The process of migrating from one EMR to another is among the most difficult technical and functional projects a healthcare organization can tackle. EMR data migration requires a thorough understanding of the underlying data structure as well as a solid foundation in interoperability standards such as LOINC, HL7, SNOMED, and CDA. Beyond the technical considerations, bringing together all of the stakeholders in your practice or practices and getting them to agree on which data will be migrated can be a significant challenge. If the right questions are not asked at the start of a migration project, it may be executed in a way that does not meet the needs of all stakeholders – resulting in time-consuming and often expensive rework or project cost overruns.
Below are the 5 most frequently asked questions (with answers) our clients pose when tackling EMR data migration. Download the full EMR data migration whitepaper for additional considerations, tips, tricks and best practices.
Q: Do you migrate all data from the legacy system, or can parameters be put in place?
A: We can migrate all of the data or a selected range of the data based upon your requirements. Typically, the data elements & amount/duration of data is driven by organizational requirements related to continuity of care, patient safety and even population-based reporting requirements. The Galen team is able to assist your organization in evaluating these requirements and industry best practices regarding these considerations. Any data not migrated can be archived using Galen’s VitalCenter Online Archival EMR data archival solution.
Q: How long does a live EMR data migration take?
A: All migrations are based on elements and the amount of data to be migrated. For example: if Medications, Allergies, Problems, and Scanned Documents are to be migrated and there are 10 years worth of data, then the process could take up to a week to migrate into live. It is recommended to do these types of migrations in stages and spread it over several weekends.
Q: What about any new items that were added in the legacy system after the initial extract was taken? How do we include those items in the migration?
A: There are a couple different ways this can be handled. It depends a bit on the exact source system you are migrating from. If the source system allows free text items (medications, problems etc.) it can be helpful to instruct users to not enter free text after the initial extract and to only use dictionary items. Then to capture any data that was added, a second extract can be taken a week or so prior to the go live and a catch-up mapping exercise can be performed. This should capture any items that were added.
Q: Why does the EMR data migration only grab the most recent instance of each item?
A: Most EMR systems store each time a clinical item was updated separately. For example, if a diagnosis was assessed three different times during three separate visits, there would be three records of that diagnosis. If we were to migrate each instance of that diagnosis, you can imagine we would end up with duplicates in the patient’s chart. We typically extract the most recent example of the item so we get the most up-to-date comments/edits to that item.
Q: What do we do when a patient is not able to be matched?
A: There are a few different options you have when patient matching fails. During the emr data migration process, we can provide a report of those patients that failed. The easiest method to correct the errors is to update the legacy system to fix the reason for the error. This might be updating the patient’s last name or some other piece of information so it matches the other system. If patients are missing from the target system, they can also be added. If the patients do exist in both systems and the first method is not an option, a one-to-one mapping exercise can be completed that will map the patient in EMR to the unmatched patient record from the legacy system. This mapping can then be added to the emr data migration logic so data is able to be migrated. Another option is to manually abstract the information for those patients that cannot be mapped. This can be a preferred option if there aren’t many patient matching errors or if the project is on a tight timeline.