions is enough for a first read, repeated monthly because answers change between runs.
- 1. Write 25 prompts: condition research, price and insurance questions, brand comparisons, and safety or legitimacy checks
- 2. Run each in ChatGPT, Perplexity, Gemini, and Google AI Overviews, logged out, with the date recorded
- 3. Record whether the brand is named and every domain each engine cites
- 4. Mark each domain as owned, review or comparison site, clinical authority, social, or competitor
- 5. Fix the most repeated surface per engine first, then rerun the same 25 prompts 30 days later
What is the cost case for fixing the sources an engine uses?
The cost case rests on customer acquisition cost and payback. ClinicAds plans telehealth paid media at $90 to $250 per paying patient against lifetime value of $600 to $2,000, with payback under three months and a 3:1 or better LTV to CAC ratio on spend of $10,000 to $50,000 a month. A source fix that adds a handful of paying patients a month without added ad spend lowers blended CAC. These are agency averages, not guarantees.
The same fix rarely pays in every engine. Because the evidence points to different leading surfaces by engine, a brand should spend its first AEO hours on the surface its own log shows repeating, and move budget back to paid only if the blended CAC from organic sources stays above its paid range.
Does a telehealth brand need a different strategy for each AI engine?
Not a different strategy, but a different first fix. Condition pages with stated prescribers and pricing, clinician profiles, and consistent third-party listings feed all four engines. The engine split only decides which to do first, and the brand's own per-engine source log shows which.
Is there independent data on which sources AI engines cite for telehealth specifically?
Partly. Temso's 2026 study of 15,769 online healthcare provider responses covers ChatGPT, Gemini, Google AI Overview, Google AI Mode, and Microsoft Copilot across 12 countries, not only the US, and it excludes Perplexity. Temso sells AI-visibility tracking, so a brand should confirm the pattern in its own prompt log.
Which engine should a telehealth brand check first?
ChatGPT and Google AI Overviews, because they reach the most patients, then Gemini and Perplexity. Whichever engine already names competitors for the brand's lead condition is the one to log first.
Does Reddit matter for telehealth recommendations?
Sometimes. Temso listed Reddit among ChatGPT's top five cited domains for telehealth provider prompts, and LLM Pulse measured reddit.com at 7.49 percent of Perplexity's US health answers. Neither study separates brand-comparison threads from general discussion, so a brand should read what its own threads say before replying to any of them.