Predictive Modeling Can Lower Workers’ Compensation Costs

Recent statistics compiled by the National Safety Council revealed that workplace injuries are at an all-time low.  The costs of workplace injuries, however, have escalated significantly over the past five years.  Employers and industry professionals alike are perplexed by this contradiction, and have struggled to find reasons to support such a paradox.

The following are factors that contribute to higher injury costs:

  • Injuries that are typically short-term are dragged out into long-term medical conditions, and often result in larger settlements.
  • According to the report, about 20% of employee injuries account for approximately 80% of claims.
  • There is no consistency in procedure for a claim; two employees with the same injury may see vast differences in claims cost.
  • The occurrence of “catastrophic injuries” is very low, so the problems are resulting from minor, “typical” injuries.

The most common workplace injuries are back and joint conditions, and cumulative trauma.  Statistics show that only three in twenty of these injuries become chronic, and cause a delayed recovery, which occurs when the length and cost of an injury do not correspond with the severity of the illness or injury.  Pre-delayed recovery intervention could be effective in ensuring employees return to work fully after an injury; however, this would not be cost-effective since only three in twenty injuries cause a problem.

The best strategy would be to determine which injured employees are most likely to experience a delayed recovery.  However, a survey to uncover these details would most likely violate an employee’s rights. So how can an employer effectively predict which employees will have a delayed recovery?

Fifty years ago, the banking and credit industries created a way of scoring loan applicants to determine which would be more likely to default. This is called Predictive Modeling, and is still used today. This same system could be applied to predict which employees are most likely to experience a delayed recovery.

There are several factors that could affect an employee’s ability to return to full productivity at work, beyond the medical concern of the injury:

  • Job dissatisfaction
  • History of prior injury or medical issue
  • Education level
  • Length of employment
  • Lack of available modified or transition duty jobs

Based on these common contributing factors, the Institute of Work Comp Professionals developed a database and questionnaire, which an employer answers for each employee after an injury.  Then, a score is assigned to predict the risk level for delayed recovery (Low, Medium, or High). Pre-developed intervention plans are available at each level.

By predicting which employees will be more likely to have a delayed recovery, and by having an established intervention plan, you can protect your company from prolonged absenteeism and lost productivity.

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