Background

Health Advocate’s data analytics team developed two AI initiatives 1) a patent-pending enhanced approach using Natural Language Processing (NLP) to transform real-time member interactions into digital information that provides new insights into a member’s health and 2) machine-learning predictive analytics that identify members who likely will be high-cost claimants the following year with an 86% accuracy rate. Both initiatives increased Health Advocate’s ability to quickly identify member health conditions and apply evidence-based interventions to proactively, and more effectively, address gaps in care and other health needs.

Problem

How to proactively use AI to do outreach to members to engage them with their health.

Solutions

1. Collect consent for SMS via app and portal and do automated HIPAA compliant SMS outreach campaigns

2. Automated HIPAA compliant email and push notifications campaigns

Results

• Data-driven notifications from zero to 2.4M annually.

• 20% of recipients took action within a week. 

• 53% of Gaps in Care closed for chronic conditions.

• $1,535 PMPY savings in clinical programs.

• 8% medical trend improvement.

Screenshots