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Data Migrations & Mapping Solutions for eClinicalWorks
Data migrations are more than moving files from Point A to Point B—they’re about protecting clinical integrity, maintaining operational continuity, and ensuring your team can actually find and use the data once it lands in eClinicalWorks. Our data migration and mapping services help practices transition from legacy systems or consolidate multiple sources into eCW with clear field mapping, validated imports, and documented rules. Whether you’re migrating demographics, insurance, appointment history, balances, clinical documents, labs, or custom data fields, we focus on accuracy, traceability, and minimal disruption.
We start by defining what should migrate (and what shouldn’t), mapping fields to eCW structures, and establishing naming conventions so imported data is consistent and searchable. Then we run test loads, validate counts and key records, identify gaps early, and refine mapping before go-live. The result is a cleaner eCW environment, fewer surprises after launch, and a smoother experience for staff and patients.
Benefits
Frequently Asked Questions
What types of data can you migrate into eCW?
Common migrations include patient demographics, insurance, appointments, balances, clinical documents, problem lists, medications, allergies, immunizations, and selected historical clinical data—depending on source system limitations and eCW import options.
What does "data mapping" mean?
Common migrations include patient demographics, insurance, appointments, balances, clinical documents, problem lists, medications, allergies, immunizations, and selected historical clinical data—depending on source system limitations and eCW import options.
How do you prevent data loss or mismatches?
We use a test-first approach: sample loads, record counts, spot checks, and validation against source exports. We also document rules and confirm definitions before final import.
Will we need to clean up our data before migrating?
Usually, yes—at least some. We can guide you on what to clean (duplicates, outdated insurers, inconsistent formats) and what can be standardized during the mapping process.
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