US Medical Clinics in Wikidata by State (2026)

When patients ask AI for a clinic near them, your practice is only in the answer if it's in the knowledge graph. ChatGPT, Claude, and Perplexity don't search the whole web—they query Wikidata and other structured knowledge bases. Today, thousands of US hospitals are in Wikidata, but only a small number of medical clinics (with an official website) are. This post uses live data to show how many US clinics appear in Wikidata and, where available, by state—and how your practice can get into the graph so AI can recommend you.

The real GEO lever isn't tracking whether you show up—it's getting listed in the first place. Publishing your clinic to Wikidata with location, specialties, and contact details puts you in the pool AI assistants actually query. Below: the numbers. At the end: how to close the gap.

National totals

• US medical clinics in Wikidata (with official website): ~35 (varies with script run; see multi-industry report).
• US hospitals in Wikidata (comparison): ~3,300+

The clinic–hospital gap is stark: the knowledge graph is heavily skewed toward hospitals, and the vast majority of independent and small-to-medium medical practices are absent.

By state

State-level counts depend on entities having located in (P131) set to a US state. When we run the coverage script, any state with at least one clinic (with website) in Wikidata appears in the report. If the state table is empty or sparse, it means most US clinic entities in Wikidata do not yet have state-level location—so national totals are the main story: very few clinics are in the graph at all.

Run the script and check reports/wikidata-medical-clinic-coverage.json for the latest byState array when you refresh the data.

What this means for you

• Largest gap: Medical clinics are among the most under-represented local businesses in Wikidata relative to demand ("find me a doctor/clinic" in AI search). That means your practice has high upside and very little in-graph competition.
• Publish and locate: Getting your clinic into Wikidata with state (and city, if possible) and specialty is what lets AI recommend you when patients ask by location or condition.
• For agencies: The national and state numbers are pitch-ready. "Almost no US clinics are in the knowledge graph. We can get your client listed so they show up when patients ask AI for a clinic."

The GEO approach that actually creates visibility

Most AI visibility tools only report whether you appear in ChatGPT or Perplexity—they don't add you to the source. GEMflush is built around the opposite idea: we publish your clinic to Wikidata with 11+ structured properties (name, address, specialties, insurance, languages, website, and more). Monthly updates keep your listing current. Once you're in the graph, you're in the set of practices AI can recommend. That's knowledge graph engineering for GEO: change the data AI uses, not just the report you see.

Methodology

• Medical clinic: instance of health care facility (Q1774898) or business with medical specialty (P1995); excludes hospitals (Q16917).
• US: country = United States (P17=Q30).
• With website: has official website (P856).
• State: P131 to state of the United States (Q35657).

Data as of March 2026. Numbers from SPARQL queries against the public Wikidata Query Service. Run pnpm tsx scripts/wikidata-medical-clinic-coverage-stats.ts to refresh.

Get your clinic in the graph

• Medical Clinic Visibility in ChatGPT — how to get your practice discovered by AI assistants.
• How to Get Your Medical Clinic in ChatGPT — step-by-step guide.
• GEMflush publishes your clinic to Wikidata with full structured data and tracks when you appear in AI responses. Get started or see AI visibility for agencies.