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. For a deeper dive into EHR replacement and data migration, download our whitepaper.
The process of converting from one EHR to another is among the most difficult technical and functional projects a healthcare organization can tackle. At the heart of the process, it’s important that clinically driven workflows across various user roles are supported, transitioned, and maintained to the greatest extent possible. Once this objective and post conversion stabilization is complete…what comes next for the legacy system and what functions does it now serve?
Will it need to be periodically accessed to reference gap data sets or date filtered content?
Are there ongoing reporting or quality initiatives that rely on access to historical & detailed source data?
What will be the costs of maintaining licensing costs and ongoing application support? Technical debt?
What will become of data sets such as biometrics? Or deceased patients?
The sheer number of decisions to make can be overwhelming!
In addition to reducing the footprint of both infrastructure and general overhead costs associated with legacy systems there will inevitably continue to be situations where access to legacy data is required and unavoidable. As the need for generating clinically driven requests from the legacy system decreases over time the non-clinical and legally driven retention standards surrounding it will continue to grow.
The longer term implications of creating a strategy for managing and decommissioning these legacy systems may also apply to systems that have or have not had data previously converted to/from them.
Coming off the tail end of a data conversion, a data archival approach can be uniquely positioned to support critical pre-requisite decommission tasks and data retention standards at the federal, state, and organizational levels.
What are potential areas of tech debt consequential to not having a consolidated archive?
Consolidation of Data Sources
Even within an existing architecture that provides the means to an end for supporting raw data archival gathering requirements there are benefits to a centralized archival solution outside of the system itself such as reducing the need for archival end user training and decreasing turnaround for electronic records requests.
Legal & Audit Requests
While it is still feasible to satisfy such requests within legacy architectures it remains a data retrieval challenge to filter out duplicate clinical items across the same patient associated with multiple data sources (such as comprehensive medication lists or problem history).
The management of duplicate records is an ongoing process for essentially all healthcare organizations. Spreading potential identities and converted demographic changes over time across current, legacy, and reporting data and then satisfying unique and particular data retrieval requests accurately is an intensive process without true consolidation of data sources combined with patient identity group management.
How does converted data stack up to comprehensive retention standards?
While converted data is available in a conversion setting it is still not considered to be fully discoverable in a way that can completely support eDiscovery requirements for Electronically Stored Information (ESI). Because it only contains the latest version of the data record, any audit records associated would need to be extracted, parsed, and correlated from the legacy system.
Scope of Data
A typical and robust data conversion may actually only include roughly up to 60% of the full scope of legacy data considered to comprise the full legal medical record. This is where archiving legacy data provides direct added value in terms of data retrieval turnaround, accuracy, and overall consistency of data.
Clinical Data Details
eDiscovery and legally driven requests in general will require more comprehensive versions of clinical detail data, version data, and any associated audit records. These are data attributes and extended properties that go above and beyond what are typically mapped and included in data conversion settings (the overall shape and depth of the data is bulkier).
This is one data set in particular that tends to reside on its own island in the legacy system after migrating to a new system. It is almost never included in clinical data conversion scope due to its higher technical complexity and lower immediate clinical impact. Legacy system audit data is considered one of the core data sets for archiving legacy source data.