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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:
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:
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