This article covers practice management systems, ambulatory and specialty EHRs and related tools sold to independent practices. For large hospital and health system buying, read our guide for healthcare software sold to health systems. Companies selling to dental offices should read how dental technology makes a dentist’s shortlist.
The short version
- The market is replacement-driven: 95% of US office-based physicians had adopted an EHR by 2024, and 91% a certified one, according to the federal health IT office (ASTP/ONC) (opens in a new tab).
- Switching is common: in a March 2025 MGMA Stat poll (opens in a new tab) of 455 practice leaders, 23% expected to switch or significantly update their EHR within 12 months.
- The independent buyer is shrinking but still large: the American Medical Association (opens in a new tab) found 42.2% of physicians worked in private practice in 2024, down from 60.1% in 2012, and 47.4% in practices of 10 or fewer physicians.
- Physicians are heavy AI users: 81% used AI professionally (opens in a new tab) in the AMA’s 2026 survey, and 68% of medical groups added or expanded AI tools in 2025, per MGMA (opens in a new tab).
- Trust must be earned with evidence: in Black Book’s 2025 survey (opens in a new tab) of 755 practice managers, only 19% trusted the AI prompts in their current systems, and 44% would be more likely to adopt AI decision support with transparent evidence trails.
Who buys software for an independent practice, and what is a customer worth?
A physician owner and a practice administrator, usually together, with the billing lead holding an informal veto.
In a small or specialty practice, the person who signs is often a physician owner, but the person who runs the evaluation is the practice manager or administrator, and the person who lives with the result is the billing lead. In the AMA’s 2024 benchmark survey, 35.4% of physicians had an ownership stake in their practice, and single-specialty practices employed 37% of physicians, more than multi-specialty practices (27.8%). The same survey shows ownership is shifting: 38% of physicians in private equity owned practices said those practices were acquired in the past five years, which brings management service organizations into many buying decisions. Hospitals and health systems buy through a different process, covered in our guide for healthcare software sold to health systems.
What a customer is worth depends on the sales model, and the two common models look very different:
| Model | Real example | How price is set |
|---|---|---|
| Self-serve trial | SimplePractice (opens in a new tab) for solo practitioners | Published plans at $49, $79 and $99 a month, with a free trial that can run to 30 days |
| Demo-led quote | Tebra (opens in a new tab) for independent practices | Licensed per prescribing provider; Tebra says “pricing is typically tailored during the demo process” |
In both models, the account is sticky. Moving clinical records, templates, claims history and staff habits is painful, so a won practice usually stays for years. We found no public benchmark for the lifetime value of a practice software customer and will not invent one. Our inference is that every won practice is worth several years of per-provider fees plus add-ons such as billing services, patient engagement and AI documentation.
Where do AI assistants sit in a practice’s software search?
Probably near the start, since buyers already use AI daily, though direct evidence on vendor research is missing.
The adjacent evidence is strong. The AMA’s 2026 survey found 81% of physicians use AI in a professional context, more than double the 2023 rate, and 39% use it for summaries of research and standards of care. The Doximity 2026 report cited by MGMA (opens in a new tab) found ambient documentation adoption rose from 20% to 29% of physicians surveyed in a year. Practice leaders are buying AI, too: MGMA reports 68% of medical groups added or expanded AI tools in 2025.
Across all B2B software, G2’s 2026 buyer research (opens in a new tab) found 51% of buyers now start their research with an AI chatbot more often than with Google. G2 did not break out healthcare practices, and we found no survey that asks practice managers how they research vendors. Our inference: a practice administrator comparing systems is likely to ask an assistant the same questions they would ask a peer, and the answer shapes which three vendors get a demo.
What do practice owners and managers ask before they book a demo?
Specialty fit, billing and clearinghouse integration, certification, pricing, switching effort and what peers say.
We wrote the practice-manager and physician prompts below ourselves to show how buying questions tend to be phrased; none was captured from a real user.
| Stage | Illustrative prompt |
|---|---|
| Specialty fit | “Best dermatology EHR for a three-provider practice with a cosmetic side” |
| Switching | “Alternatives to our current EHR that can migrate charts and claims history” |
| Integration | “Practice management software that works with our clearinghouse and lab” |
| Certification | “Is this EHR on the ONC certified list for MIPS reporting?” |
| Price | “How much does an ophthalmology EHR cost per provider per month?” |
| AI features | “Which EHRs include an ambient AI scribe, and what does it cost extra?” |
| Peer proof | “What do billing managers say about this system’s denial management?” |
Some of these answers are easy to get wrong. Vendor names change after mergers: Tebra’s own pricing page notes that “Kareo is now part of Tebra.” An assistant that learned about the market before a rename may describe a product that no longer exists under that name. We explain why that happens in why ChatGPT misses new products.
How does an AI answer become a signed practice?
Through a shortlist, a demo or trial, a quote and a migration plan, usually over weeks rather than months.
- Trigger. A practice opens a new location, joins a management services organization, loses patience with a billing system or wants an AI scribe. MGMA’s respondents planning a change mostly said they were moving to a new vendor rather than upgrading.
- Shortlist. The manager asks peers, checks KLAS or Black Book ratings, reads reviews and, we infer, increasingly asks an assistant. Vendors not named here rarely get a demo.
- Demo or trial. Self-serve products convert through a trial; quote-based products through a demo where the price is set.
- Proof. The practice checks references, certification, integrations and the contract. In Black Book’s survey, 17% of managers said they would replace their EHR or practice management platform with a vendor that guaranteed real-time FHIR-based data exchange.
- Contract and migration. The practice signs per provider, and the revenue repeats for years.
Pricing is a weak point in step two. In our pricing accuracy study across 45 software products, 61.9% of plan prices quoted by AI assistants were fully faithful to the official page. When prices differed, the figure often came from somewhere else on the vendor’s own site: for 39 of 64 differing prices, the same number appeared on another vendor page. For quote-based vendors, our inference is that a page explaining how pricing works (per provider, what is included, what costs extra) is the best defense against a wrong number.
What decides which medical software vendor an assistant names?
Independent evidence of specialty fit and customer satisfaction; the platforms do not publish their selection rules.
What is documented: Google says (opens in a new tab) SEO best practices remain relevant for AI Overviews and AI Mode, with no additional requirements or special optimizations needed to appear.
What has been observed:
- Answers vary. In our consistency study, only 25.2% of the brands ChatGPT named appeared in all five repeats of the same question. One check of “best EHR for my specialty” proves little.
- Mention matters to B2B buyers. In G2’s research, 85% of buyers said they think more highly of a vendor when AI includes it in an answer. That is a buyer survey across software, not a test of what assistants do.
What we infer, based on how practices already judge vendors: the evidence an assistant can find is the same evidence a practice manager trusts. That includes:
- Independent ratings. KLAS (opens in a new tab) named athenahealth the Overall Independent Physician Practice Suite for a third consecutive year in 2026, and Greenway Health the most improved physician practice product after a 24% rise in satisfaction among its revenue cycle clients. Black Book’s 2025 ratings named ModMed for OB/GYN and NextGen Healthcare for practice management.
- Certification and compliance. Certified EHR status, a signed business associate agreement and interoperability readiness, stated plainly.
- Specialty depth. Templates, imaging, devices and workflows for the specialty, described on pages an assistant can read.
- Transparent AI. Black Book found 44% of managers would be more likely to adopt AI decision support if vendors showed the data source, logic and limits behind each recommendation. The same openness on your website gives an assistant something accurate to repeat.
What does a medical software vendor lose when it is missing from AI answers?
A place on the shortlist during a switching window that may not reopen for years.
We have no direct measurement of deals lost to AI absence, so we label the reasoning. With 23% of medical groups planning to switch or overhaul their EHR in a year, the window is real but brief for any one practice. A vendor left off the shortlist loses that practice until the next switch, and a demo-led vendor loses the chance to set the price in a conversation. A vendor described with an old name, an old price or a feature it no longer offers may be shortlisted for the wrong reasons and lost in the demo. If an assistant still describes your old pricing or a retired feature, the steps for fixing wrong brand information in AI answers apply.
How does generative engine optimization work for practice software?
Generative engine optimization (GEO) makes your product easy for assistants to find, describe accurately and verify through outside evidence.
For a vendor selling to independent practices and specialty clinics, the work usually covers:
- One consistent identity. The same product names, specialties served and practice sizes across your site, KLAS and Black Book profiles, review sites, marketplaces and partner pages, especially after a merger or rename.
- A page per specialty. What the system does for dermatology, orthopedics, ophthalmology or behavioral health: templates, imaging, devices, billing codes and workflows, in text rather than only in videos. Dental offices are a separate market, covered in how dental technology makes a dentist’s shortlist.
- Pricing logic in writing. Published plans, or a clear explanation of how quotes are built: per provider or per user, what is included, implementation fees and add-ons.
- Proof of certification and integration. Certified status with a link to the ONC Certified Health IT Product List (opens in a new tab), named clearinghouse, lab and imaging integrations, and a plain statement on business associate agreements.
- Switching guides. Honest migration pages for practices leaving common systems: what moves, how long it takes and what it costs. Fair comparison pages also help; see whether comparison pages help B2B AI citations.
- Independent coverage and reviews. KLAS and Black Book participation, specialty society and MGMA presence, case studies with named practices, and reviews from billing managers as well as physicians.
- Measurement. Ask a fixed set of illustrative specialty, switching, pricing and certification questions across ChatGPT, Gemini, Perplexity and Google’s AI features, repeatedly, and track who is named and which sources are cited.
No vendor can be promised a place on an assistant’s shortlist, and anyone who promises one is overselling. What this work does is make your product the easiest one for an assistant to describe correctly to a practice that is ready to switch.
What don’t we know yet about how practices choose software with AI?
How often practice managers ask assistants about vendors, and whether AI-sourced demos close at different rates.
- No direct survey. The AMA, Doximity and MGMA measure clinical and operational AI use, not vendor research. G2’s figures cover B2B software buyers in general.
- Self-reported data. MGMA Stat polls and Black Book surveys rely on what respondents say, and Black Book also publishes vendor ratings.
- No tests on medical software queries. Our consistency and pricing studies used other categories and products. Applying them here is our inference.
- Platforms change. Assistants update their search and answer features often, and none publishes how it chooses vendors.
Where should a practice software company start?
Start with the questions a switching practice in your specialty would ask, then see who assistants name and why.
That first check usually shows whether your product is named for the specialties and practice sizes you serve, whether your name, pricing and certification are described correctly, which ratings and reviews shape the answer and which competitors appear instead. From there, the work is to publish the specialty, pricing and integration proof that a practice manager would want and to keep it consistent everywhere.
If your growth depends on demo requests and trials from independent practices, ask us to map your visibility in AI answers. We will show where your product appears for specialty and switching questions, why competitors are named instead, and which changes are most likely to bring more qualified practices to your demo calendar. What the follow-on work involves, from specialty pages to pricing logic and switching guides, is described on our generative engine optimization service page.
Frequently asked questions
Do practice managers use ChatGPT to choose an EHR?
No survey we found measures it directly. Physicians are heavy AI users, 81% in the AMA’s 2026 survey, and G2 found 51% of B2B software buyers start research with an AI chatbot.
Should we publish our prices if we sell through demos?
Publishing at least the pricing logic helps. In our study, AI assistants quoted software prices fully faithfully 61.9% of the time, and many errors came from other pages on vendors’ own sites.
Do Best in KLAS awards affect AI answers?
No study shows that directly. We infer that independent ratings help, because they are the evidence practices already trust and they appear on pages assistants can read.
Is this different from selling to health systems?
Yes. Independent practices buy faster, with smaller committees and per-provider pricing, and often through trials. Health systems buy through long, committee-led evaluations tied to their main EHR.
Sources
- ASTP/ONC (2024), Office-based Physician Electronic Health Record Adoption (opens in a new tab)
- MGMA (2025-03-19), Building a robust RFI process and RFP for a new EHR system (opens in a new tab)
- Medical Economics (2025-05-29), AMA: Physician private practice unraveling due to low payment, high costs, administrative burdens (opens in a new tab)
- Fierce Healthcare (2026), AMA: Physicians’ use of AI doubled from 2023 to 2026 (opens in a new tab)
- MGMA (2025), Document, schedule, communicate: AI tools (opens in a new tab)
- MGMA (2026-05), Are AI tools making clinicians more productive? It’s complicated (opens in a new tab)
- Black Book Research (2025-09-26), Physician Practice IT at a Crossroads (opens in a new tab)
- KLAS Research (2026-02-04), Epic, athenahealth, Chartis, Optimum Healthcare IT and Impact Advisors win 2026 Overall Best in KLAS Awards (opens in a new tab)
- SimplePractice (2026), SimplePractice EHR Pricing and Plans (opens in a new tab)
- Tebra (2026), Tebra Pricing: Software Plans for Private Practices (opens in a new tab)
- G2 (2026-04-15), In the Answer Economy, Don’t Win the Click — Win the Answer (opens in a new tab)
- ASTP/ONC (n.d.), About the ONC Health IT Certification Program (opens in a new tab)
- Google Search Central (2025), AI features and your website (opens in a new tab)
- Underneath (2026), How faithfully do AI assistants quote software prices?
- Underneath (2026), Ask an AI the same question 5 times: do the brands change?