"We use ChatGPT." "Claude writes better, apparently." "Gemini is free." Service names circulate freely in AI conversations.
But for a clinic deciding which to use, the deciding factor is not a capability comparison. This article organizes the differences and then sets out the selection criteria specific to healthcare.
Disclaimer: This article provides general information. Features, pricing, and contract terms change frequently. Always confirm each provider's current official information and terms of service.
The Three Services
| Service | Provider | Commonly cited characteristics |
|---|---|---|
| ChatGPT | OpenAI | The most widely known, with the largest user base and surrounding ecosystem |
| Claude | Anthropic | Regarded for handling long text and for writing quality; emphasis on safety design |
| Gemini | Integration with Google's services; affinity with search |
All three are conversational AI services built on LLMs. What they fundamentally do—write, summarize, translate, answer—is common across them.
Critically, each provider releases new models at a rapid pace, and rankings of "which is best" change within months. Choosing on the basis of a point-in-time comparison means your reasoning goes stale quickly.
The Criteria Are Not About Capability
Handling medical information sets the priorities.
1. Whether your input is used for training (highest priority)
Free consumer services may default to using your input for service improvement. Entering patient information under those conditions can amount to disclosing it externally.
For corporate and API-based use, all three providers commonly treat input as not used for training. But terms differ by plan—verify it contractually.
Confirm: that input is not used to train or improve models, the retention period and location, and whether third-party disclosure occurs.
2. Contract tier and scope of responsibility
| Tier | Overview | Suitability for healthcare |
|---|---|---|
| Free consumer | Immediately usable by anyone | Patient information must not be entered; limit to general internal work |
| Paid consumer | Expanded features | Contracted by an individual; hard to govern institutionally |
| Corporate | Contracted and managed at the organization level | Training exclusion and admin controls; a strong option |
| Via API | Embedded in your own systems | Enables EMR integration; realistically through a vendor |
The first practical step is not leaving staff to use personal accounts. You cannot see who is using what, nor manage the risk of patient information being entered.
3. Alignment with the three-ministry guidelines
Passing information to an external AI service requires confirming alignment with the guidelines' thinking. See The Three-Ministry Guidelines Explained and Practical Steps for Compliance.
4. Whether it integrates with existing systems
Pasting into a chat window and running inside the EMR differ enormously in practical value.
In a chat window: copy from the chart, paste into the AI, copy the result back. The round trip is itself the burden, and the copying introduces risk of mixing up information.
Embedded in the system: the draft appears with the chart still open. No round trip.
This is exactly the bolted-on versus built-in distinction in What Is an AI-Native Electronic Medical Record?.
5. Cost structure
Consumer plans are typically flat monthly rates. API use is generally metered by volume processed (tokens). Where AI is embedded in a healthcare product, it is usually included in that product's pricing—with the benefit that you need not track which AI is underneath.
Selection Checklist
| Item | What to confirm |
|---|---|
| Training use | Is exclusion from training contractual? |
| Data retention | Where, and for how long? |
| Contracting party | Not a personal contract? Governable institutionally? |
| Guidelines | Aligned with the three-ministry guidelines? |
| Integration | Usable directly from the EMR, or copy-paste only? |
| Permissions | Who may use it? Are records kept? |
| Cost | Flat or metered? Estimate at expected volume |
| Patient information | Has the clinic defined what may not be entered? |
A Practical Split—Think in Two Tiers
Tier 1: work without patient information → general AI services
Drafting internal manuals, job postings, training material outlines, checking general medical knowledge (always confirm finally against primary sources).
Here the choice is largely preference. Free plans rarely obstruct the work; try a few and pick what suits.
Tier 2: work involving patient information → systems designed for healthcare
Chart documentation, referrals and certificates, billing verification, patient data analysis.
Here the principle is that pasting patient information into a general chat service is not among the options. Use systems designed for medical information, with contracts and permissions in place.
See also ChatGPT for Physicians on general versus healthcare-specific AI.
Common Misconceptions
"A paid plan makes patient information safe." Training use and retention differ by plan. Paid and suitable-for-medical-information are different things.
"AI doesn't make mistakes, so verification is unnecessary." Hallucination is unavoidable by design.
"We must standardize on one." Using different services for different purposes is fine—the two-tier split is more realistic.
"Pick the highest-performing one." For providers, contract terms and integration drive daily value far more; performance rankings turn over quickly.
Decide Clinic Policy First
More important than choosing a service is deciding your internal rules. At minimum, document:
- Never enter patient-identifying information (names, dates of birth, addresses, contacts, chart numbers)
- The scope of work where AI may be used
- Which services are approved (preventing unsanctioned personal accounts)
- AI output is a draft; a human verifies and finalizes
- Who to ask when unsure
The most dangerous state is "we use it because it's convenient" with no rules. Conversely, rules clarify where AI can be used confidently—which is what lets adoption progress.
Conclusion
- ChatGPT, Claude, and Gemini come from different companies but do fundamentally similar things
- Rapid model releases mean capability rankings turn over quickly; choosing on them dates your reasoning
- The criteria are training use, contract tier, guideline alignment, integration, and cost structure
- The top priority is whether input is used for training; never enter patient information into a free consumer plan
- The realistic pattern is two tiers—general services without patient information, healthcare systems with it
- Document clinic policy before selecting a service
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