Online Program

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Saturday, February 16
Sat, Feb 16, 11:00 AM - 12:30 PM
Jackson
Predictive Analysis

Targeting Return-to-Work Intervention by Predicting Prolonged Workers' Compensation Claim (303747)

*Mei Najim, Advanced Analytics Consulting Services, LLC 

Keywords: Claim Analytics, Predictive Modeling, Claim Triage, Machine Learning, Advanced Analytics, Return-to-work Predictive Model

Injured workers being away from work constitutes one of the greatest claim cost drivers. In this case study, a Return-to-Work model is introduced to predict the likelihood that injured workers will stay away from work for longer durations. This model serves to target early interventions, such as proper treatments and return to work programs to assist in returning to work. Such measures reduce claim costs. We explore millions of claims and hundreds of millions of payment records, including myriad variables. Cutting-edge statistical and machine learning algorithms (GLM, Decision Tree, Random Forest, Gradient Boosting, Neural Network, etc.) are utilized, in combination with broad insurance claim business knowledge.