In the workers’ compensation claims administration process, medical and indemnity losses are affected by a number of factors related to the individual claimant, including demographic and socioeconomic factors, employment, injury, medical conditions, and treatments. In the past decade, predictive modeling has become increasingly important as a key decision-support tool in the management of workers’ compensation claim costs, driven in part by the combination of the following industry and societal trends:
- Workers’ compensation medical inflation has been consistently higher than general inflation. In addition, the medical inflation rate varies significantly by provider type (hospital, physician, pharmacy).
- Cost is shifting from healthcare to workers’ compensation.
- Employees are living longer with more chronic diseases. Conditions such as diabetes, obesity, and heart disease can complicate treatments and recovery from a work-related injury, creating more variability and uncertainty in indemnity and medical losses. As the average age of the workforce increases, this issue will affect workers’ compensation costs even more than in the past.
- Effective medical management plays a key role in reducing medical costs and shortening the duration of claims.
Better treatment and reduced costs
By combining claim data with detailed medical transaction data, predictive models can supplement the claims administration process to estimate and score an injured worker’s propensity for high future medical costs. This allows companies to more quickly identify injured workers who are at risk for high medical cost and utilization, to provide them more appropriate and effective medical treatment, and to manage medical providers more closely. Ultimately, this reduces workers compensation costs.
A comprehensive approach that brings together actuarial, clinical, and claims expertise is the key to deriving the most value out of predictive models, and to lowering medical costs. The Milliman approach includes: