EMR data extraction at MDH Insight is one of the fundamental features that truly set us apart from our competition. Typically the critical first step in obtaining existing legacy patientdata, proper EMR data extraction means exporting as much data as possible in a usable format in order to seamlessly migrate to the new system. Leveraging technology with the vast skills of our technical team, our sole focus is unshackling your data from the clutches of the legacy EMR system. With ourcomprehensive, efficient, and effective approach, your practice is able to grow in a pain-free and secure manner.
At MDH Insight, we are able to take patient data from the old system, and depending on the circumstances, often without engaging the EMR vendor. Unfortunately, many EMR vendors are slow, costly, and difficult when it comes to getting data out of their system. We promise our clients faster, more accurate, and higher quality results. Additionally, we are able to make certain that the data is converted into the new EMR system’s format, ensuring a smooth and safe transition.
Capable of desktop and/or server-based extraction in your office, MDH Insight saves time and ensures accuracy with our proven two-pull data system. Quality assurance at MDH Insight is powerful and unique:
The Example Tree Structure Of Ehr Data Types And Primary Types
Two data pulls means thorough and meticulous EMR data extraction, each and every time. While our in-depth, systematic approach remains the steady, MDH Insight is able to tailor data extraction to meet the specific needs of each individual client. Consequently, our clients can feel confident and secure in trusting our process, allowing them to shift their focus to the continual improvement of patient care.
MDH Insight understands that the healthcare industry depends on complete and accurate data, especially during the EMR data extraction process. For that reason, when it comes to accurate data: We Deliver.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.
Federal Mandate For Electronic Medical Records (emr)
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.
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?
Future Of Ehr/emr
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.
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.
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.
Standardized Electronic Health Record Data Modeling And Persistence: A Comparative Review
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.
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.
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.
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