Management Consulting
Aon
Full Credential Description
In the face of rising healthcare costs and increasing employee expectations, a professional services firm faced a significant challenge: 17% of its employees were categorized as high-risk claimants, with annual claims exceeding $2,000. Without intervention, predictive models indicated that this percentage could rise to 25.1%. Alarmingly, over 50% of those predicted to become high-cost claimants were identified as 'emerging risks'employees who had not previously generated significant claims. A particular concern was the trend of musculoskeletal (MSK) conditions among males and females aged 3049, who had not yet triggered high claims but were trending in that direction. To address these issues, Aon implemented its Health Risk Analyzer, which utilizes AI and machine learning to forecast emerging health risks by analyzing both employer data and broader market intelligence. This tool enabled HR leaders to identify at-risk cohorts before they generated claims, model likely outcomes, and shift decision-making from reactive to proactive. For instance, the predictive model allowed the firm to target interventions specifically at the demographic showing signs of potential MSK issues, such as physiotherapy programs and ergonomic training. The results of implementing the Health Risk Analyzer were significant. By using the insights gained from the predictive analytics, the firm projected a modest 2% reduction in claims trends. While this may seem small, it represented substantial savings over time, especially against a backdrop of 14% inflation. Additionally, the insights provided a clearer view of the workforce's underlying health state, which could inform strategies related to productivity, absenteeism, and succession planning. This proactive approach not only aimed to reduce insurance premiums but also enhanced overall employee wellbeing and engagement, ultimately leading to better talent retention and a more effective benefits strategy.