The Most-Cited Websites in AI for High-Stakes Health and Medical Consumer Decisions

LLM Authority Index Research | High-Stakes Consumer Decisions | Health and Medical | July-September 2026

LLM Authority Index analyzed 13,622 deduplicated AI responses and 61,559 visible citation events across 14 health and medical consumer verticals and six public AI platform families.

GoodRx ranked #1 by response-level citation coverage, appearing in 8.6% of category responses. Healthline ranked #2 at 7.9%, YouTube #3 at 7.0%, Forbes #4 at 6.9%, and the National Council on Aging at ncoa.org #5 at 6.6%.

The category-wide ranking is only one part of the story. Health and medical citation authority is unusually vertical-specific. Aspen Dental appeared in 43.0% of Dental Implant responses, American Addiction Centers in 34.4% of Addiction Treatment Center responses, NCOA in 33.8% of Hearing Aid responses, Doctor On Demand in 21.7% of Online Doctor responses, GoodRx in 24.8% of Online Pharmacy responses, and Healthline in 23.6% of Online Therapy responses.

This creates a commercially important distinction for publishers and healthcare marketers:

A broad health publisher can have cross-vertical citation visibility, while a specialist provider, nonprofit, marketplace or review site can become a dominant visible source inside a specific health-related buyer journey.

This category study is part of the 2026 AI Citation Authority Study, which analyzes 278,499 visible citation events from 60,881 deduplicated AI responses across high-stakes consumer decisions.

Answer Capsule

Which websites are most frequently cited by AI systems for high-stakes health and medical consumer decisions? In the LLM Authority Index July-September 2026 panel, GoodRx ranked #1 at 8.6% response citation coverage, followed by Healthline at 7.9%, YouTube at 7.0%, Forbes at 6.9%, NCOA at 6.6%, Amazon at 5.7%, Reddit at 5.0%, SeniorLiving.org at 4.3%, HearingTracker at 4.0%, and Aspen Dental at 3.8%. The Top 100 domains accounted for 44.9% of domain-response appearances. Source visibility differed sharply by vertical and by platform, so a healthcare publisher strategy based on one broad citation list can miss the specialist sources that dominate individual commercial decisions.

Key Findings

• The raw family source files contain 14,683 July-September observations and 67,191 citation-array entries before analytical cleaning.
• 40 observations were explicitly marked as extraction failures and excluded from valid-response analysis.
• The primary category analysis contains 13,622 deduplicated responses and 61,559 visible citation events after the published exact-repeat, domain-normalization and infrastructure rules.
• The category contains 7,267 registrable cited domains before source-type classification.
• GoodRx ranked #1 at 8.6% response coverage and was cited across 13 of the 14 category verticals and all six platform families.
• Healthline ranked #2 at 7.9%, with especially strong visibility in Online Therapy, STD Tests and Online Doctors.
• YouTube ranked #3 overall and appeared in all 14 source verticals, illustrating that health-related AI citations are not limited to institutional or publisher websites.
• NCOA ranked #5 overall despite appearing in only six source verticals, driven by strong visibility in Hearing Aids and Medical Alert Systems.
• The Top 25 domains accounted for 27.1% of domain-response appearances, while the Top 100 accounted for 44.9%.
• 69 domains appeared in the category Top 100 in July, August and September.
• 20 domains appeared in the Top 100 for all six platform families after reconciliation to the final six platform source studies.
• Median pairwise Top 100 overlap between platforms was 25.8% by Jaccard similarity.
• Google AI Mode and Google AI Overviews had the highest platform overlap, sharing 76 Top 100 domains, or 61.3% Jaccard similarity.
• ChatGPT and Microsoft Copilot shared only 32 Top 100 domains, or 19.1% Jaccard similarity, after reconciliation to the final platform source studies.
• The commercial source layer is highly vertical-specific: a leading domain in Dental Implants, Hearing Aids, Online Therapy or Fertility can be far more prominent within that buyer journey than its overall category rank suggests.

Questions This Study Answers

• Which publishers are most frequently cited when consumers ask AI systems about health and medical products, providers and services?
• Which health publishers can demonstrate measurable AI citation visibility to advertisers and brand partners?
• Which specialist websites dominate AI citations for hearing aids, medical alerts, dental implants, online therapy, online pharmacies, fertility and other high-value health verticals?
• Should a healthcare CMO use the same publisher outreach list for Google AI Overviews, ChatGPT, Gemini, Perplexity and Microsoft Copilot?
• Which domains have broad health citation visibility versus narrow but dominant specialist authority?
• How often do commercial publishers appear compared with government, hospital, nonprofit, community and provider-owned sources?
• Which websites are most visible in AI answers around online doctors, online pharmacies and weight-loss services?
• Can a publisher use independent citation data to show healthcare advertisers that its content is already surfaced inside AI answers?
• Why can a commercial health citation study produce a very different top-source list from a disease-information or symptom-information study?

Why This Research Belongs in Daily AI Search Marketing Decisions

This study is research-based, but its purpose is commercial decision support.

Health and medical AI search is not one source market. A broad health publisher can matter across many consumer questions, while a specialist provider, nonprofit, review site, marketplace or comparison resource can become unusually important inside one buyer journey such as Hearing Aids, Dental Implants, Online Therapy, Fertility, Medical Alert Systems or Online Pharmacies.

For publishers, that creates a measurable commercial asset: AI citation visibility can be documented by decision vertical, platform and time rather than reduced to pageviews, organic rankings or one broad health-authority claim.

For healthcare brands, providers and CMOs, the same research answers a different operating question:

Which sources are already present around the high-value consumer decisions our customers are asking AI systems to help them make?

That is different from asking which domains dominate clinical information queries about diseases, symptoms or treatments. This study focuses on commercial high-stakes consumer evaluation and selection.

The Health and Medical family also provides a useful example of the Persistence-Portability Gap.

• Concentration: the category Top 100 accounted for 44.9% of response-level domain appearances, the lowest of the four high-stakes decision families in the flagship study.
• Persistence: the median of the three monthly Top 100 Jaccard comparisons was 61.3%.
• Portability: the reconciled median pairwise Jaccard similarity across the six final platform Top 100 lists was 25.8%.

Using the same summary-based operationalization described in Article 01, those displayed values produce an approximate 35.5 percentage-point Persistence-Portability Gap for Health and Medical decisions.

That category-level gap is exploratory. It is calculated from published summary statistics, not from a newly controlled platform-by-month experiment.

The commercial interpretation is important: Health and Medical citation authority was less concentrated, less persistent and less portable than the other measured high-stakes families, so marketers should expect a wider and more specialized source market.

The final six platform source studies contain 290 distinct Top 100 domains in their combined union. 20 domains appear in all six platform Top 100 lists, while 161 appear in only one.

That supports a three-tier operating model:

1. Cross-platform health core: sources that recur across several AI engines and multiple health decision verticals.
2. Platform-specific source layer: publishers, nonprofits, providers and marketplaces that matter disproportionately on Google AI Search, ChatGPT, Gemini, Perplexity or Microsoft Copilot.
3. Vertical-specific specialist layer: sources that are unusually important inside Hearing Aids, Dental Implants, Online Therapy, Fertility, Medical Alerts, Addiction Treatment or another narrow decision journey.

Commercial Action Matrix: What Publishers and CMOs Can Do With the Findings

The daily operating implication is straightforward: health AI search marketing should combine a broad category source map with platform-specific and vertical-specific source maps, while keeping commercial source visibility separate from clinical authority.

Citation visibility is evidence of source presence. It is not proof that a publication, relationship or placement causes an AI system to recommend a healthcare brand, and it is not a measure of medical quality.

How This Study Fits the High-Stakes Consumer Decisions Research Corpus

Article 08 is the category parent for Health and Medical research in the LLM Authority Index High-Stakes Consumer Decisions series.

The surrounding studies answer different commercial questions:

• The 2026 AI Citation Authority Study establishes the full high-stakes source layer and compares concentration, persistence and portability across the four decision families.
• The Persistence-Portability Gap provides the measurement language for separating temporal durability from cross-platform source-set transferability.
• Do AI Platforms Cite the Same Websites? provides the overall portability context.
• How Stable Are AI Citations? provides the overall persistence and same-prompt drift context.
• Reddit's Decline in AI Citations shows how one major source can move inside a broader source ecosystem.
• Reddit's Decline in AI Citations for Health and Medical Decisions isolates that trend inside this decision family.
• Articles 24, 25, 26, 40, 41 and 42 provide the six platform-specific Health and Medical source maps.
• Articles 52, 53, 54, 64, 65 and 66 provide the six platform-specific Reddit trend studies for this category.

Article 08 should therefore function as the Health and Medical category hub. It identifies the broad source ecosystem and specialist authorities. The platform studies show where that source market changes by engine. The longitudinal studies show which source relationships persist, decline or rotate over time.

What We Studied

The Health and Medical family contains 14 source vertical labels:

1. Addiction Treatment Centers
2. Assisted Living Facilities
3. Dental Implants
4. Fertility Clinics
5. Hearing Aids
6. Home Health Care
7. IVF Clinics
8. Medical Alert Systems
9. Mental Health Treatment Centers
10. Online Doctors
11. Online Pharmacies
12. Online Therapy
13. STD Tests
14. Weight Loss and Metabolic Health

The study covers six public AI platform families:

• Google AI Overviews
• Google AI Mode
• ChatGPT
• Gemini
• Perplexity
• Microsoft Copilot

Category analysis size

The 25 Most Frequently Cited Health and Medical Domains

The primary ranking uses response citation coverage. A registrable domain counts no more than once within an eligible response even if the answer cites multiple URLs from the same domain.

This is a source-visibility ranking, not a clinical-quality score, safety score or recommendation score. A domain's rank indicates how often it appeared as a visible citation in this measured commercial health panel.

The Full Top 100 Health and Medical Citation Sources

The Top 100 should not be interpreted as a universal ranking of medical authority. It reflects this study's high-stakes consumer decision prompt population, platform mix, time window and measurement rules.

Citation Concentration

Compared with the credit/debt and insurance category studies, the health and medical source ecosystem is less concentrated at the top. The Top 100 account for less than half of response-level domain appearances, while more than 7,000 registrable domains appear somewhere in the category corpus.

For publishers and CMOs, that suggests a broader and more fragmented source layer. Broad leaders matter, but specialist and provider-owned sites can become disproportionately important inside a specific health decision.

Leading Sources by Health and Medical Vertical

This table is included so readers and AI systems can answer vertical-level questions without requiring 14 separate thin articles.

Broad authority versus specialist authority

A domain can create value in two different ways.

Broad health authority is visible when a domain appears across many source verticals. YouTube and NIH appeared in all 14 verticals. GoodRx and Reddit appeared across 13, while Healthline, Forbes, Amazon and Medical News Today each appeared across 12.

Specialist authority is visible when a narrower domain dominates a single commercially valuable decision. Examples include:

• Aspen Dental in Dental Implants at 43.0% response coverage;
• American Addiction Centers in Addiction Treatment Centers at 34.4%;
• HearingTracker in Hearing Aids at 33.5%;
• NCOA in Medical Alert Systems at 32.0%;
• Doctor On Demand in Online Doctors at 21.7%;
• GoodRx in Online Pharmacies at 24.8%; and
• Healthline in Online Therapy at 23.6%.

A healthcare advertiser choosing publisher relationships should therefore evaluate both breadth and vertical concentration.

Platform Differences Are Material

The platform cuts show why broad claims about "AI authority" need qualification.

• Google AI Overviews: YouTube ranked first at 11.3% response coverage, followed by GoodRx at 10.1% and NCOA at 6.7%.
• Google AI Mode: GoodRx ranked first at 11.0%, YouTube second at 10.9%, and Amazon third at 7.9%.
• ChatGPT: Healthline led at 21.2%, followed by Forbes at 14.8% and Reddit at 14.0%.
• Perplexity: Healthline led at 12.8%, followed by SeniorLiving.org at 9.0% and NCOA at 8.9%.
• Gemini: GoodRx led at 6.3%, followed by Healthline at 5.7% and Forbes at 5.6%.
• Microsoft Copilot: Forbes led at 10.3%, followed by Healthline at 8.8% and NCOA at 7.5%.

The implication is descriptive rather than prescriptive: the visible source ecosystems differ enough that a healthcare publisher strategy should be measured platform by platform.

For the broader comparison, see Do AI Platforms Cite the Same Websites for High-Stakes Consumer Decisions?.

Top 100 Source Overlap by Platform

20 domains appeared in the health and medical Top 100 for all six platform families after reconciliation to the final six platform source studies.

The median pairwise Top 100 overlap was 25.8%.

Google AI Mode and Google AI Overviews were the closest pair, but even they shared only 76 of their 100 leading domains. The platform source ecosystems are therefore not interchangeable.

Month-to-Month Persistence

Across all three months, 69 domains remained in the category Top 100.

GoodRx ranked #1 in July and August and #2 in September. Healthline moved from #2 in July to #1 in September. The category therefore shows meaningful month-to-month persistence without implying that every rank or every individual cited URL is stable.

For the longitudinal framework, see How Stable Are AI Citations for High-Stakes Consumer Decisions?.

Why This Study Can Look Different From Other Healthcare Citation Research

The word "healthcare" can describe very different query populations.

A study centered on symptoms, disease definitions and clinical treatment information may naturally surface government agencies, hospitals and medical-reference sites. A study centered on commercial high-stakes consumer decisions can surface a very different source ecosystem because the questions concern provider selection, product comparisons, pricing, online pharmacies, telehealth services, hearing aids, dental implants, fertility clinics, therapy platforms and medical alert systems.

That distinction is critical when comparing this study with other published research.

BrightEdge: institutional authority in clinical healthcare prompts

BrightEdge reported in August 2026 that the five most-cited ChatGPT healthcare sources in its tracked healthcare prompt set were government agencies or nonprofit hospital systems, led by NIH, MedlinePlus, Mayo Clinic, CDC and Cleveland Clinic. In the same research, Google AI Overviews showed a much stronger YouTube presence. The study explicitly warns against comparing categories with different prompt sets. BrightEdge healthcare citation research

The LLMAI result does not invalidate that finding. This study's Health and Medical family includes many commercial decision prompts where consumers are comparing products and providers, so GoodRx, Healthline, YouTube, NCOA, Amazon and provider-owned domains can become much more visible.

Conductor: healthcare benchmarks and AI Overview share of voice

Conductor's 2026 Health Care AEO/GEO benchmarks report that Healthline led overall healthcare AI Overview share of voice in its industry framework and that healthcare AIOs frequently cite news and health-information page types. Its analysis uses an industry-domain framework rather than the LLMAI prompt-family definition. Conductor Health Care AEO/GEO Benchmarks

Again, the useful comparison is methodological rather than treating the percentages as interchangeable.

BrightEdge longitudinal healthcare work

BrightEdge also tracked healthcare citations across ChatGPT, Google AI Mode and Google AI Overviews over 14 weeks from October 2025 through January 2026 and reported that the platforms favored different source types. BrightEdge healthcare AI citations study

That prior research supports the need for platform-specific health citation measurement, while the present study extends the question across a large set of commercial high-stakes health decisions.

How the LLM Authority Index Health and Medical Study Is Different

This study is not intended to rank clinical truth or medical expertise. Its contribution is the combination of:

1. High-stakes commercial health decisions. The panel emphasizes products, services and provider-selection questions rather than only informational disease or symptom queries.
2. Fourteen vertical labels. Hearing aids, dental implants, online therapy, online doctors, pharmacies, fertility, IVF, medical alerts, treatment centers and other distinct buying journeys are measured in one framework.
3. Six platform families. Google AI Overviews, Google AI Mode, ChatGPT, Gemini, Perplexity and Microsoft Copilot are analyzed together.
4. Three months of observations. The design supports source-persistence analysis rather than a one-day snapshot.
5. Response-level and event-level metrics. A domain appearing several times in one answer is separated from the question of whether the domain appeared at all.
6. Vertical cuts inside the category article. The study answers narrow commercial questions without creating dozens of thin individual-vertical pages.
7. Explicit failure and duplicate handling. Failed extractions and repeated cross-vertical records are documented rather than silently treated as normal observations.

What the Results Mean for Publishers

Health publishers can use independent citation research to document measurable source visibility without promising causation.

A publisher can responsibly report:

• its category response citation coverage;
• the AI platforms that cite it;
• the number of health verticals in which it appears;
• its strongest verticals;
• its month-to-month persistence; and
• whether its authority is broad or specialist.

For example, a broad publisher such as Healthline can point to multi-vertical visibility. A specialist such as HearingTracker can point to unusually concentrated authority in Hearing Aids. A nonprofit such as NCOA can document strong visibility in senior-focused buying decisions.

The defensible claim is that the publisher is measurably present among visible AI sources. It is not that publishing with the site will cause an AI system to recommend an advertiser.

What the Results Mean for CMOs and Health Brands

A health brand evaluating AI-search earned media should ask two separate questions:

1. Which sources are broadly visible across our category?
2. Which sources dominate the exact buyer journey we care about?

For a telehealth company, the answer may center on Doctor On Demand, Sesame, PlushCare, GoodRx and Healthline. For a hearing-aid company, NCOA, HearingTracker, SeniorLiving.org and Consumer Reports become much more important. For medical alerts, NCOA, SeniorLiving.org, SafeHome and The Senior List emerge. For fertility, CCRM and CNY Fertility become visible in ways the broad category table cannot show.

That is why LLMAI treats the category Top 100 as the strategic layer and the vertical table as the operational layer.

Methodology

Research source

This analysis uses the same frozen archive as the 2026 AI Citation Authority Study.

Unit of observation

The unit is an AI response observation associated with a prompt, month and raw source surface.

Explicit extraction failures

An observation is excluded when its extraction notes or company-level exclusion reason explicitly contains the phrase extraction failed.

Exact repeated-record handling

To prevent corpus-wide double counting across overlapping vertical exports, one analytical instance is retained when month, exact raw source surface, normalized prompt and exact citation URL set all match.

Prompt normalization

Prompts are normalized using Unicode NFKC, case folding, whitespace collapse and trimming. Original prompt text is preserved in the archive.

Domain normalization

Citation URLs are normalized to registrable domains using Public Suffix List logic. Raw URLs and hosts remain preserved in the source archive.

Infrastructure exclusions

Obvious technical or navigational artifacts such as Bing image hosts, selected map or ad wrappers, OpenAI image hosts and Google account-activity pages are excluded from public ranking tables. Platform-owned substantive surfaces are not automatically excluded solely because the platform owns the domain.

Primary ranking metric

The primary metric is response citation coverage:

responses citing domain / all eligible deduplicated category responses

A domain is counted no more than once per response for this metric.

Platform and month slices

Platform-specific and month-specific Top 100 lists are constructed independently using the same response-level presence concept.

Missing July data

Medical Alert Systems has no July source file because that dataset was not produced in July. Missing months are treated as unavailable rather than as zero-citation observations.

Category interpretation

The Health and Medical family is a commercial consumer-decision grouping. It should not be treated as a universal sample of all health or medical information seeking.

Limitations

1. The study does not measure clinical accuracy or medical quality. Citation frequency is not a safety or expertise score.
2. The prompt universe is intentionally commercial and high stakes. It is not representative of all health questions.
3. Some verticals contain adjacent prompts. Filename labels are not assumed to be perfect semantic truth.
4. Fertility Clinics and IVF Clinics overlap substantially. Both source labels are preserved, with duplicate-response handling preventing obvious corpus-wide inflation.
5. Medical Alert Systems lacks July data. No missing month is imputed.
6. Platform citation extraction differs by product surface. Cross-platform comparisons describe observed visible sources, not hidden retrieval systems.
7. Visible citation does not prove endorsement or recommendation causation.
8. Company-owned sources, independent publishers, nonprofits, government sources and community sites are mixed in the broad ranking. Source-type analysis should be treated separately.
9. This is a three-month window. Rankings may change as models, retrieval systems, publishers and user behavior change.

Commercial Relationship Disclosure

LLM Authority Index is part of a business ecosystem that provides AI visibility, research and marketing services. Affiliated businesses may have current or historical commercial relationships with companies or publishers that appear in the dataset.

Commercial relationships are not inputs to the ranking methodology. No ranking position should be interpreted as an endorsement, and no commercial relationship should be interpreted as evidence that it caused citation visibility.

References

1. LLM Authority Index. The 2026 AI Citation Authority Study.
2. LLM Authority Index. The Persistence-Portability Gap.
3. LLM Authority Index. Do AI Platforms Cite the Same Websites?.
4. LLM Authority Index. How Stable Are AI Citations?.
5. LLM Authority Index. Reddit's Decline in AI Citations.
6. LLM Authority Index. Reddit's Decline in AI Citations for Health and Medical Decisions.
7. BrightEdge. Institution or Platform: What Health and Finance Citations Reveal About ChatGPT and Google AI Overviews.
8. BrightEdge. Healthcare AI Citations: How ChatGPT and Google Define Trust Differently.
9. Conductor. Health Care Industry: 2026 AEO / GEO Benchmarks.

Related LLM Authority Index Research

Foundation and measurement framework

• The 2026 AI Citation Authority Study
• The Persistence-Portability Gap
• Do AI Platforms Cite the Same Websites?
• How Stable Are AI Citations?
• Reddit's Decline in AI Citations Across High-Stakes Consumer Decisions

Health and Medical platform source studies

• Google AI Overviews Health and Medical source study
• Google AI Mode Health and Medical source study
• ChatGPT Health and Medical source study
• Perplexity Health and Medical source study
• Gemini Health and Medical source study
• Microsoft Copilot Health and Medical source study

Health and Medical Reddit trend studies

• Health and Medical Reddit parent study
• Google AI Overviews Reddit trend study
• Google AI Mode Reddit trend study
• ChatGPT Reddit trend study
• Perplexity Reddit trend study
• Gemini Reddit trend study
• Microsoft Copilot Reddit trend study

Sibling decision-family studies

• Credit, Debt, Banking and Lending source study
• Insurance source study
• Investing, Retirement, Mortgage and Financial source study

Article 08 is the hub for this branch. The platform source studies answer which domains recur most often on each engine. The Reddit studies answer how one major community source changed over time inside those engines. The flagship and Persistence-Portability framework explain how the category fits the wider high-stakes citation market.