LOINC Code Mapping: Why It Matters

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 Workbench 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 allows healthcare organizations to collaboratively map local, proprietary, and standard data and distribute it in real-time across the enterprise. Clinical auto-mapping powered by domain-specific algorithms ensures 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 the 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 nearly 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.