Validation: The success of your data migration will be only as good as your validation efforts
This entry is part of our data migration blog series – a range of topics intended to help organizations who are migrating from one EHR to another.
Not to be overlooked, one of the most important keys to a successful data migration is the validation effort. Without a well-developed strategy and proper implementation, the hard work put forth prior to the validation process could be for naught. Taking that into consideration, it is vital to thoughtfully plan how this effort will be executed. But what does a successful validation effort truly look like, and who are the assets driving the process forward?
First, it is important to understand the different steps of the validation process and the role that each step serves. Validation can be broken down in five steps:
- Unit Testing ensures that each element of the data conversion from the legacy system to the target system is confirmed prior to hand off to the clinical team for validation. When Galen is assisting a client with a data migration, this step is performed by the Galen Tech.
- Small-Scale Validation targets common issues utilizing a small sample set of patients (usually ten patients). This ensures that large-scale validation can be maximized to find less common issues. Looking at patient-level data elements also helps to ensure that everything in scope for the data migration is being captured. When Galen is assisting a client with a data migration, this step is performed by the Galen Clinical Data Migration Analyst.
- Large-Scale Validation along with full-scale validation are collaborative efforts. When Galen is assisting a client with a data migration, multiple iterations of this validation step are performed by both the analyst and the client. As problems are identified at the element level, they are worked on by the tech team and then retested. Ensuring that the issue has been corrected and no new issues have been identified. This round of validation also focuses on workflows, ensuring that each data element is functioning correctly while working through patient charts.
- Full-Scale Validation encompasses the entire patient population. The goal is to test the extraction, timing, delivery. Loading of all the live patients in scope to a test environment that closely mimics production. This gives the data migration team time to identify and work any errors before the final load into production. It also allows for one last sample set of patients to be validated to ensure issues have been fully resolved.
- Gap Load Validation is similar in nature to full-scale validation. However a smaller data set is used to capture the information that is added to an EHR after the initial extracts are taken in preparation for end user go-live. It is the last round of validation for a data migration. When Galen is assisting a client with a data migration, this step is performed by the Galen Clinical Data Migration Analyst.
As you can see, the validation process is complex and requires a number of resources from an organization in order to successfully complete. So how does an organization plan for and implement a successful strategy to fully engage those required resources? There are several factors here, but the good news is Galen can help lead the effort and provide key considerations to guide this process:
Identify Validation Team – Ideally, having people who know both the legacy system and target system as validators expedites the process of reviewing each converted data element. However, these resources are hard to come by. In order to address this, organizations can host training sessions to show proper workflows for testing the migrated data in the target system. The majority of validators should be clinical in nature, so allocating their time to the project must be accounted for early on in the process.
System Access – Each one of the validators will require access to the legacy and target systems that house the converted data elements. It is important to verify access to these systems so the user provisioning team can address any issues prior to beginning the validation cycle.
Central Validation Location – Having a central location to perform validation makes issue tracking and addressing any questions from the validators much easier. It also allows for demos to be performed to keep everyone on the same page when validating all the data elements in scope. Another item to consider is provisioning dual monitors for each validator, as this allows him/her to view both systems, which increases accuracy and expedites the validation effort. Reserving this facility and coordinating validation resources should be scheduled well before the validation efforts are slated to begin.
Validation of in-scope data elements during a data migration project is a very complex process, and these are just a few of the many considerations to take when coordinating resources. Galen has the expertise to help you through this process as well as the entire migration project. If you would like additional information about our services, please contact us and continue to watch the blog for upcoming articles in our data migration blog series.
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