Originally published in July 2019, updated March 2022
The first article in our mapping series will focus on lab data, addressing the following common questions: Why is LOINC code mapping important? What exactly is being mapped and why? How can an advanced data quality solution help?
Why is LOINC code mapping important?
Today, healthcare organization must code lab data using the industry IT standard terminology LOINC® (Logical Observation Identifiers Names and Codes), based on USCDI to advance interoperability. Once this data is harmonized, then it can be used for care management programs, longitudinal reporting and better patient outcomes.
Providers and payers need access to reliable lab data and other clinical codes to evaluate patient populations and inform decision-making for disease management. The reality is that the quality of the lab data being used today across electronic medical records (EMRs) and other clinical systems to generate analytics is recognized across the industry as an area that desperately needs improvement.
What exactly is being mapped and why?
Consolidating lab data across an entire health system is especially challenging due to the variation in (non-standardized) terminologies used to document in the various databases. For example, one of our large health system clients reported having more than 100 different representations within their data warehouse for documenting the A1C test for diabetes, of which none were mapped to LOINC.
Without a framework in place to ensure lab data is normalized to this industry standard, healthcare organizations run the risk of negative downstream impacts including:
- Inaccurate, skewed metrics for reporting quality measures
- Missed opportunities for reimbursement due to invalid codes
- Misinformed population health strategies
- Compromised patient safety due to unrecognized care gaps
- Compliance risks
How a data quality solution can help
When it comes to data quality strategies, the business case for leveraging an infrastructure that automates the mapping process for labs is an easy one to make due to the sheer volume of data that exists. The Health Language data quality solutions combine the efficiency of machine learning with the deep clinical knowledge of our industry experts to help organizations address the burdensome, error-prone processes often managed across numerous spreadsheets and departments.
Specifically, our web-based Map Manager application allow healthcare organizations to collaboratively map local, proprietary, and standard data and distribute in real-time across the enterprise. Clinical auto-mapping powered by domain-specific algorithms ensure the highest map rates and accuracy, and dashboards alert teams to maps that require manual review.
In addition to standard and proprietary maps, the Wolters Kluwer Health Language experts are available to help organizations design custom maps based on specific needs.
LOINC code mapping use cases
Driving population health initiatives
One of the largest HIE networks in the U.S. leveraged the Health Language data quality solutions and services to map general lab data to LOINC in order to expand reporting and public health visualizations. This framework empowered the HIE's clients with key insights to drive successful population health initiatives around high-value health indicators and high-profile disease states such as diabetes.
Improving data quality and HEDIS® measures
A large payer organization covering 13 million lives is leveraging the Health Language data mapping services to map lab results to CPT® and LOINC codes in order to improve data quality in a longitudinal health record, as well as ensure the organization’s proprietary reports contain proper HEDIS® measures to avoid any compliance issues.
Drive alerts within clinical surveillance solutions
Wolters Kluwer has several health IT vendor clients who rely on the Health Language data quality solutions to improve mapping of labs within their own platforms.
One client leverages the Health Language mapping algorithms within a clinical surveillance solution to identify state reportable conditions mandated by law. The solution must normalize lab and medication data coming from 325 unique hospitals and a variety of EMR systems to drive alerts of these conditions at the point-of-care and ensure care compliance. This process would be near impossible without an automated system in place to do this kind of mapping.
As demonstrated through these examples, the right lab data mapping strategy, powered by an advanced data normalization solution, delivers significant value across a wide variety of use cases. Speak to a Health Language expert to learn more about how our data quality solutions can empower your interoperability needs.
Be sure read our second installment in this data mapping series, where we will explore the challenges and opportunities of medication mapping.