EHR Migrations
When a healthcare organization switches EHRs, the biggest blocker isn't the new platform — it's the old one.
The Challenge
EHR migrations are notoriously painful because patient data is often trapped behind:
Limited exports
Lack of APIs
Costly extraction fees charged by legacy EHR vendors
Proprietary data formats that differ between source and destination systems
"Information blocking" patterns that make retrieval slow and manual
For EHR vendors onboarding new customers, this creates a growth constraint: migrations can take weeks, engineers get pulled away from high-value product work to handle manual point-and-click retrieval, and customers start their "new EHR experience" with frustration instead of momentum.
The Solution
A browser-based workflow that extracts and packages patient data end-to-end
Secure login + patient list access
The workflow begins with customer-provided access (URL + credentials) to the legacy EHR environment. From there, XY navigates to the patient list and begins processing records systematically.
Extract documents and relevant patient data at scale
XY loops through each patient record and retrieves attached documents, record details required for continuity of care, and key patient history artifacts needed for onboarding.
Store and package the migration output for handoff
Extracted data is collected and organized as structured data inside the XY workflow pipeline, then delivered via chosen method (API, file share, Browser Agent) so the structured data can be ingested into the new EHR cleanly.
Support multiple legacy EHR "flavors" with reusable workflows
XY addresses different legacy EHR UIs with reusable browser workflows that can be created from an FTE walkthrough/recording, reused when the same legacy system appears again, and extended into a multiplexed pipeline.
Why It Matters
This workflow transforms migrations from a weeks-long grind into a background process that can run in hours or days. In one real-world scenario, a parallelized XY workflow reduced what would have been an estimated year of a single human working around the clock — and likely longer given that humans work slower than automated agents — down to less than a week of migration time. EHR vendors onboard customers faster, teams avoid throwing headcount at migration work, and new customers start with their data already in place.