What does secure AI in healthcare take?
AI can give clinicians more time with the patient. But in healthcare you must also be able to show where patient data is, who has accessed it and who is responsible for the text.
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After a visit, there is often a stretch at the computer. The clinical note has to be written, perhaps a referral or a sick note too. It is necessary work, but it takes time from the next patient. This is where AI can make a real difference. The doctor dictates their notes and gets a first draft to review, instead of starting from a blank page.
At the same time, few environments are more demanding. Patient data is covered by strict legislation, and patients must be able to count on their records being read only by those who need them for their care. So the question is not whether AI can help in healthcare. It is what needs to be in place for it to be safe.
Patient data stays where it belongs
Everything starts with where the data is processed. When an AI service sends clinical text to an external supplier, questions arise about data processors, transfers and confidentiality that can take months to resolve. Sometimes there is no good answer at all.
The simplest answer is to run the whole chain in the care provider’s own environment, the language model included. Patient data then never leaves the organisation, and no outside party needs to see it. That makes the assessment easier for lawyers and security staff alike, and it makes it easier to explain to patients how their data is handled.
Just as important, the data is not used for anything else. A secure solution uses the clinical text to produce the draft, and nothing more. It trains no models on patients’ data.
People review and remain responsible
AI in healthcare is support, never a substitute for clinical judgement. A draft clinical note is exactly that, a draft. The person who saw the patient reads it, adjusts it and makes the call, and responsibility stays where it has always been.
That needs to show in the workflow. A good tool makes review easy and never suggests that a draft is finished. The same goes when staff ask about a routine. The answer should be based on the organisation’s own, current documents and show which documents it came from. A nurse wondering how a particular sample should be taken should be able to open the routine and see for herself. An answer without a source has to be taken on trust, and in healthcare that is not enough.
There is another benefit. When everyone gets answers from the same routines, a new colleague gets the same guidance as someone with twenty years on the ward.
What this looks like in an ordinary working day is described in the article on AI for primary care.
The right people see the right data
In healthcare, not everyone has access to everything, and an AI solution must follow the same principle as other systems. Staff sign in with the account they already have, with two-step verification. Their role decides what each person can see and do. Changes to roles or retention periods, for example, should require approval from a second person, so nobody can open up more than intended on their own.
It must also be possible to see afterwards who did what. An audit log that cannot be altered without it showing, and that connects to the security monitoring already in place, makes AI support part of normal follow-up instead of a new blind spot. Encryption in transit and at rest is the obvious foundation.
How it works in iSearch
iSearch is used in healthcare today. The doctor dictates after the visit, and the assistant drafts the clinical note and referral from the organisation’s own templates. The doctor reviews and remains responsible for the text. Staff can also get answers in their daily work, straight from the organisation’s routines.
The whole chain in iSearch can run in your own environment, so patient data does not leave it, and fully isolated with an air gap when required. Every customer gets a separate installation of its own. SSO, MFA, role-based access, the four-eyes principle and a tamper-evident audit log are included. Every answer shows which documents were read, and your data is never used to train models.
See how iSearch is used in healthcare, read more about security or book a walkthrough.
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