BUYER’S GUIDE · HEALTHCARE

How to choose a healthcare AI automation partner

Reviewed by Mohammed Affaan Khan, GenAI & Agentic AI Engineer · Updated October 2026

In short: Choose a healthcare AI workflow automation partner on five things: whether they sign a business associate agreement and build to HIPAA (or the UK and EU equivalents), whether they integrate with your EHR — Epic, Oracle Health (Cerner) or others — over FHIR and HL7 rather than screen-scraping, whether clinicians sign off anything with clinical consequence, whether every automated step is auditable, and whether they have shipped in a clinical setting before. This guide is a checklist for teams choosing a partner, based on the questions buyers ask us.

What to evaluate

• HIPAA and the business associate agreement

  A vendor that touches PHI signs a BAA, and so does every sub-processor it relies on — model and hosting providers included. Ask for that list. In the UK the equivalents are UK GDPR and the NHS Data Security and Protection Toolkit; in the EU, GDPR.

• EHR integration done properly

  FHIR R4 APIs where the EHR offers them, HL7 v2 feeds where it does not. For Epic and Oracle Health, ask whether they have worked through the vendor’s developer programme. Screen-scraping a clinical system is a warning, not an integration.

• A clinician in the loop

  Automation should prepare, route and chase. Anything with clinical consequence goes to a clinician for sign-off, with the reasoning shown so the approval means something.

• An audit trail you can export

  Every automated action logged with its inputs, outputs and who approved it — what a compliance review or an incident investigation will ask for first.

• Prebuilt versus custom

  Platforms with prebuilt healthcare agents are faster for standard workflows; custom builds fit unusual workflows and integrations. Ask which parts are configured and which are built — and who owns what is built.

• A clinical track record

  A deployment in a real clinical setting with measured results and a reference — not a pilot that stopped at the demo.

Red flags

• !No BAA, or vague answers about which providers see patient data
• !Integration by screen-scraping the EHR
• !Automated steps that write to the record with no human able to override
• !No audit log you can export
• !Accuracy claimed from another organisation’s data and never validated on yours

Where Midalaxy stands

For transparency: this guide is written by Midalaxy — weigh it as one vendor’s view. Our clinical platform, used in the NHS ecosystem, combines role-based clinical workflows with automated reporting that took reporting time from about 30 minutes to about 5, and logs every automated decision. We publish no prices: tell us the workflow, your EHR and your budget, and we will say what it takes.

Questions

• What is healthcare AI workflow automation?

  Software that runs the administrative steps around care — referral triage, patient intake, prior-authorisation chasing, reminders, report drafting — as supervised workflows against the EHR, with a clinician signing off anything clinical and every step logged.

• Which healthcare workflows are worth automating first?

  The ones with high volume and clear rules: appointment reminders and rescheduling, referral triage, patient intake and prior-authorisation follow-up. Start with one, run it alongside the manual process, and measure it for a few weeks.

• Can it integrate with Epic or Oracle Health (Cerner)?

  Usually, through their FHIR APIs and developer programmes, or HL7 interfaces where those are what the hospital exposes. Where there is no write access, the workflow prepares the update and a member of staff commits it.

• What does HIPAA require from an automation vendor?

  A business associate agreement, the minimum access each workflow needs, encryption in transit and at rest, BAAs with its own sub-processors, and an audit trail of automated actions. No tool is compliant on its own; the build has to be.

• How do we know whether it worked?

  Measure it against the baseline: referral-to-triage time, admin minutes per patient, no-show rate, prior-authorisation turnaround, and how often staff override the automation. A rising override rate means the design is wrong.