Simplification is critical because data migrations often occur during times of major transitions—for example, when a healthcare organization implements a new electronic health record (EHR), merges with another health system, or acquires a medical practice. What you don’t want to do is embark on a data migration project without having a clear sense of what you’re trying to accomplish, why, and how you’ll do it. Without a strong healthcare data management plan, you may struggle to set expectations, meet short- and long-goals, and obtain the intended return on investment.
There are several reasons why defining your data migration strategy is beneficial to your facility or organization. Consider the following advantages of a well-thought-out approach:
While each hospital’s data migration strategy may vary depending on the specifics of the data and systems involved, there are several universal steps that apply.
While no data migration is the same, they all should involve these steps:
1. Develop a detailed healthcare data management project plan.
Take the time to think through (and document) why your data migration project is necessary, whether the project will include a full or partial migration, the estimated timeframe, key stakeholders and their responsibilities, budget, anticipated challenges and solutions, and tools that will be necessary to execute data migration best practices and automate processes for increased efficiency. This project plan will keep everyone united, accountable, and moving toward the common goal of successful data migration.
2. Assess and organize the data.
In this step, you’ll take a deeper dive into what healthcare data you have and where it resides. You’ll need to review all structured and unstructured data in healthcare systems and go beyond electronic applications to investigate paper-based data sources as well. The goal? To gain a comprehensive understanding of the totality of your data management landscape.
During this step, you’ll also ask questions to determine whether retaining any of your data is no longer necessary (potentially leading you to archive it or even destroy it), whether any of the data is of particularly high value (and should thus receive priority migration status), and whether the quality of the data is sufficient.
Be sure to review all databases, files, and applications that hold healthcare data. If, at any point during the review process, you discover problems with data quality (e.g., missing or incomplete data), you may need to develop data quality standards or use data profiling or data normalization techniques before starting the migration process. Data profiling helps you assess issues with data duplication, inconsistency, and inaccuracy while data normalization ensures data entries are similar across all fields and records, making it easier to find, group, and analyze information.
3. Perform data conversion, if necessary.
Healthcare data—particularly EHR data—comes in different formats. This means you may need to convert everything into a single, unified format suitable for the new system. A singular structure also makes it easier to work with the data moving forward as business goals and data use cases evolve. Data mapping shows the relationships of data elements in different systems and can help you identify precisely where to focus your conversion efforts.
4. Ensure compliance and security.
Use data encryption and secure channels before, during, and after the data migration process to comply with HIPAA and any other state or local requirements. Also be sure to conduct a risk assessment as part of your data migration strategy to identify cybersecurity vulnerabilities and proactively address them for all data in transit and data at rest.
5. Choose the right tools.
Given the volume and complexity of the structured and unstructured data in healthcare systems that your organization may choose to migrate or archive, you’ll need tools to automate certain processes. Automation helps reduce errors and keep your healthcare data management project on track. Any tools you leverage should be healthcare-specific and incorporate data migration best practices as well as the most modern data management techniques to ensure your success.
6. Validate data in the new system.
Once you’ve migrated the data, you’ll need to ensure its accuracy. Why? Even if you don’t notice any obvious problems during migration, this doesn’t mean you can make widespread assumptions about the success of the project. Problems could lurk beneath the surface, and it’s important to recognize and address them immediately. Testing the data post-migration ensures it meets usability requirements and that the new system functions properly.
7. Prepare for downtime.
Even despite your best intentions, downtime during data migration may occur. The good news? There are ways to minimize it, starting with adding safeguards into your data migration strategy. This includes scheduling data migration during off-peak hours, using modern data migration and data archiving solutions, and monitoring the process continuously to detect and respond to issues as they arise. Following the other data migration best practices outlined in this article can also mitigate downtime.
Healthcare data migration may seem daunting at first, but having an effective data migration strategy can ease stress. With the right healthcare data management approach, your organization can quickly reap the rewards, including reduced costs, easier access to data, improved backup and disaster recovery, and greater storage capacity. Contact us to learn more about Olah’s safe, secure, and fast archiving solution.