For hospitals and health systems in the U.S., data mapping is a critical function of any healthcare data conversion project. Yet poor, inefficient processes and avoidable errors can cause a host of significant negative downstream effects, including delays, additional staff burden, an impact on operations, patient care, and compliance, and higher costs. With the right strategy and processes, however, healthcare data mapping doesn’t have to be difficult.
What is Healthcare Data Mapping?
Health systems have different types of data coming from various sources, or even from one source. These data constructs sit behind the scenes and connect to one or many other locations in an application.
For example, discrete data and documents can come from an EHR, while other documents can come from a care platform that is linked to the EHR. Images can also be generated on the fly from data that is stored in the EHR or the care platform.
That’s where data mapping comes in. Data mapping is the process by which two or more similar sources of data are matched in order to successfully extract legacy application data and convert it into the current EHR.
The Pitfalls of Poor Healthcare Data Mapping to EHR Data Extraction
Although data mapping should be simple and straightforward, poor processes can create significant issues.
For example, if Cerner Millennium data is to be extracted, there is the potential for approximately 3,200 flat files to be delivered so the risk of missing data is exponential. If just one file is missing, and it is mapped to seven different locations, for example, the result could be catastrophic without the right processes in place.
Over the years, we’ve seen these types of data disasters play out time and time again.
Take one of our clients who had initially engaged with a vendor that specialized in data extraction. When we kicked off the project, the vendor was selective about which data they were willing to provide us with, which led to missing data. After frequent rounds of discussions attempting to get the data—about 18 rounds in total—the project was consequently delayed by about 9 months, costing the health system much more than they planned for.
Another client wanted to figure out how to execute the data mapping on their own and started by looking at the front end of their applications, which is inefficient and can create errors. As a result of going it alone, they added nearly 4 months to the extraction process and created extra work for themselves. There are countless stories like this, including this client who was left with inaccurate, incomplete documentation after their previous conversion vendor performed improper data mapping and extraction.
Why Accurate Data Mapping is Critical for Healthcare Data Conversion
Accurate data mapping is critical for successful healthcare data conversion projects. Here are some reasons why.
Timeline and Budget
If additional data has to be extracted because it was incorrect or incomplete, unnecessary delays can occur, wasting time and resources, impacting end users, and driving costs. Internal staff may be pulled away from their day-to-day roles and responsibilities to review the data again, which can impact care and operations.
Regulatory Compliance
Data gaps can pose compliance risks. For example, patients may request data that may not be available. Plus, organizational compliance and regulatory audits could leave an organization vulnerable to lawsuits.
Quality Patient Care
Missing data about a diagnosis or treatment plan, for example, could lead to patient safety risks and impact care.
Operations
With any EHR data conversion project, it’s vital to take into account all of the places in an application where an end user is going to expect to see the data. If the data isn’t mapped the right way, the end user will see incomplete or incorrect data. Inaccurate data mapping can also impact accounts receivable and other critical operations.
How MediQuant Ensures Accurate and Complete Data Mapping
The right partnership is important for accurate healthcare data conversion projects, yet not all vendors are created equal. With MediQuant’s active legacy data archiving platform DataArk®, we ensure healthcare data conversion projects are done right from the start, are completed within the designated timeline, and are on budget. Here, learn more about our unique approach.
Collaboration
We not only identify our clients’ goals, but we take the time and use our years of experience and expertise to determine how we can best guide them. We work with them and other relevant stakeholders to identify clinical datasets that require translation or a crosswalk between applications. We provide mapping workbooks that contain legacy application codes, descriptions, usage counts, and percentages to allow clients to prioritize the mapping of frequently used codes.
Lights Out: The Threat of Vanishing Data Access
Capability To Work With Diverse, Disparate Applications
We have the capability to extract data from diverse sources whether it is provided via an application backup, programmatic extracts, or extracts provided by HIT vendors. With the capability to match unusual proprietary data sets with similar data constructs, we have the context and knowledge of nearly all major HIT applications on the market today, as well as homegrown or older apps that are no longer in production.
Advanced EHR Data Extraction and Mapping Capabilities
We use advanced data mapping and extraction technology such as ETL as well as Recovery Manager (RMAN), to streamline EHR data extraction and mapping for Oracle-based databases like Cerner Millennium, ensuring accuracy and reducing project timelines. Using RMAN, we can reduce legacy data archiving project timelines by 75%, increasing data quality.
Standard Data Modeling
While we recognize that our clients have customizations within their applications, using a flexible approach can cause issues and drive costs. Our solution, therefore, has a standard structure in place which reduces excessive, time-consuming, and costly customizations.
We use proven scripts that contain the most used and required data elements, and have over 30 project implementation templates to support our client projects in a scalable way. This approach decreases implementation time and the risk of validation issues and unnecessary cycles to resolve them.
Comprehensive Data Validation
With our scripts, we conduct internal validation to ensure the extracted and mapped data is accurate, complete, and aligned with the target application before the data is ever provided to our clients. Plus, for financial data extractions, we perform two rounds of validation.
Healthcare Data Conversion Expertise
We have 25 years of experience supporting healthcare data conversions and archiving medical records for hundreds of hospitals and health systems. Our team includes subject matter experts—some of whom helped to set up EHRs at health systems and have a comprehensive understanding of what the applications look like from the front and backends. Our clinical experts, data modelers, and others bring real-life experiences using many different types of healthcare datasets and have decades of experience in healthcare and healthcare IT.
Data Stewardship and Governance
Our team lends their expertise and experience of performing EHR data extractions and implementations to educate our clients about how to have conversations with their legacy vendors. Our approach ensures data integrity and properly structured data that meets our clients’ current and future needs.
Compliance and Security
Our expertise in meeting regulatory requirements like HIPAA ensures the privacy, security, and accuracy of protected health information while maintaining full compliance throughout the process. We, and our third-party vendors, are HITRUST certified, ensuring we adhere to the same standards.
Through DataArk, MediQuant’s vendor-neutral legacy data archiving platform, extracted data is mapped and provided in an intuitive system for end users. Our implementation process typically takes 6 to 7 months, versus the 12- to 18- month process of other vendors.
Case Study: MediQuant Corrects Critical Data Conversion Failures from Previous Vendor
Planning or in the midst of a healthcare data conversion? Schedule a discovery call today to find out if your data mapping is helping or hurting your conversion.
