Session ID: 
275

Machine Learning and Big Data to Drive Patient Engagement and Better Health Outcomes

9:00pm - 10:00pm Thursday, March 8
Las Vegas - Venetian Convention Center
Marcello 4405

Description

For many years, companies in the retail, telecom, insurance, and banking industries have used machine learning techniques to analyze terabytes of real-time data representing a wide range of customer interactions (across all channels), demographic characteristics, and lifestyle events. This session will explain how CIGNA has leveraged some of the machine learning techniques used to influence consumer behavior in other industries for their own purpose of influencing consumer behaviors towards lower medical costs and better healthcare outcomes. One example to be discussed is how they used a combination of claim data, demographic data, lab data, call center data, and click-stream data from web-interactions and mobile phone interactions to improve the timing, channel, and content they use to engage members with chronic conditions in coaching that lowers medical costs and improves healthcare outcomes for those patients.

Learning Objectives: 

  • Recognize opportunities to use machine learning to increase patient/consumer engagement
  • Analyze customer interaction data to identify ways to reduce total medical cost
  • Apply machine learning and big data techniques to improve health outcomes for patients and customers

Speaker(s): 

o Senior Director of Customer Engagement and Experience Analytics,
Cigna
Principal,
EY
Continuing Education Credits: 
AAHAM
1.00
ABPM
1.00
CAHIMS
1.00
CME
1.00
CNE
1.00
CPHIMS
1.00

Audience: 

Clinical Informaticists
Healthcare Financial Professionals
IT Professional

Level: 

Intermediate