How to Plan an EHR Migration Without Disrupting Patient Care

Migrating patient records between EHR systems is one of the highest-stakes projects a healthcare software team can take on. Get it wrong and you’re not just dealing with a broken feature, you’re dealing with clinicians who can’t access a patient’s history, compliance exposure, and trust that’s hard to rebuild.

I was part of the team that migrated 60,000+ patients from AthenaHealth to Healthie for Brave Health, a virtual therapy and psychiatry provider, with zero compliance gaps. Here’s the playbook that made that possible.

The real risk isn’t the data move

It’s tempting to treat an EHR migration as a data engineering problem: extract records, transform them to fit the new schema, load them into the destination system. That part matters, but it’s not where migrations actually fail.

They fail when:

• A clinician logs in on cutover day and can’t find a patient’s medication history
• A field maps cleanly in testing but loses meaning in production (a “status” field that meant one thing in the old system and something subtly different in the new one)
• Nobody validated data integrity end-to-end before the old system got decommissioned
• Compliance sign-off happened after the technical work was done, instead of alongside it

The technical migration is necessary but not sufficient. What actually protects patient care is the process around it.

A phased approach that holds up under pressure

1. Discovery and mapping, done with clinicians in the room. Before writing any migration code, map every field, every workflow, and every edge case with the people who actually use the system daily, not just the ones who requested the migration. The gaps between how a system is “supposed” to work and how it’s actually used in practice are exactly where migrations break.

2. Parallel-run validation. Run the new system alongside the old one before cutover, with real (or shadowed) data, and reconcile the two continuously. This is where you catch the field-mapping issues that look fine in a spec but produce wrong results with real-world data.

3. Phased cutover, not a big bang. Migrate in cohorts, not all at once. Start with a low-risk subset, validate thoroughly, then expand. If something breaks, it breaks for a fraction of your patient population, not all of it.

4. HIPAA compliance as a continuous checkpoint, not a final gate. Compliance review needs to happen at every phase, not as a sign-off at the end. By the time you’re at cutover, there should be no compliance surprises left to find, because you’ve already found and resolved them earlier.

5. Post-migration monitoring with a real rollback plan. Cutover isn’t the finish line. Keep the old system accessible and monitor closely for the first weeks after migration, with a concrete plan for what happens if something needs to be rolled back.

The result

Zero compliance gaps, and a migration that clinicians didn’t have to think about because it just worked. That’s the actual measure of success for a project like this: not that the data moved, but that patient care never noticed.

If you’re planning something similar, the single highest-leverage thing you can do is get compliance and clinical stakeholders involved from day one, not brought in to review a plan that’s already been decided.