Data migration & conversion
When legacy systems are retired or integrated with a new EMR, years of clinical data has to come with them. IntOps professionals extract, normalise and migrate it, so your clinicians don’t start from scratch on day 1.
Why it matters
Whether a legacy system is being retired in favour of a new EMR or EMR module, or kept and integrated with it, the key clinical data accumulated over the years needs to be available to clinicians, for patient safety and for efficient care.
Without migration, critical information is simply not there when a clinician opens the new record.
So a known allergy is never missed in the new system.
Safety and care alerts carried across, not re-entered.
The history clinicians rely on to make decisions.
Other key data defined with you during scoping.
How it works
Most migrated data is normalised and brought into the EMR through interfaces. Normalisation is where the real work happens. Legacy data is cleaned, standardised and mapped to the structures of the future-state build, often with clinical and build input to get it right. This includes codification, so every item carries the right codes in the new system.
Thorough normalisation is what makes migrated history usable and safe in the new system, not simply present.
Our approach
We scale up in stages so problems are found while they are small. Every step is fully validated and signed off before the next one begins.
We agree which systems and data sets are in scope, how much history to bring across, and what clinicians need to see on day 1.
We get access to the source data early and assess its quality before any migration is designed: completeness, consistency, duplicates and how it has been recorded over the years. Issues found here are far cheaper to fix than issues found at go-live.
A first migration of 5 randomly selected patients, checked record by record against the source with your clinical and build teams.
Around 200 patients migrated to prove the approach at volume and bring real-world edge cases to the surface.
The complete data set, checked for completeness, accuracy and timing so the load fits within your cutover window.
Validation at scale
Each round runs against more patients, so issues surface at the smallest scale they can. By the time the full data set is loaded, the approach has already been proven on real records.
Day 1 confidence
Our experienced team works closely with your clinical, build and integration teams throughout, so you reach day 1 confident that data has not been lost and your clinicians are not starting from scratch.