Broker Case Study: Early Risk Prediction Improves Effectiveness of a Musculoskeletal Point Solution

This case study for brokers highlights the transformative potential of early risk prediction for improving financial outcomes and ensuring a healthier, more productive workplace.
The challenge
Musculoskeletal (MSK) conditions, such as back pain, arthritis, and repetitive strain injuries, pose significant challenges for employers, leading to substantial direct medical costs and indirect costs through lost productivity and absenteeism.
In response to these rising costs, many employers are turning to point solutions, but often struggle with low engagement rates, resulting in negative ROI.
The innovative solution
A large employer group in the warehouse business sought to address these challenges by partnering with our innovative analytics platform.
Utilizing Claritev’s proprietary risk prediction model that leverages advanced machine learning techniques, the employer aimed to identify high-risk individuals early, allowing for targeted and effective intervention.
The benefit for brokers and their clients
- Maximize Effectiveness By identifying high-risk members early, tailored interventions can improve both financial and health outcomes.
- Enhance Member Engagement Targeted outreach ensures that the right members receive timely, relevant communications.
- Reduce Costs Proactive management of conditions helps lower both direct medical expenses and indirect costs from lost productivity.
With BenInsightsâ„¢, brokers and their clients can maximize the effectiveness of point solutions, ensuring that the right members receive the right interventions at the right time.
Ready to talk to a member of our team? Contact us today.
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