Why EHR Data Extraction Makes or Breaks Health Data Archival 

What EHR Data Extraction Is and Isn’t

You’ve heard the promises: seamless EHR conversion and healthcare data migrations, perfectly indexed, active data archives with historical and current info at your staff’s fingertips.

Delivering on these promises hinges on solving one complex question: how do you pull decades of information from applications that weren’t designed to let it go? It all starts with data extraction.

Data extraction in healthcare is a multi-step process that retrieves relevant data—structured or unstructured—from legacy applications to prepare it for transformation, data mapping, and integration into its new environment. In EHR data migrations, healthcare data extractions pull legacy data before it’s loaded into the go-forward application.

In clinical data archiving, historical or inactive data is extracted so it can be stored in a secure, centralized repository for compliance and other needs. One of the most important is providing hospital staff with easy access to the historical patient records information needed for critical functions.

What healthcare data extraction isn’t? A simple copy-and-paste operation. Legacy data rarely aligns with new application formats and requires transformation to ensure usability in clinical, financial, administrative or future secondary initiatives such as research and analysis.

What Makes EHR Data Extraction So Complex?

Legacy applications weren’t built for modern IT environments or designed with EHR data extraction in mind. One example is Cerner Millennium which features an interface with more than 3,200 flat files scattered across multiple locations—missing even one can compromise the entire project.

Some common challenges that can complicate data extraction include:

• Legacy Application Complexities: Applications like McKesson STAR or MEDITECH Magic use proprietary database structures. Some use outdated languages like COBOL which require increasingly rare, specialized knowledge.
• Legacy Vendor Dependency: Proprietary applications frequently leave organizations reliant on software vendors, who may lack urgency or technical expertise.
• Unstructured Data: Clinical notes, scanned images, and other unstructured records are critical to continuity of care but are often overlooked during extraction.
• Data Mapping Challenges: Legacy schemas rarely align with new application requirements, posing costly downstream issues without careful data mapping.
• Rushed Timelines: Inexperienced archive or legacy application vendors that are ill-equipped for healthcare data extraction can skip essential steps when faced with aggressive deadlines, causing preventable errors.
• Unclear Extraction Responsibilities: EHR data extraction responsibilities are often outlined in contracts but it’s not always clear whether your organization, your legacy application vendor, or archive partner must perform it or how legacy data should be provided.

Take this client example: A healthcare organization purchased data extracts from their legacy application vendor but never received a complete copy of the contracted deliverables. The project ended up two years behind schedule because the proprietary data extract didn’t include critical patient accounting documents. After several months struggling to clarify requirements with the legacy application vendor, the client couldn’t find anyone a resource within the vendor’s organization that understood what was needed for extraction, dragging the project out without resolution.

The lesson? Clearly define both your data needs and data extract responsibilities upfront—whether they fall to the legacy application vendor, archive vendor, or your organization.

Gaps in expectations can lead to delays, increased costs, and operational disruptions. In some cases, the impact is more severe, posing risks to compliance or even patient care. The key is to recognize the signs of flawed data extract early.

5 Essential Tips for Successful EHR Data Extractions

The best EHR data extraction strategy is proactive, guided by clear expectations and experienced archive vendor insights. Before starting, it’s essential to determine whether you need a static archive for basic information access, or a dynamic, active data archive. Beginning with the end goal in mind helps inform strategies that support better healthcare data extraction results.

Here are 5 best practices for ensuring successful EHR data extraction:

1. Know Where Data Resides: Data within legacy applications like Cerner Millenium are spread out across different “behind-the-scenes” software applications and formats. Make sure your data extract includes all information stored within the legacy application.
2. Understand Data Formats: Applications like MEDITECH Magic or McKesson STAR use proprietary formats, while others use programming languages like MUMPS or ones as old as COBOL. In some cases, the legacy application vendor may charge for the extract and a programmer may need to write code that allows extraction.
3. Define What Data You Need: Clearly identify which data sets need to be extracted. Everything visible in the application, from clinical notes to billing records, should be accounted for to prevent gaps.
4. Discuss Data Transfer Methods Early: Align on secure transfer methods, such as secure file transfer protocols (SFTP) or cloud-based solutions, to avoid delays and miscommunication later in the project.
5. Understand Preparation Requirements: Certain datasets may need preparation before healthcare data extraction. For instance, eClinicalWorks progress notes require decryption and user-locked actions before they can be extracted. Identifying these prerequisites upfront helps prevent bottlenecks.

Don’t Let Flawed EHR Data Extractions Be Your Weakest Link

Getting EHR data extractions right the first time is crucial for successful medical records archiving as well as EHR conversion and healthcare data migration. With decades of enterprise legacy data management experience and an expert healthcare data extraction team, MediQuant has the knowledge, resources, and best practices to help you avoid or recover from healthcare data extraction issues.

Concerned about a current project or planning an upcoming initiative? Schedule a complimentary discovery call with one of MediQuant’s data extract experts for an assessment to help you get your project back on track for success.