New Wolters Kluwer payer tools boost health data analytics and member satisfaction

Payer analytics teams optimize clinical and claims data for advanced predictive models call center CSRs cut complex jargon for more satisfied members.

Wolters Kluwer, Health announced today two new payer solutions added to the Health Language platform’s reference data management (RDM) capabilities. RDM for Advanced Analytics offers payers cloud-based content, software, and services to power more dynamic, analytics-based strategic planning. To drive member engagement and satisfaction, Code Explorer for Call Centers helps payer customer service representatives (CSRs) reduce health plan member confusion and dissatisfaction by quickly translating complex medical codes and terms into easy-to-understand language.

“Working together with health insurance organizations across the United States, we identified common strategic challenges payers are facing that impact the quality and cost of care,” said Frank Jackson, Vice President and General Manager of Health Language at Wolters Kluwer, Health. “With the Health Language platform, we apply reference data management principles and offer data solutions that enable payers to effectively leverage both clinical and claims data for real-time analytics and enhanced member communications.”

Future-ready payers overcome barriers to advanced analytics

As payers faced unheard of fluctuations in elective care utilization and care venues during the pandemic, historical data became less reliable for forecasting, and more payers started turning to models using real-time data and predictive analytics. According to a recent PricewaterhouseCoopers (PwC) “Top Health Industry Issues of 2021” report, 74 percent of health executives said their organizations would invest in predictive modeling in 2021.

To help payers navigate today’s volatility with critical, forward-looking insights, Wolters Kluwer added the RDM for Advanced Analytics solution to its cloud-based Health Language platform to maximize the value of high quality clinical and claims data. The new toolkit helps payers form a more complete view of patient health by merging claims and clinical data. Unstructured data or non-standard clinical data like labs are normalized to standard terminology such as LOINC for fuller inclusion in analytics. And the most continuously updated reference data is used to push machine learning models to the leading edge.

Predictive analytics: only as good as the data

RDM for Advanced Analytics can be used to improve high value use cases such as population simulations to evaluate the impacts of different interventions. Payers seeking to use real-time data to forecast enrollment churn or changes in medical loss ratios can leverage more optimized data for improved accuracy, context, and insights. With skyrocketing demand for virtual care and remote patient monitoring, payers are also pressing clinical and claims data for indicators of changes in demand so that capabilities are aligned.

More than nine out of ten payers surveyed by the Society of Actuaries rated predictive analytics as important for the future of the industry. RDM for Advanced Analytics ensures claims data, EHR data, lab data, prescription choices, and unstructured data can all be harnessed to propel payers beyond traditional analytics to machine learning artificial intelligence (AI) models.

Less jargon means happier health plan members and better call center metrics

Customer service representatives at health insurance call centers are on the front lines of communication with members who often need help understanding an obscure term or code in their bills, explanation of benefits (EOB) or health insurance portal. Health Language Code Explorer for Call Center equips CSRs with a simple and easy to use code search so they can avoid jargon and answer consumer questions with plain, easy-to-understand language.

With a smart online lookup tool for codes, common descriptions, synonyms, acronyms and even misspellings, CSRs can spend precious call time answering member questions with layperson terms instead of trying to decipher complex medical or coding jargon. Code Explorer targets call centers’ operational goals by increasing performance metrics like first call resolution, average handling time, call duration, quality assurance, net promoter score, and other industry standard metrics.