CM/DM Propensity to Engage in Different Disease Programs

3AI August 18, 2020

Healthcare company in US

Problem Statement

• Identify enrollees not yet engaged with high likelihood to get themselves engaged in CM Oncology and Disease Management (Diabetes, Heart Failure) programs

Analytics Led Approach

• Developed and implemented an Advanced Analytics driven CM/DM Engagement prediction model
• To identify members who were more/less likely to get engaged in CM/DM
• Stratify members for member outreach to improve response rates.
• leveraged 3rd party demographic and psychographic data in addition to internal client data to develop and implement analytical models for member stratification and identification

Business Impact

• Member Stratification based on Propensity to Engage
• Outreach Target List Generation with ‘More Likely to Engage’ members selected based on the Propensity Scores generated by Logistic Regression model

Critical Success Factors

• Advanced analytical process to identify members high/low likely to Engage
• Ability to pro-actively segment and target ‘More Likely to Engage’ members to ensure increased Engagement while lowering costs