What to Validate Before you Hit ‘Go’ on Your EMR Conversion

What Data Validation Actually Looks Like in EMR Conversion

In a proper EMR data conversion, validation starts after the test load. This involves not only confirming that the data exists, but verifying is accurate and usable. The ultimate goal? Ensure that your clinical, operational, and financial teams can fully trust and access the data they need without friction.

Data validation usually involves:

• Randomized record sampling across key domains (clinical, administrative, billing)
• Match-rate and field-level integrity audits
• Format consistency checks between legacy and target systems
• Comparative analysis of migrated vs. source application data
• Workflow simulations to confirm frontline usability
• Discrete data validation–ensuring structured fields didn’t flatten into PDFs or scanned images
• Departmental reviews to surface function-specific red flags

If you’re wondering, “what is EMR conversation validation really for?” The answer is simple: reducing the chance of post-live chaos. Skipping or improperly performing validation is often the root of issues that show up later in EMR conversions and wreak havoc on timelines and budgets.

Metrics that Matter

Effective validation is measurable. Digital healthcare leaders that lead successful migrations that include healthcare data conversions don’t wait for anecdotal issues to surface; they define clear success metrics:

• Match rate: Percent of fields that mapped and loaded correctly 
• Error rate: Percent of fields with formatting, logic, or data loss issues, 
• User acceptance rate: Number of departments signing off with no red flags 
• Test workflows pass rate: Percent of simulated workflows that run successfully  

These are the types of numbers that drive confidence. They are also critical warning signs to check to see where you may need more due diligence before go-live.

How Much is Too Much Data in EMR Data Conversion?

Deciding how much data to convert can be tricky. Not all data is equally useful—and not all documents should make the leap. This is where validation collides with scope.  

Converting everything slows down the process and inflates costs. But converting too little? This creates downstream disruptions and user distrust. 

Some organizations try to convert entire record sets, only to discover after testing that scanned documents or image-heavy PDFs don’t map cleanly and can’t be easily searched or used in the new application. It’s issues like these that make understanding and being able to identify discrete data in your healthcare IT setting mission-critical in medical data conversions.  

Discrete data can be cleanly mapped and used, while non-discrete data often requires archival or alternative storage strategies. Consequently, deciding what to convert often comes down to understanding your organization’s data types.

Don’t Skip the Last Check in EMR conversion

It can be tempting to quickly move ahead after the first foundation of validation “looks good.” But don’t. The best EMR data conversion service partners run multiple cycles. Each one catches more, improving data integrity and ensuring quality.  

When your organization approaches validation, remember that you’re not just protecting your go-live process. You’re also protecting your organization’s operations, billing, and care quality.  

With so much risk, the costs of improper medical data conversion are considerable and not worth paying.