Six Phases of Data Lifecycle Solutions: Put Health Data Archives to Work for You

By Jim Hammer, VP of Operations and Product Development, Harmony Healthcare IT
Twitter: @HarmonyHIT

After 20 years in healthcare IT and witnessing countless implementations, mergers, acquisitions and data archives, a recurring theme that I know to be true is this: The best time to start your legacy data management project is today. Whether you’re looking to migrate data to a new system or archive existing legacy data, the success that comes from this work can reward your organization tenfold.

Moving old data from legacy systems and making it easily available within new applications drives significant benefits for your end users and patients. Archiving this data from aging silos also secures PHI and delivers hard and soft cost savings for your healthcare provider organization.

In a recent episode of HealthcareNOW Radio’s “The Tate Chronicles,” I sat down with host Jim Tate to discuss the six phases of the data lifecycle and how they inform legacy data management. Each phase guides the next practical step for effective data archival and system decommissioning. The six phases include:

  1. Consultation
  2. Extraction
  3. Migration
  4. Retention
  5. Integration
  6. Destruction
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The first step in legacy data consolidation is to consult with data management experts. This initial kickoff meeting ensures everyone is aligned and on the same page. Here are important points to cover:

  • Establish best practices and research expert guidance
  • Discuss data retention requirements from the local, state and federal standpoints
  • Identify what documentation is required for each type of record
  • Determine what strategy or approach to take: retention, migration or destruction

Setting a solid foundation for your project is the cornerstone for lower costs, reduced risk and fortified cybersecurity defenses. I’ll use clinical data from an EHR as an example here, but a similar path also applies to business or employee records.

Data extraction is critical when replacing one EHR with another. The goal of extraction is to remove data from the source application or system. Accurate, discrete EHR data extraction lays the road map for successful subsequent processes such as transformation and load. Each system has its own unique set of challenges and solutions to make the end result possible, so you want to partner with an experienced, knowledgeable vendor.

After extraction comes the necessary step of migration. Because conversions to a new EHR can be lengthy and expensive, many organizations are choosing a hybrid strategy. They will convert and migrate only the most important and recent records to a new EHR. Then the rest of the data will be migrated to an archive, such as HealthData Archiver®, since the records still need to be maintained and accessed. This allows the old legacy system to be decommissioned, saving on hard and soft costs.

The time span for most healthcare data retention is seven to ten years, but it can be more. There are many benefits of using an active archive to meet those requirements. Records from various legacy systems can be consolidated and secured in one place. An intuitive user interface enables workflows for clinical and health information management teams to easily access historical records.

In the age of 21st Century Cures Act and interoperability, it is more important than ever before for data integration to deliver connectivity in the form of data exchange and sharing.
Be informed of interoperability standards when moving or archiving your data. Set a standardized approach for future legacy data management projects.

The final phase of the data legacy lifecycle is destruction. This ultimately answers the question, “What are the proper steps to shut down the legacy application?” This can also apply to hardware, such as servers that store PHI. If your organization is ready to wind down the extra expense of legacy system maintenance and support, this step in the journey brings a sigh of relief for the organization.

The result at the end of each of these six phases? Cost reduction, risk mitigation and better use of your legacy data.