The ChartPath Blog

The Complete EHR Data Migration Checklist: Before, During, and After Your Transition

Written by Cortney Swartwood | Feb 20, 2026 1:17:03 PM

EHR data migration is one of the most critical (and risky) projects a healthcare organization can undertake. Patient histories, clinical documentation, scheduling data, billing information, and compliance records must transfer accurately and securely from one system to another. Any gaps can disrupt care, interrupt workflows, or create long-term data integrity issues.

Whether your organization is moving to a modern EHR for interoperability, scaling operations, or replacing legacy technology, having a structured plan is essential. This guide walks through a comprehensive checklist for each stage of the migration process: pre-migration planning, execution, and post-migration validation.

Before the Migration: Pre-Migration Preparation

Successful EHR data migrations are built on thorough preparation. This phase ensures that the data you move is accurate, complete, and formatted correctly for the receiving system.

1. Audit Your Current EHR Environment

Before any data moves, review the existing system to understand:

• Data quality issues
• Duplicate or inactive patient records
• Missing or outdated demographic fields
• Inconsistent formats across providers or departments

This audit determines the scope of the migration and highlights areas requiring cleanup.

2. Define Your Migration Goals

Clear goals guide the strategy. Examples include:
• Improved clinical documentation accuracy
• Better reporting and analytics
• Enhanced interoperability with labs or partners
• Reduced manual data entry and administrative time

Knowing your goals ensures the new EHR supports future workflows.

3. Build Your Cross-Functional Migration Team

Include representatives from:
• IT
• Clinical leadership
• Billing
• Scheduling
• Compliance
• Vendor migration specialists

Each group provides vital input on workflows and data dependencies.

4. Map Your Data

Data mapping defines how each field in your current EHR transfers into the new system. This includes:
• Demographics
• Clinical notes
• Medication lists
• Allergies
• Diagnoses and codes
• Orders
• Document attachments

Accurate mapping prevents data from landing in the wrong fields or being excluded entirely.

5. Clean and Standardize Your Data

Data cleanup is one of the most important steps:
• Remove duplicates
• Standardize date formats
• Correct inconsistent abbreviations
• Ensure mandatory fields are populated
• Verify insurance and payer details

Clean data reduces errors during migration and improves downstream reporting.

6. Establish Your Backup and Risk Mitigation Plan

Before importing data into the new EHR:
• Create secure, redundant backups
• Use multiple export formats if possible (CSV, XML, HL7 extracts)
• Document versions
• Ensure rollback capabilities

If anything goes wrong, you need the ability to restore original data.

During the Migration: Execution Checklist

Once the planning is complete, the migration process begins. This stage requires close monitoring and timely communication.

1. Start With a Test Migration

Run a migration using a sample dataset:
• 10–20 patient records
• Medication lists
• Clinical notes
• Billing history
• Scheduling data

Validate that everything lands correctly in the new EHR before moving the full dataset.

2. Monitor Migration Activity in Real Time

Your team should track:
• Import progress
• Data discrepancies
• Error logs
• Time estimates
• Fields that did not map as expected

Immediate visibility reduces the risk of undetected issues.

3. Maintain Clear Communication Across Teams

Daily or twice-daily updates keep everyone aligned. Your clinical and billing teams need to know:
• What data is currently migrating
• Whether downtime will occur
• What workflows may be temporarily affected

4. Address Errors Quickly

Common migration issues include:
• Missing mandatory fields
• Incorrect data types
• Mismatched date formats
• Character limit overflows
• Custom field compatibility problems

Resolving errors during migration reduces rework and delays.

After the Migration: Post-Migration Validation

Once the data lands in the new EHR, the real work begins. Validation ensures the accuracy and completeness of migrated records.

1. Validate Patient Charts

Review:
• Demographic accuracy
• Medication lists
• Problem lists and diagnoses
• Progress notes
• Allergies

Spot-check large batches of records to ensure consistency.

2. Validate Clinical Workflows

Test whether staff can complete key tasks:
• Document visits
• Enter vitals
• Order labs
• Route messages
• Access care plans

An EHR migration is not complete until clinical workflows function reliably.

3. Validate Billing and Financial Workflows

Confirm accuracy across:
• Charge capture
• Coding
• Claims submission
• Clearinghouse connections
• Remittance posting

Billing disruptions are among the most costly migration failures.

4. Train and Support Your Staff

A structured training plan helps reduce resistance and errors:
• Role-based training sessions
• On-demand training materials
• Go-live coaching
• Helpdesk escalation paths

5. Implement a 30-Day Optimization Plan

For the first month:
• Hold weekly feedback sessions
• Track error patterns
• Identify workflow slowdowns
• Prioritize enhancement requests

This ensures continuous improvement after go-live.

Common Pitfalls to Avoid

Even well-planned migrations encounter challenges. Avoid these frequent errors:

• Migrating unclean or incomplete data
• Skipping validation steps
• Not performing a pilot migration
• Underestimating workflow disruption
• Lack of clinician involvement
• Overlooking payer and billing configurations


Proactive planning minimizes these risks.

Conclusion

EHR data migration doesn’t have to be disruptive. With a structured checklist, careful planning, and thorough validation, healthcare organizations can transition smoothly and improve clinical and operational performance in the process.

If your organization is preparing to migrate to a new system, ChartPath can support data mapping, workflow planning, and implementation to ensure a successful transition.