Original research · 2026-07 edition

AI SEO Statistics: Orthopedic Surgeon (2026-07 edition)

40 questions · 120 AI responses · 3 models · measured 2026-07-06

See how AI talks about YOUR businessFull data table

The question bank

The questions we tested — sampled from real buyer journeys in orthopedic surgeon.

Each model answered every question once, same wording, same day. These are the prompts behind every percentage on this page.

How do I know if my knee pain is just a strain or if I actually need to see an orthopedic surgeon?
What's the difference between a sports medicine doctor and an orthopedic surgeon for a torn ACL?
Can a physical therapist fix a rotator cuff tear without me needing surgery?
I have a $5,000 deductible; how much does a typical meniscus repair cost out of pocket?
What questions should I ask an orthopedic surgeon during the first consultation to see if they're a good fit?
Is it better to go to a private practice orthopedist or one affiliated with a major university hospital?
My hip has been clicking for months, should I get an MRI before I even book an appointment?
How can I check a surgeon's complication rates for total hip replacements?
Show all 40 questions
Are there any non-surgical treatments for carpal tunnel that actually work long-term?
How long is the typical recovery time for a spinal fusion before I can return to a desk job?
What are the red flags I should look for when reading online reviews for an orthopedic clinic?
Should I see a general orthopedist or a hand specialist for a suspected scaphoid fracture?
Does insurance usually cover a second opinion if the first surgeon recommends a total knee replacement?
I'm a marathon runner with a stress fracture; how do I find a surgeon who specializes in athletes?
What's the wait time usually like for an elective shoulder surgery in a mid-sized city?
Can I get a cortisone shot from my primary care doctor or do I need to see a specialist?
What are the pros and cons of robotic-assisted knee surgery versus traditional methods?
How do I find out if an orthopedic surgeon is board-certified and has any malpractice claims?
I fell and think I broke my wrist, should I go to the ER or try to find an ortho with same-day appointments?
Is it normal for an orthopedic surgeon to spend less than 10 minutes with you during an evaluation?
What are the latest alternatives to surgery for chronic lower back pain?
If I need a joint replacement, how do I compare the quality of different local surgical centers?
Are there specific orthopedic surgeons who focus on geriatric care for hip fractures?
How much does a consultation cost if I don't have health insurance?
What should I do if my surgeon is pushing for an operation but I feel like I can manage the pain?
Do I need a referral from my GP to see an orthopedist for a chronic ankle issue?
How can I tell if a surgeon is just a factory doctor versus someone who provides personalized care?
Is there a way to verify how many times a surgeon has performed a specific procedure like a Tommy John surgery?
What kind of post-operative support or physical therapy is usually included in the surgical package?
Why is my orthopedic surgeon recommending a partial knee replacement instead of a full one?
How do I know if my persistent elbow pain is tennis elbow or something that requires a specialist's intervention?
Are there specific orthopedic surgeons who specialize in minimally invasive spine procedures?
What are the signs that my hardware from a previous surgery might be failing?
Can I get a ballpark estimate for a bunion correction surgery including the facility fees?
How do I find an orthopedic surgeon who is comfortable working with patients who have high BMI?
What is the success rate for PRP injections versus traditional surgery for tendonitis?
Should I be worried if an orthopedic surgeon doesn't have any fellowship training in their sub-specialty?
Is it better to travel to a center of excellence for a complex revision surgery or stay local?
What are the common complications of a labral tear surgery that I should be aware of?
How do I prepare my house for recovery after a major orthopedic procedure like a hip replacement?

Model by model

21-point average divergence: which AI you ask changes the answer.

The divergence index is the average gap between the most and least likely model per behavior. Higher = the models disagree more about orthopedic surgeon buyers.

Behavior rates across 40 orthopedic surgeon buyer questions, 2026-07 edition. Last column: average across models.
ChatGPTClaudeGeminiConsensus
Recommends hiring a professional65%53%35%60%
Suggests DIY first15%10%10%90%
Names specific providers5%5%13%85%
Gives price or cost info8%10%13%93%
Tells to check reviews15%23%5%78%
Tells to verify credentials20%30%18%60%
Mentions case studies / portfolio8%3%0%90%
Mentions local proximity30%20%18%63%
Gives selection criteria45%50%35%45%
Warns about red flags20%18%5%75%
Asks a clarifying question70%78%0%8%
Recommends multiple quotes15%18%0%73%

By model

How each assistant handled Orthopedic Surgeon questions.

Reading the 120 answers model by model shows how differently the three assistants treat the same orthopedic surgeon questions. On the most consequential behavior — whether to send the buyer to a professional at all — the rate ranged from 65% (ChatGPT) down to 35% (Gemini), a 30-point gap on an identical question set.

Across the 40 orthopedic surgeon answers it produced, ChatGPT recommended hiring a professional in 65% of them and suggested a DIY approach first 15% of the time. It named a specific provider in 5% of answers (about 0.2 distinct providers per answer) and included price or cost information 7.5% of the time. ChatGPT asked a clarifying question before answering in 70% of cases, warned about red flags or scams in 20%, and told the buyer to verify credentials in 20%, averaging 492 words per answer. On the remaining cues it told the buyer to check reviews in 15%, pointed to case studies or a portfolio in 7.5%, and framed the choice around local proximity in 30%; a selection-criteria checklist appeared in 45% of its answers and a recommendation to gather multiple quotes in 15%.

Across the 40 orthopedic surgeon answers it produced, Claude recommended hiring a professional in 52.5% of them and suggested a DIY approach first 10% of the time. It named a specific provider in 5% of answers (about 0.2 distinct providers per answer) and included price or cost information 10% of the time. Claude asked a clarifying question before answering in 77.5% of cases, warned about red flags or scams in 17.5%, and told the buyer to verify credentials in 30%, averaging 294 words per answer. On the remaining cues it told the buyer to check reviews in 22.5%, pointed to case studies or a portfolio in 2.5%, and framed the choice around local proximity in 20%; a selection-criteria checklist appeared in 50% of its answers and a recommendation to gather multiple quotes in 17.5%.

Across the 40 orthopedic surgeon answers it produced, Gemini recommended hiring a professional in 35% of them and suggested a DIY approach first 10% of the time. It named a specific provider in 12.5% of answers (about 0.3 distinct providers per answer) and included price or cost information 12.5% of the time. Gemini asked a clarifying question before answering in 0% of cases, warned about red flags or scams in 5%, and told the buyer to verify credentials in 17.5%, averaging 269 words per answer. On the remaining cues it told the buyer to check reviews in 5%, pointed to case studies or a portfolio in 0%, and framed the choice around local proximity in 17.5%; a selection-criteria checklist appeared in 35% of its answers and a recommendation to gather multiple quotes in 0%.

Taken together, ChatGPT is the assistant most likely to route an orthopedic surgeon buyer to a professional (65%) and Gemini the least (35%). ChatGPT produced the longest answers, at 492 words on average. Specific providers were named most often by Gemini (12.5%) — even there, roughly one answer in 8 carried a name.

Where they disagree

The behaviors where the choice of model changes the answer.

The divergence index for this study is 21.3 points — the average distance between the most and least likely model across the coded behaviors. The gaps below are where which assistant an orthopedic surgeon buyer happens to ask matters most:

  • Asks a clarifying question: from 0% (Gemini) to 77.5% (Claude) — a 78-point spread.
  • Recommends hiring a professional: from 35% (Gemini) to 65% (ChatGPT) — a 30-point spread.
  • Tells the buyer to check reviews: from 5% (Gemini) to 22.5% (Claude) — a 18-point spread.
  • Recommends multiple quotes: from 0% (Gemini) to 17.5% (Claude) — a 18-point spread.
  • Gives selection criteria: from 35% (Gemini) to 50% (Claude) — a 15-point spread.

The widest single gap — asks a clarifying question, 78 points — means an orthopedic surgeon buyer can receive materially different guidance on the same question depending only on which assistant they happen to open, so any visibility strategy built on a single model's behavior describes only part of the orthopedic surgeon market.

Where they agree

The points of near-consensus in Orthopedic Surgeon.

On other behaviors the three models move almost in lockstep — the points of near-consensus for orthopedic surgeon, where all three landed within a few points of each other:

  • Suggests a DIY approach first: 10%–15% across all three (a 5-point spread).
  • Gives price or cost information: 7.5%–12.5% across all three (a 5-point spread).
  • Names a specific provider: 5%–12.5% across all three (a 8-point spread).
  • Mentions case studies or portfolio: 0%–7.5% across all three (a 8-point spread).

Measured question by question, the three assistants coded a response the same way most consistently on "gives price or cost information" (identical coding in 92.5% of questions) and least consistently on "asks a clarifying question" (7.5%).

Every behavior, measured

All twelve coded behaviors for Orthopedic Surgeon, averaged across the three models.

The behaviors AI models reproduce most often for orthopedic surgeon are recommends hiring a professional (50.8% on average), asks a clarifying question (49.2%) and gives selection criteria (43.3%); the rarest are mentions case studies or portfolio (3.3%), names a specific provider (7.5%) and gives price or cost information (10%). Each figure below is the share of a model's 40 answers in which the behavior appeared at least once, averaged across the 3 models with the full per-model range in parentheses:

  • Recommends hiring a professional: 50.8% on average (ChatGPT 65%, Claude 52.5%, Gemini 35%) — a 30-point spread.
  • Asks a clarifying question: 49.2% on average (ChatGPT 70%, Claude 77.5%, Gemini 0%) — a 78-point spread.
  • Gives selection criteria: 43.3% on average (ChatGPT 45%, Claude 50%, Gemini 35%) — a 15-point spread.
  • Tells the buyer to verify credentials: 22.5% on average (ChatGPT 20%, Claude 30%, Gemini 17.5%) — a 13-point spread.
  • Mentions local proximity: 22.5% on average (ChatGPT 30%, Claude 20%, Gemini 17.5%) — a 13-point spread.
  • Tells the buyer to check reviews: 14.2% on average (ChatGPT 15%, Claude 22.5%, Gemini 5%) — a 18-point spread.
  • Warns about red flags or scams: 14.2% on average (ChatGPT 20%, Claude 17.5%, Gemini 5%) — a 15-point spread.
  • Suggests a DIY approach first: 11.7% on average (ChatGPT 15%, Claude 10%, Gemini 10%) — a 5-point spread.
  • Recommends multiple quotes: 10.8% on average (ChatGPT 15%, Claude 17.5%, Gemini 0%) — a 18-point spread.
  • Gives price or cost information: 10% on average (ChatGPT 7.5%, Claude 10%, Gemini 12.5%) — a 5-point spread.
  • Names a specific provider: 7.5% on average (ChatGPT 5%, Claude 5%, Gemini 12.5%) — a 8-point spread.
  • Mentions case studies or portfolio: 3.3% on average (ChatGPT 7.5%, Claude 2.5%, Gemini 0%) — a 8-point spread.

Trust signals

How well the models protect the orthopedic surgeon buyer.

Beyond whether to hire, the rubric codes how carefully each assistant protects the orthopedic surgeon buyer once a decision is made. Telling the buyer to check reviews or ratings appeared in 14.2% of answers on average. Verifying credentials or certifications appeared in 22.5%. Warning about red flags or scams appeared in 14.2%.

On structuring the decision, a selection-criteria checklist showed up in 43.3% of answers on average and a recommendation to gather multiple quotes in 10.8%. The single least-reproduced protective signal for orthopedic surgeon is "recommends multiple quotes" at 10.8% on average — the clearest opening for content that supplies it, since the models are not yet reliably surfacing that guidance on their own.

Referral behavior

Do AI models name Orthopedic Surgeon providers?

For service providers the decisive question is whether these systems name anyone at all. Across 120 orthopedic surgeon answers, a specific provider was named in 7.5% of responses on average — roughly 0.2 distinct providers per answer. In practice the assistants behave far more as an explanatory layer than as a referral engine for orthopedic surgeon: visibility comes from being the reasoning a model reproduces, not from being the named recommendation.

The question set

What these 40 Orthopedic Surgeon questions cover.

The 40 questions behind every percentage on this page were drawn from real orthopedic surgeon (healthcare services; buyer hiring decisions for this specific service) buyer journeys. Each was put to all 3 models once, with identical wording, so the rates above describe how the assistants handled this exact orthopedic surgeon question set — not a general prior or a hand-picked subset. The full list is shown earlier on this page; the coded percentages are what those specific questions produced.

How to read this

A note on the numbers.

A percentage here is the share of a model's 40 answers in which the behavior appeared at least once — not a confidence score. Because each model answered every question exactly once on 2026-07-06, the figures describe this specific orthopedic surgeon question set and snapshot rather than a general prior. The full protocol and coding rubric are documented in the study methodology.

Methodology

A controlled snapshot, documented end to end.

40 standardized buyer questions per industry, one response per model per question (ChatGPT (gpt-5-mini), Claude (claude-sonnet-5), Gemini (gemini-3-flash-preview)), collected 2026-07-06, coded against a fixed 12-behavior rubric with human QA. AI outputs vary with model version, location and time — figures describe this sample and window, and are refreshed each edition. Read the full methodology →