Health Language Blog

Lab Mapping...what the LOINC?!

Posted on 07/10/19

Labs

To kick off our mapping series, our first blog entry will focus on lab data, and will specifically address the following common questions:  

  • Why Is lab mapping important?
  • Why should you (provider/payer) care?
  • What exactly is being mapped and why?
  • How Health Language® Solutions can help
  • Client use cases

Why is lab mapping important?

Today, healthcare organization must code lab data using the industry IT standard terminology LOINC® (Logical Observation Identifiers Names and Codes), which is required for HIPAA, Meaningful Use, and quality measures reporting.

Why should you (provider/payer) care?

Providers and payers need access to reliable lab data to quantitatively evaluate patient populations and inform decision-making for chronic disease management. The reality is that the quality of the lab data being used today to generate analytics is poor and 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
  • Misinformed population health strategies
  • Compromised patient safety due to unrecognized care gaps
  • Compliance risks

How Health Language Solutions can help

When it comes to data normalization 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 Normalization Solution combines 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.

Client Use Cases

Client Example 1: CORHIO, one of the largest HIE networks in the U.S., leverages the Health Language Data Normalization Solution and services to map general lab data to LOINC in order to expand reporting and public health visualizations. This framework empowers CORHIO constituents with key insights to drive successful population health initiatives around high-value health indicators and high-profile disease states such as diabetes.

Client Example 2:  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, as well as ensure the organization’s proprietary reports contain proper HEDIS® measures to avoid any compliance issues.

Client Example 3: Wolters Kluwer has several health IT vendor clients who rely on the Health Language Data Normalization Solution 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. To learn more about how the Health Language Data Normalization Solution can help your organization, contact a Health Language Solutions expert today.

Be sure to look for our second installment in this data mapping series, where we will explore the challenges and opportunities of medication mapping.

LOINC® is a registered trademark of Regenstrief Institute, Inc.
CPT® is a registered trademark of the American Medical Association (AMA).
HEDIS® is a registered trademark of the National Committee for Quality Assurance (NCQA).

Topics: data normalization, interoperability, mapping, quality reporting, Natural Language Processing, Machine learning, clinical decision support, quality measure reporting, value-based care, clinical and claims data, enabling interoperability

About the Author

Ali Gilinger has over eight years of experience in the healthcare industry, with primary focus on product management and strategic product marketing. Prior to joining the Wolters Kluwer Health Language team, Ali was a Solutions Manager for the pharmacy automation division of Swisslog Healthcare. Ali is responsible for strategic product marketing of the complete Health Language solution portfolio.