Not All Healthcare AI Is Created Equal. Check What's Running Under the Hood
Healthcare technology vendors are racing to add AI to their products. Some were built for healthcare from the ground up. Others were built for everyday consumers, then tweaked for healthcare later. Before you sign anything, look under the hood. The model powering the AI matters more than a flashy demo.
Healthcare AI Is Everywhere. Check at What's Underneath.
New AI-powered tools are hitting the healthcare market almost daily. The demos look polished. The decks promise time savings and automation. Most of them look the same at first glance. They are not.
What separates them is what's underneath: the AI model, how it handles patient data, and what compliance commitments actually back it up. None of that shows up in a demo.
Before your organization evaluates another healthcare software vendor, ask this question: What AI model are you running, and what happens to our patients' data under HIPAA?
The answer tells you most of what you need to know.
The Model Matters More Than the Demo
Most healthcare operators are not AI researchers, and they should not have to be. But the AI model a vendor chose is important. It determines not only how well it works for your team, but also how your patients' data is handled, who can access it, and what happens to it after your staff hits submit.
Three things worth knowing:
Not every AI provider is covered by a Business Associate Agreement (BAA). A BAA is the contract HIPAA requires any time a company handles protected health information on your behalf. Some AI providers only offer one on enterprise plans. Others do not publish a compliance statement at all. If a vendor cannot tell you whether the AI handling your data is covered by a BAA, that exposure can flow back to your organization.
Some setups use your data to improve the model. What you send can be retained and used to train future versions, depending on how the model is configured. In healthcare, that means clinical notes and patient information could be used in ways you never agreed to. The questions to ask: is our data used for training, and is the answer in writing?
A model built for regulated work runs differently than one built for general use. Different data terms, different controls, different oversight. When AI is informing an admissions decision rather than drafting an email, that difference matters.
A lot of the new software hitting this market is running on consumer-grade AI: The household name, not the one designed for healthcare enterprises. That is worth knowing before you sign anything.
How Olio Answered Its Own Questions
Olio holds itself to the same standard. Here is how we answer each question.
Olio uses Anthropic's Claude to power its AI-assisted admissions and summarization features. That was a deliberate choice. Our engineering team evaluated multiple providers against the criteria that matter in healthcare: how patient data is handled, the model's safety design, independent certifications, and performance on the documents we actually work with.
The model was only half of the decision. Data protection is the other half.
User data stays inside an environment Olio controls. Patient data reaches the model through AWS Bedrock, Amazon's enterprise AI service, inside an isolated AWS account under a BAA (Business Associate Agreement). Put more plainly, user data is not used to train any model and is not retained after the request. Anthropic, the company that makes Claude, never even receives it.
Safety is built into the model, not added on top. Anthropic trains Claude against a published set of safety principles and holds ISO 42001, the international standard for responsible AI management. An outside body audits how they build and govern the model.
It can handle the documents SNFs actually deals with. Referral packets run dozens of pages: physician notes, medication lists, diagnoses, insurance records. Reliable summarization of that is hard. It takes a model designed for the work.
Five Questions to Ask Any Healthcare AI Vendor
Start here, not with the demo.
Who is your underlying AI provider? Get specifics. Model name and provider. Vague answers are a signal.
Is every path your data travels to reach the AI covered by a signed BAA? Not just the application vendor. Trace it all the way to whoever processes the data.
Is our data retained or used to train the model, and is that in writing? "We don't think so" is not an answer.
Where does the model run, and who controls that environment? A model running inside the vendor's own isolated environment is a different risk than prompts sent to a public API.
What independent certifications does the vendor hold? Self-attested HIPAA compliance is a vendor grading its own homework. It is not the same as a third-party audit like HITRUST CSF r2 or SOC 2 Type II.
What This Looks Like at Olio
Olio is a care coordination platform. Our admissions workflow is where AI does the most for care teams. A referral packet that runs dozens of pages becomes a structured summary your team can act on, with every claim cited back to its source document. A reviewer can verify any line in one click.
AI can be wrong. So we do not just trust the output. Automated checks compare it against clinical expectations, and clinically trained reviewers step in when something looks off.
Traceable, governed, and verified by an outside party. Olio is HITRUST CSF R2 certified.
Take these five questions to your next vendor meeting. Ask Olio too. We will answer all five in writing and show you the architecture behind them.
Questions about Olio's AI or security? Contact security@olio.health.
