An off-site citation map for AI patient-discovery, built from 38,178 ChatGPT citation events across 200 NPI-stratified practices, 16 metros, and 11 specialties. The vendor pitch ranks national directories first. The data ranks them fourth.
Off-site citation sources differ by specialty and metro. In most markets, the largest lanes are free sources that practices rarely manage, such as hospital staff rosters and specialty-association credentialing pages.
Where the 38,178 citation events actually land. Practice-owned domains, hospital systems, and specialty associations together carry 72.6%. National directories – the standard vendor pitch – are fourth at 8.0%. Pick a specialty to see how the map reshapes.
| # | Source bucket | Cites | Share |
|---|---|---|---|
| 1 | Practice-owned domains | 10,061 | 26.35% |
| 2 | Hospital systems + AMC staff rosters | 9,565 | 25.05% |
| 3 | Specialty associations + credentialing | 8,100 | 21.22% |
| 4 | National medical directories | 3,038 | 7.96% |
| 5 | State medical boards | 2,165 | 5.67% |
| 6 | Review aggregators | 1,428 | 3.74% |
| 7 | Federal authority (NIH, CDC, FDA) | 1,130 | 2.96% |
| 8 | Regional city magazines | 1,047 | 2.74% |
| 9 | Ranking aggregators (Newsweek, MediFind) | 970 | 2.54% |
| 10 | Lab + imaging chain locators | 432 | 1.13% |
| 11 | Other (Castle Connolly, news, misc) | 242 | 0.63% |
Hospital-system staff rosters and specialty-association credentialing pages together carry 46.3%. National directories carry only 8.0% – and most practices have two or three vendors there.
Get providers added to the staff rosters of the hospital systems you affiliate with before renewing another directory subscription.
Plastic surgery: specialty-association credentialing at 30.1%. Cardiology: hospital systems at 33.4%.
Filter the map above by your specialty before deciding which lanes to invest in. The all-specialties mean is the wrong target for any single cell.
Review aggregators are 3.7% combined, Yelp is 0.11%, and Google Business Profile has zero direct citations.
Reviews and Google Business Profile support patient conversion rather than direct ChatGPT citations, so they should keep their own budget.
Exploratory secondary analysis of an existing corpus, single-platform (ChatGPT), cross-sectional, US-only. Source-type buckets were generated by a deterministic Python classifier on May 21, 2026 – the previous "practice-or-other" residual was split into clean buckets using deterministic rules plus Claude Code subagent classification of the long tail. No causal claims; all numbers are descriptive citation-share data. Dentistry is a post-hoc, single-vertical addition collected on June 14, 2026 with model gpt-5.5-2026-04-23 (517 responses across the same 16 retained metros and 12 templates as the medical verticals) – collected later and in a single day, separate from the pre-registered medical run. Full methodology and pre-registered hypothesis verdicts available on request. For the on-site companion, see why ChatGPT doesn't mention your practice.
The analysis lives in MGMA – including the magazine-pipeline geography (which eight metros carry it, which five have no pipeline) and the three on-Monday moves administrators can run themselves. Read the full article in MGMA →
Also covered in Medical Economics: “Why ChatGPT Favors Hospitals Over Independent Practices” →Run a free scan to see your A–F visibility grade and how often ChatGPT cites your practice.