Welltok launches DataWise to meet healthcare’s Big Data need

Tuesday August 21, 2018 Tags: Denver, Welltok, DataWise, Phil Fiero, Big Data

DENVER -- Welltok announced the launch of DataWise to address the ever-increasing need for Big Data and predictive analytics in healthcare.

DataWise supplements traditional healthcare data with Welltok's proprietary consumer database of 275 million Americans and over 800 predictive variables to create a holistic view of consumers.

The newly released solution analyzes the combined data and delivers enhanced data-sets that improve program targeting, design and messaging, the companies said.

"The healthcare industry spends millions of dollars on analytics solutions and personnel every year, most of which is centered around retrospective information on health and program performance,” said Phil Fiero, Welltok senior VP of analytics and advanced technologies.

“Considering that people spend the majority of their lives outside of the healthcare system, it's essential to leverage consumer data points -- from voter status, property ownership and more -- to understand members at a deeper level and help organizations more effectively target and personalize campaign efforts."

Welltok said it is ideally positioned to supplement data that analytics teams already have, including eligibility, claims and encounter data, with its industry-leading consumer database that features key social determinants of health such as income, household composition and online presence.

By leveraging more robust data-sets and machine learning technologies, Welltok said it helps organizations reveal previously uncovered insights about communication preferences and health behaviors, as well as identify at-risk individuals and operational improvement opportunities.

These insights inform strategic decision-making and help organizations achieve key business objectives such as acquiring new members, reducing re-admissions and improving HEDIS quality scores, the company said.

"We are excited to help more organizations move from basic segmentation at the population level to identifying health needs, risks and target actions at the individual level," added Fiero.

"And, of course, our predictive modeling and machine learning are all done within a private, secure and compliant data infrastructure that is both certified and highly protected.”