US Healthcare AI Overview Citation Study 2026 — Who Google Cites, and Why
50 healthcare queries. Eight clinical clusters. Five metros. What we found about which entities Google surfaces in AI Overview answers, which content patterns win the citation, and how HIPAA-aware providers should structure content in 2026.
The five things AI Overview is doing to US healthcare search in 2026
- AI Overview surfaced on 43 of 50 US healthcare queries in the sample — a 86 percent presence rate. The seven queries without an AI Overview were almost all pure navigational or transactional phrasing where a knowledge panel or a local pack sufficed.
- Provider websites earned 27 out of 168 total citation slots (16.1 percent). Federal agencies (HHS, CDC, NIH, FDA) took 47 slots (28.0 percent). Medical societies and specialty colleges took 39 slots (23.2 percent). Peer-reviewed journals and educational institutions took the remaining 55 slots.
- Provider citations concentrated in the second and third citation positions, not the first. Of the 27 provider citations, only 5 held the primary slot; the remaining 22 sat in slot 2 (14) or slot 3 (8). The first slot is a fight the provider website will usually lose to a federal agency or a medical society.
- Four content features correlated with provider citation: page length above 1500 words, FAQ block with structured markup, byline with named provider credentials, and outbound citations to primary sources. Pages carrying all four earned an AI Overview citation on tracked queries at 3.2x the rate of pages missing more than one feature.
- HIPAA compliance did not depress AIO surfacing. Every provider page cited was HIPAA-clean by construction — no patient identifiers, no case-specific claims, no unconsented testimonials. The AI Overview appears to reward clinical depth and structured Q&A regardless of whether the page carries a single testimonial.
Cite this report
Inline HTML:
Ichelon Consulting US. (2026). US Healthcare AI Overview Citation Study 2026. Retrieved from https://ichelonconsulting.com/reports/us-healthcare-aio-citation-study-2026
APA 7:
Reddy, S. (2026, September). US Healthcare AI Overview Citation Study 2026: Who Google Cites and Why. Ichelon Consulting US. https://ichelonconsulting.com/reports/us-healthcare-aio-citation-study-2026
Licensed under Creative Commons Attribution 4.0 (CC BY 4.0). Reproduce, share, adapt freely with attribution.
Executive summary
The AI Overview — the generative summary Google places above the ten blue links on high-intent informational queries — has been rolling across US healthcare search since mid-2024. By the third quarter of 2026 it appears on a comfortable majority of clinical questions and it is meaningfully changing how a US healthcare buyer arrives at a provider brand. This report is our attempt to answer, with first-party observed data, three questions the operators we work with keep asking us at the Dallas office: which sources does the AI Overview actually cite in US healthcare, what content patterns win those citations, and how much of a HIPAA-aware provider's content can realistically compete for the citation slot.
We watched 50 healthcare queries across five metros and eight clinical clusters between February and August 2026. We recorded whether the AI Overview appeared, which sources it cited, in what order, and — where a provider website earned a slot — what structural features that page carried. The sample is not a representative census of the entire US healthcare search surface; it is a longitudinal probe deep enough to reveal the pattern language of how the AI Overview picks citations. Our conclusion, at a high level, is that the AI Overview is a citation engine that favors comprehensiveness, primary sources, and structured question-answer content. Providers who ship those three signals consistently will earn citation slots. Providers who lean on thin sales pages will not.
The rest of this report walks through methodology, cluster-level findings, entity-type breakdowns, content-pattern correlations, and a 12-week playbook that a US practice can run against its own pages to compete for AI Overview citation. It also spends time on the HIPAA question, because every US operator we talk to raises it, and the answer is not what most of them expect.
Methodology — how the 50 queries were selected and observed
We selected 50 queries across eight clinical clusters — dental (6 queries), medical dermatology (6), aesthetic dermatology and med-spa (6), plastic surgery (6), IVF and fertility (6), primary care and DPC (7), orthopedic surgery (7), and psychiatry and mental health (6). Each cluster carried a mix of high-commercial intent (best pediatric dentist near me, cost of laser hair removal, breast augmentation recovery), symptom-led informational intent (why does my knee crack going down stairs, how do you know if you need IVF), and category-comparison intent (concierge medicine versus direct primary care, in-office versus takehome whitening).
We deliberately excluded branded provider queries (best XYZ practice) — the goal was to observe how the AI Overview builds its answer when the searcher has not yet committed to a provider entity. We also excluded pure transactional queries (schedule appointment, book online) because those trigger a local pack rather than an AI Overview in the majority of cases.
Queries were run from five representative US metros — Dallas-Fort Worth (Ichelon Consulting US's home HQ), Los Angeles, New York, Chicago and Boston. Each query was observed at least three times across the observation window to smooth out day-of-week and mid-day volatility. Where the AI Overview appeared, we recorded up to eight citation slots per query — the source name, the source type (federal agency, medical society, peer-reviewed journal, provider website, media outlet, educational institution), the citation order, and — for provider websites — the observable structural features of the linked page.
Structural features observed on cited pages: total word count, presence of an FAQ block, presence of structured FAQ markup (FAQPage schema), presence of a named-provider byline with credentials, presence of a table or comparison element, presence of outbound links to primary sources (HHS, CDC, NIH, FDA, or a specialty college), presence of a HIPAA notice, and presence of a first-party outcome disclosure. A page was scored on each feature independently and the aggregate feature count was correlated with citation frequency.
What this study is not. It is not a citation census of the entire US healthcare AI Overview surface. It is a 50-query longitudinal probe. It does not measure AI Overview traffic — no click data is reported, because AI Overview click attribution is not reliably available in the third-party tooling we have access to. It does not attempt to predict which specific practice will win a citation on a specific query; it identifies pattern-language features that raise citation probability. Individual results will vary. The point of this study is to give operators a defensible content specification, not a click forecast.
What the underlying dataset row looks like. Each observation in the rolled-up dataset carries: query string (normalised to lower-case, US-English), cluster label (one of the eight), metro (DFW / LA / NYC / Chicago / Boston), observation timestamp, AIO-shown boolean, citation slot count, and for each cited slot an entity-type tag plus source-domain hash. For provider-cited slots the row also carries the eight structural-feature booleans we scored on the linked page. A representative row 1 records a "cost of dental implants" query in DFW, AIO shown, four citations, with slot 1 the American Dental Association consumer surface, slot 2 an independent DFW practice site scoring six of eight structural features, and slots 3 and 4 a peer-reviewed publisher and a national insurance carrier consumer page. A representative row 5 records "how do I know if I have psoriasis" in Boston, AIO shown, five citations, with slots 1 through 3 held by NIH DermNet, the American Academy of Dermatology, and a peer-reviewed journal, slot 4 a Boston teaching-hospital practice page, and slot 5 vacant. The 168-slot aggregate reported in this study is the sum across those rows over the observation window.
1. AI Overview presence — how often it appears on US healthcare queries
Across the 50-query sample the AI Overview appeared on 43 queries (86.0 percent). Of the seven queries with no AI Overview, three were pure transactional local-pack queries (schedule dermatologist LA), two were branded shortcut queries where a knowledge panel occupied the top slot, and two were emergency-adjacent phrasing where Google appears to suppress generative summaries entirely (chest pain radiating to arm, sudden vision loss right eye). The suppression pattern on emergency-adjacent phrasing is consistent with public statements from Google's Search Liaison team about generative-summary safety on high-stakes health queries; it also means a plastic surgery marketing page has to compete for AIO surfacing while an ER-content page will rarely see one.
| Cluster | Queries | AIO shown | % shown | Avg citations per AIO |
|---|---|---|---|---|
| Dental | 6 | 6 | 100% | 3.8 |
| Medical dermatology | 6 | 6 | 100% | 4.2 |
| Aesthetic dermatology / med-spa | 6 | 5 | 83% | 3.4 |
| Plastic surgery | 6 | 5 | 83% | 3.6 |
| IVF / fertility | 6 | 6 | 100% | 4.4 |
| Primary care / DPC | 7 | 6 | 86% | 3.7 |
| Orthopedic surgery | 7 | 6 | 86% | 4.0 |
| Psychiatry / mental health | 6 | 3 | 50% | 3.2 |
| Total | 50 | 43 | 86% | 3.9 |
Two cluster-level observations matter. First, psychiatry and mental-health queries surfaced an AI Overview at only 50 percent — half the queries in that cluster showed a resource-panel or a direct SAMHSA / 988 answer instead. Google's health-content guardrails on mental health remain visibly more restrictive than on aesthetic or dental categories, and a psychiatry practice looking to win AIO citations needs to understand it will only see the AIO surface on a subset of its intent phrasing. Second, dental, medical dermatology, and IVF fertility ran at 100 percent AIO surfacing — those clusters are dense with informational search intent (cost, procedure explainers, insurance, recovery) and Google appears to have decided the generative summary is the right default there.
2. Who gets cited — the entity-type breakdown
Across 43 AI Overviews and 168 total citation slots, four entity types absorbed 100 percent of the citations. The relative shares are the single most useful number in this study for a US healthcare operator deciding how much editorial budget to spend on AIO surfacing.
Two conclusions follow from this distribution. First, more than half of the citation slots (51.2 percent, federal plus medical society) are effectively reserved for authority sources a private provider cannot outrank. A dental practice will not push HHS out of the primary citation on a cavity-cause query, and a plastic surgery practice will not push the American Society of Plastic Surgeons out of a procedure-safety citation. The competition for provider citations happens in the remaining slots — the second, third and fourth positions — where peer-reviewed sources, media outlets, and provider websites all fight for surface area.
Second, the 16.1 percent provider-website share is meaningfully higher than a lot of pessimistic AI Overview coverage would suggest. On more than one in six citation slots the AI Overview reached into a provider website — sometimes a single-location independent practice, sometimes a two or three-location group, occasionally a hospital system. This is where an honest budget decision lives. If you write clinical content well, you will win citation slots. If you ship thin conversion pages, you will lose those slots to a media platform that shipped a comprehensive explainer instead.
3. Content patterns that win provider citations
We isolated 27 provider-website citations across the sample and examined the structural features of each cited page. Four features consistently correlated with citation. A fifth feature — first-person authority language — correlated weakly but did not appear to be required. The correlated features:
| Structural feature | Cited pages carrying it | Non-cited comparable pages carrying it | Signal strength |
|---|---|---|---|
| Total word count > 1500 | 26 of 27 (96%) | 31% | Very strong |
| FAQ block with FAQPage schema | 24 of 27 (89%) | 18% | Very strong |
| Named provider byline with credentials | 22 of 27 (81%) | 26% | Strong |
| Outbound links to primary sources | 21 of 27 (78%) | 14% | Strong |
| Table or comparison element | 16 of 27 (59%) | 22% | Moderate |
| Explicit HIPAA notice on page | 18 of 27 (67%) | 44% | Weak-moderate |
| First-person authority language | 14 of 27 (52%) | 39% | Weak |
The dominant pattern is comprehensiveness plus structure. Long-form explainer content that carries a named-provider byline, an FAQ block with structured markup, and outbound links to HHS or a specialty college wins citations at multiples of the rate that thin sales pages do. The presence of tables and comparison elements is meaningful but secondary. The presence of a HIPAA notice does not seem to drive citation directly — it correlates because pages that ship a HIPAA notice tend to be pages built by operators who also ship comprehensive content.
Two operator-side interpretations. First, if you have to prioritize, prioritize word count and FAQ schema. A dermatology practice page that goes from 900 words with no schema to 1700 words with a properly structured FAQ block will have moved from the 31 / 18 percent baseline column to the 96 / 89 percent citation column on both features. Second, the named-provider byline is doing work not just for AI Overview but for E-E-A-T signals broadly — the same byline that helps a page get cited by AIO also helps the same page rank higher in the ten blue links below the AIO.
What "1500-plus words" looks like when it is doing the work. The word-count feature correlates with citation not because Google is counting words, but because at 1500-plus a page necessarily covers the three-to-five sub-topics an AIO answer wants to draw from — condition definition, cause and epidemiology, treatment options with trade-offs, cost or insurance context, and recovery or maintenance. Pages that hit 1500 words by padding a thin sales pitch with generic filler do not earn citations; pages that hit 1500 by walking the five sub-topics honestly do. In the sample, the median cited page carried 2,180 words, an interquartile range of 1,650 to 2,740, and one outlier at 4,900 words on a plastic-surgery recovery explainer. The FAQ block on cited pages averaged 9.4 questions, with 60-to-140-word answers each, and the outbound-source count averaged 4.2 primary-source links per page — three of which were typically to HHS, CDC, or the relevant specialty college and one of which was typically to a peer-reviewed publisher.
4. HIPAA framing that AI Overview surfaces
The single most common question we get from US practice operators is whether HIPAA constraints depress AI Overview surfacing. The short answer, based on this sample, is no — HIPAA-appropriate content is cited by AIO at rates equal to or exceeding non-HIPAA-appropriate content. The longer answer requires distinguishing what HIPAA governs from what it does not.
HIPAA — the Health Insurance Portability and Accountability Act of 1996, administered by HHS through the Office for Civil Rights (OCR) — regulates protected health information (PHI). PHI is identifiable information about a specific individual's past, present, or future health condition. HIPAA does not regulate clinical explainer content, procedure economics, insurance coverage explanations, standard-of-care protocols, or general educational content about a condition. A dermatology explainer that says "acne has three underlying drivers — hormones, sebum, and bacterial colonization" is not PHI. A page that says "our patient Jane, a 34-year-old with severe cystic acne, saw complete clearance in 12 weeks on our protocol" is PHI-adjacent and creates HIPAA exposure unless the patient signed an OCR-compliant authorization.
Every provider page in our sample that earned an AI Overview citation was HIPAA-clean by construction. None named specific patients. None quoted case-specific outcomes tied to identifiable people. Most carried a HIPAA notice at the footer. The pattern we consistently observed: AIO-cited provider pages spoke in clinical generalities backed by primary-source citations, not in patient anecdotes. That structure is both what AIO wants and what OCR wants. The two forces are aligned in a way that surprises operators when they first understand it.
Practical HIPAA-safe content moves that also drive AIO surfacing: use aggregate outcome language rather than individual case narratives, cite peer-reviewed evidence for outcome claims, reserve testimonials for BAA-covered channels or explicit written authorizations, keep provider credentials and NPI numbers visible in the byline, and route all patient-communication actions (SMS reminders, appointment recall) through TCPA-safe workflows with clear opt-in language.
5. Cross-vertical patterns — dental vs. derm vs. plastic vs. IVF
Cluster-level behavior of the AI Overview differs meaningfully across our eight verticals. Two clusters — dental and IVF — surface the highest provider-citation share; two clusters — plastic surgery and mental health — surface the lowest.
| Cluster | Provider citations | % of cluster citations | Dominant non-provider citation source |
|---|---|---|---|
| Dental | 6 | 26% | American Dental Association, ADA consumer content |
| Medical dermatology | 4 | 16% | AAD, NIH DermNet, HHS |
| Aesthetic dermatology / med-spa | 2 | 12% | FDA (approvals), ASDS |
| Plastic surgery | 2 | 9% | ASPS, AAAASF, peer-reviewed journals |
| IVF / fertility | 7 | 27% | ASRM, SART, CDC ART reports |
| Primary care / DPC | 3 | 14% | AAFP, HHS, CMS |
| Orthopedic surgery | 2 | 8% | AAOS, NIH, peer-reviewed journals |
| Psychiatry / mental health | 1 | 10% | APA, SAMHSA, NIH, 988 |
| Total | 27 | 16% | — |
Dental is the highest-provider-share cluster because the American Dental Association's consumer content covers a wide but shallow surface area, leaving depth-of-explanation citations available to well-written practice pages. A dental practice that ships a 2000-word explainer on aligner-versus-brackets economics will consistently sit in slot 2 or slot 3 of the AIO alongside the ADA and Delta Dental. IVF and fertility earns the highest provider share at 27 percent because the clinical questions are numerous, technical, and highly personalized to a couple's specific hormonal or anatomical situation — patients want depth, and ASRM plus SART carry the primary-authority slots but rarely fill all four citation positions.
Plastic surgery, aesthetic derm and orthopedics sit at the lower end. In plastic surgery and aesthetic derm, the FDA and specialty-society citations dominate because most of the informational queries in those clusters have a safety or approval component that Google routes to a regulator-first citation. In orthopedics, peer-reviewed journals and AAOS content are so comprehensive that a private-practice page rarely adds citation-worthy depth. Mental health sits at the bottom because SAMHSA, APA and 988 hold the safety-adjacent slots almost exclusively.
6. Do citations shift by metro? The five-city test
We ran the same 50-query set from Dallas-Fort Worth, Los Angeles, New York, Chicago, and Boston. The high-order finding is that citation stability across metros is far higher than most operators expect. For 41 of 50 queries the primary AIO citation was identical across all five metros. For 6 queries the primary citation rotated between two federal-agency sources of equivalent authority (e.g. HHS versus CDC). For 3 queries — all in the local-pack-adjacent range — Google shifted from an AI Overview to a local-provider knowledge panel in one or two metros and left the AIO surface in the others.
Where metros did differ was in the provider-citation slot. The provider slot rotated between practice sites within the same metro at a meaningful rate — roughly one in three tracked queries showed a different provider-website citation in Los Angeles than in Boston over the observation window. The plain reading is that the AIO is geo-personalizing the provider-citation slot to some degree while holding the federal, medical-society, and journal slots stable across metros.
Two operator consequences. First, if you are a Dallas practice, you will not typically compete with a Los Angeles practice for the same AIO slot — you are competing within-metro. Second, the total number of provider-citation slots is roughly stable across metros, so the aggregate opportunity size is the same; the difference is which practice earns it in each local surface.
7. A 12-week AIO surfacing playbook for a US practice
The following is the sequenced playbook we run on a US healthcare marketing engagement out of Ichelon Consulting US's Dallas HQ. It is not a guarantee — as noted in the methodology, individual results vary — but it is the compressed version of what we have seen produce citation events across dental, medical derm and IVF clients on tracked queries within eight to twelve weeks.
Weeks 1-2: audit and target
Pull the ten highest-intent informational queries your practice would want to be cited for. For each, run the query from a fresh browser in your target metro and record whether AIO surfaces, which sources are cited, and in what order. Score every provider-facing content page you already own against the four structural features from Section 3 — word count over 1500, FAQ block with FAQPage schema, named-provider byline, outbound links to primary sources. Rank the shortest gap-to-citation opportunities to the top of the queue.
Weeks 3-6: content depth build
Rewrite the top three target pages to hit the four structural features. Word count is the biggest single lever — most practice pages sit between 400 and 900 words and need to move to 1500 to 2500. The FAQ block is the second-biggest lever; write eight to twelve real questions, answer each in 60 to 120 words with a primary-source outbound link where the claim needs one, and wrap the block in FAQPage schema. Add a named-provider byline with an NPI number, a CV link, and a signed authored-by disclosure. Add three to six outbound links per page to HHS, CDC, or the specialty college.
The FAQ questions are worth writing from first principles rather than pulling from a generic list. The pattern that correlated with citation in our sample was practitioner-authored questions that walked the actual pre-consult decision — "how do I know whether I need a biopsy or watchful waiting on this lesion", "what does the recovery look like week-by-week for the first six weeks after this procedure", "which parts of this treatment does BCBS Texas typically cover and which parts stay out-of-pocket". Generic FAQ boilerplate — "what is dermatology", "is your practice licensed" — does not earn citation. It also helps to structure the answer text so the first sentence stands as a direct-answer clause the AIO can lift verbatim; a 60-to-120-word answer that opens with a clean 20-word declarative sentence is the shape the AIO surfacing engine appears to reach for. Photos and diagrams should carry descriptive alt text that names the specific clinical entity or procedure, not the practice brand, because the AIO's image-associated citations occasionally reach through alt text to prioritise a page with named clinical imagery over one without.
Weeks 7-8: HIPAA + TCPA hardening
Sweep all patient-communication surfaces for HIPAA and TCPA exposure — form-to-CRM handoffs under a BAA, SMS opt-in language explicit and time-stamped, testimonial page audited for consent, aggregate-outcome language replacing case-specific claims where the source lacks explicit written authorization. The AIO does not read your privacy notice, but the OCR does read your patient-communication logs when a complaint escalates, and a practice earning AIO citations while carrying HIPAA exposure has traded one risk for another.
Weeks 9-12: monitor and iterate
Re-run the target queries weekly. Track citation events per page. Where the AIO surfaces a competitor practice site instead of yours on a target query, pull the competitor page and compare structural features. Most of the time the delta is either word count, FAQ depth, or outbound-source density — patch the gap. Where the AIO surfaces a federal or medical-society citation instead of yours, treat that as un-winnable in the primary slot and target the secondary or tertiary citation instead.
8. Limits and methodology notes
This study observes 50 queries and reports 168 citation slots. It is a probe, not a census. The queries are curated and skew commercial and clinical rather than fully representative of the entire US healthcare AIO surface. Personalization effects — signed-in Google account, prior search history, device — are not fully controlled; we mitigated by using fresh browser sessions and neutral geo-locators but we did not run a laboratory-grade experiment. Citation stability was tested weekly across a four-week re-sample; longer-window volatility remains unknown at this study's timeline. Provider-page structural-feature scoring is manual and subject to some observer variance. Sample-size limitations mean the reported multipliers (e.g. 3.2x citation rate for four-feature pages) carry wide confidence intervals and should be read as directional rather than precise.
This study also does not attempt to measure downstream click behavior or clinical-outcome impact from AIO citation. The click question — how many people actually click into a provider website from the AI Overview citation — is an open one that the ecosystem has not answered with reliable data, and any operator basing spend decisions purely on AIO click-through-rate assumptions should treat those assumptions as speculative.
About Ichelon Consulting US (Dallas HQ)
Ichelon Consulting US is the US-facing sister brand of Ichelon Consulting Group, headquartered in Dallas-Fort Worth, Texas. Ichelon Consulting US runs HIPAA-aware healthcare marketing engagements across dental, dermatology, aesthetic, plastic surgery, IVF, primary care, and orthopedic verticals. Every engagement is built on the same three-part discipline this report reflects: comprehensive clinical content, primary-source citation hygiene, and HIPAA-plus-TCPA compliant patient-communication design. Practices interested in a market-fit review or a citation-audit of an existing content library can book a benchmarking call from the office card below.
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Frequently asked
How were the 50 queries chosen?
Six to seven queries per cluster across eight clinical clusters, mixing high-commercial intent, symptom-led informational intent, and category-comparison intent. Branded queries were excluded because the goal was to observe AIO citation behavior on unbranded searches — where the searcher has not yet committed to a provider entity.
Does AIO cite the page or the source?
Both. On 34 of 50 queries the AIO cited a mix of primary sources (federal, society, journal) and secondary sources (provider website, media). On 11 queries only primary sources appeared. Well-structured provider pages compete for the secondary slot with meaningful consistency.
Is HIPAA-safe content surfacing in AIO?
Yes. Every provider page cited in the sample was HIPAA-clean — no patient identifiers, no case-specific claims, no unconsented testimonials. AIO rewards clinical depth and structured Q&A; HIPAA constrains what you say about identified people. The two are aligned.
How often do AIO citations change?
41 of 50 primary citations stayed stable across a four-week re-sample. Six rotated between peer sources of similar authority. Three lost the AIO surface entirely. Provider-slot rotation was higher — roughly one in three provider citations rotated between practice sites in the same metro over four weeks.
Can a small clinic realistically rank in AIO?
Yes. Nineteen of the 27 provider citations in the sample came from single-location or two-location independent practices. The correlated features — word count over 1500, FAQ schema, credentialed byline, primary-source outbound links — are all achievable on a modest editorial budget over an eight-to-twelve-week window.
Want us to audit your practice for AIO surfacing?
Book a 30-minute benchmarking call with Ichelon Consulting US's Dallas team. We will pull the AIO surface for your top ten target queries, score each of your existing pages against the four structural features from Section 3, and hand you a prioritized citation-opportunity list — no obligation.
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