Wolters Kluwer, Health announced it has expanded its Health Language® Interoperability and Data Normalization Solutions to include a suite of services designed to help payers, providers and health IT vendors leverage exponentially increasing volumes of clinical data.
Health Language Data Normalization Services draws on deep terminology management knowledge and clinical expertise that is now powered by machine learning to reduce the time, resources and costs associated with harmonizing data for interoperability and analytics initiatives.
“Integrating clinical data is a real challenge for our clients. For example, we’ve seen clients represent an A1C laboratory test over 100 different ways or manage over 500 representations of aspirin within their medication lists. These variations make it nearly impossible to share, analyze and use clinical data to improve patient outcomes and reduce costs,” said Cheryl Mason, MHSI, Director of Clinical Informatics Consulting at Health Language, Wolters Kluwer, Health. “We help clients overcome these variations by mapping clinical data to standards that power analytics, longitudinal reporting and feed into clinical decision support tools.”
Today’s healthcare organizations increasingly acquire vast amounts of clinical data from disparate sources such as EHRs, practice management systems, laboratories, and pharmacies – each system encoding labs, drugs, and other clinically significant information in a different way. To overcome these widespread interoperability barriers, data must be mapped to industry standards such as LOINC®, RxNorm and SNOMED CT® to support industry initiatives like quality measures reporting, clinical decision support as well as care and disease management programs.
Health Language combines unmatched industry expertise with advanced terminology tools and finely-tuned matching algorithms powered by machine learning. Wolters Kluwer clinical experts—each offering an average of more than 25 years of healthcare terminology experience—partner with healthcare organizations to analyze use cases, create a strategic approach for their unique data normalization challenges and efficiently map disparate data across domains such as labs, medications, allergies, problems, diagnoses and procedures.
“Obtaining quality data remains one of healthcare’s greatest challenges,” said Dan Buell, General Manager of Health Language at Wolters Kluwer. “Our expanded services help healthcare organizations tackle this challenge by building a foundation of normalized data to enable semantic interoperability and enhance reporting and analytics.”
