If you’re about to embark on an electronic health record (EHR) migration, you’re likely wondering about the data conversion aspect. How can you get all patient data to the new system in the easiest possible way? Can it be automated? How much work will it require from internal staff? How expensive will it be?

Many organizations approach EHR migration thinking they have the answers to these questions — only to find out there’s a lot they didn’t know. It’s natural to assume all your data will magically move from one system to another, but it’s not that simple.

The good news is, organizations that keep a few considerations top of mind before attempting to convert patient data set the stage for lasting success and ROI. It’s possible to get patient data to your new system securely, within budget, and on schedule — having preserved the clinician and patient experiences. Take note of the following realities to achieve that goal.

1. Not all data transfers automatically.

Patient data does not move from one spot in your legacy system to a new spot in your modern EHR in a straight line. Nor is there a magic wand that moves everything in one fell swoop. Understanding early what can and can’t be transferred saves you a ton of headaches later.

Every EHR system maps data differently — data structures, field formats, and mapping capabilities vary. For example, a lab value in one system may not have an exact corresponding field in the next. It’s critical to conduct data inventory early to see what may be automatically transferred to your new EHR and what may require manual abstraction.

Key takeaway: To some extent, you will need to perform manual data abstraction.

2. You don’t need to move every record.

It’s common to think all data from your legacy system is valuable and needed in your new one. Not true! Migrating everything is not only unrealistic from a cost and time stand point, you simply don’t need to do it. For instance, you don’t need a patient’s vitals from five years ago, but you do need the last several months of vitals for a pregnant patient.

It’s essential to identify which data is clinically valuable. Ask the following questions as you evaluate your data:

• What data supports patient care?
• What data supports reporting or compliance?
• What data will never realistically be accessed again?

Key takeaway: Focus on the data your organization will actually use, and archive the rest.

3. Make a plan for data you don’t move.

Speaking of archiving, you can’t just delete data that stays behind. You also shouldn’t pay for full licensing in your legacy EHR system to keep that data online. You have a couple options for retaining and securing that data while keeping it retrievable for legal and clinical reasons:

• Use archive solutions like cloud storage or an external data repository
• Keep data in read-only mode — reducing the need for licensing and support

GuideIT helped a client save $200,000/year by moving to a cloud solution instead of paying for full EHR licenses.

Your archive solution will need to support your compliance requirements, which may mandate data retention of anywhere from seven to 20 years depending on the patient population.

Key takeaway: Plan for data archival before go-live so you’re not stuck paying for a system you don’t use.

4. Budget for data conversion now, or pay for it later.

Many EHR migration budgets only cover system implementation and overlook data migration entirely. If you don’t budget accurately and early for medical data abstraction and conversion, you’ll end up short-funded or rushed. We see it all the time.

In a notable instance, GuideIT has spent the last several years helping a multi-state healthcare organization convert +2 million patient charts and consolidate over a dozen legacy EHR systems into a single platform. When we began work together, they had not fully scoped their abstraction project — ultimately adding millions of dollars in unplanned costs. (Read the full story here.)

Key takeaway: Include data abstraction as a defined workstream in your migration map and budget — with clear cost, timeline, and staffing assumptions.

5. Consider regulatory and reporting requirements.

Some organizations realize after go-live that they are obligated to report on data they didn’t migrate. GuideIT has worked with organizations that discovered they needed data from multiple groups for regulatory reports, but they had only migrated one group’s data.

Avoid these gaps and compliance scares by asking these questions early:

• Which data supports your regulatory and quality reporting?
• How far back do you need to retain data for compliance?
• Does certain data need to live in the new EHR, or can you archive it securely elsewhere?

Key takeaway: Make compliance and reporting considerations a part of your initial planning stages.

6. Know what your vendors will and won’t tell you.

Don’t assume your EHR software vendors will fully outline what’s possible for data transfer and storage. The legacy vendor may not disclose what data formats they can export, or they may promise full conversion capabilities that don’t exist.

We once saw a case where a vendor assured a client they could migrate everything from their existing system to the new system, but in practice, only a fraction of the data was compatible. In this instance, the client required more manual abstraction yet had not budgeted for such.

Before you sign any contracts, clarify responsibilities and capabilities, including:

• In what formats can the vendor export data?
• What data types do they guarantee to convert?
• Are there costs associated with exporting or extracting data?

Key takeaway: Approach vendors with the knowledge that you need to ask the right questions to get the right info.

7. Anticipate clinician and patient experience impacts.

Adequate planning for data conversion affects more than budget, time, and compliance — it affects people. If you don’t abstract and migrate data properly or on schedule, both the clinician and patient experience suffer.

Let’s say a patient comes in after go-live and is asked to repeat medical details from their history that should be present in the new system. Or maybe the clinician can’t pull up the patient’s information easily — requiring them to switch between two systems to find it. These friction points add up — frustrating clinicians, slowing down workflows, and negatively impacting the patient experience.

Worst case scenario, patient data is missing or unretrievable in the moment, causing the clinician to make ill-informed diagnoses or decisions that directly affect patient health.

Key takeaway: Aim for data conversion so seamless that no one knows it happened.

8. Plan for quality assurance (QA) — a must-have.

A thorough QA process is often what separates a smooth migration from a risky one. Unfortunately, when organizations handle abstraction internally, they end up cutting QA because deadlines or budgets tighten. Migration leaders see it as a nice-to-have, when it is anything but.

This is where bringing on an external abstraction partner is the difference-maker. GuideIT builds QA into every step of the process, with regular validation. Our approach ensures accuracy from the beginning and avoids compounding errors — protecting patient safety and compliance.

Attempting QA internally? Ask the following questions:

• How often should teams review records?
• Who is accountable for validation?
• What’s the escalation process when errors appear?

Key takeaway: Even if you manage data abstraction and conversion in-house, define a structured QA process upfront.

9. Expect variability across clinics and systems.

If your organization has multiple facilities, you may need to wrestle with transitioning multiple systems. Even if you run the same legacy EHR, each clinic and department within those clinics likely has its own set of workflows and data priorities.

To get even more granular, individual providers may notate and enter data differently — requiring additional levels of standardization and reconciliation.

Key takeaway: Build in time and flexibility to address each site’s needs and move data in waves of smaller transitions.

10. Don’t lose sight of the bigger picture.

The end goal of your data migration isn’t just to get secure data where it needs to be at the right time — it’s about maintaining continuity of care. Your data migration should ultimately support:

• Clinician satisfaction
• Patient safety
• A long-term growth plan

Spending time upfront to cover all the bases we’ve discussed in this blog is well worth it when you see the bottom-line results of positive patient experiences and high clinician adoption of your new EHR.

Key takeaway: Focus on the long-term vision of your organization, and the technical details will align around it.

Start your migration with this question: “Do we know what we’re moving and why?”

If the answer to that is murky, the abstraction experts at GuideIT are here to help. We have 30+ years’ experience helping healthcare organizations abstract data and successfully move EHR systems. We offer a free, custom advisory session on your migration plan. Book your assessment here to get free guidance on how to plan a smart EHR migration, avoid costly surprises, and protect your operations and patient base.