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Managing Risk in Workers’ Comp: The Value of Predictive Analytics

Posted by Michelle Despres on January 2, 2017 at 12:16 PM


Today’s guest, Michelle Despres, shares with us what predictive analytics is all about. Among the topics of discussion are the importance of predictive analytics, why it is trending in organizations today, and its role in claims management.

Predictive analytics utilizes many techniques to analyze data points to predict future events. This aspect permits organizations to become proactive and anticipatory of employee behavior, resulting in a useful tool for handling increasingly trendy and expensive workers’ compensation claims.

Predictive Analytics helps organizations with employee issues such as obesity, aging, injuries, etc., in turn reducing costs and managing outcomes. For example, a number of professionals know when a claim can become costly but don't have the data to identify these claims as bad claims. Predictive analytics provides the data that stops or manages these potentially bad claims and prevents them from becoming very expensive.

Benefits of Predictive Analytics Programs

The benefits of collecting data with P.A. programs help organizations in the following ways:

  • By identifying the most objective way to allow for better management of claims.
  • By helping organizations understand what is happening, what is causing the event, and the best way to manage the event.
  • By allowing organizations to make substantial savings, calculations, and outcome measurements.
  • By giving organizations the opportunity to apply the right resources at the right time.
  • By helping organizations get in front of claims proactively.

The data received from P.A. helps reduce the risk of re-injury for employees returning to work as it improves the return to work outcome, controls rising costs, and allows for tighter claims management.

The data also helps organizations foresee claims before they become bad and assists in promoting an efficient medical management approach.

An example of P.A. recognizing a bad claim is a situation whereby a certain department or category of workers in a company developed hand and wrist injuries. The predictive analytics data can help determine the cause of the injuries, how they happened, and the best approach to managing the situation to prevent further reoccurrences.

Tips for Organizations that Want to Begin Implementing Predictive Analytics 

  • Start with the end in mind: The objective of the P.A. should be ascertained before you delve into it.
  • Beware of data leakage.
  • When you have a claims management dilemma, start with the most expensive and frequent claims.
  • Determine what action should be taken on identified cases in a timely manner.

How to Measure a Successful Predictive Analytics Program

A critical factor for successful predictive analytics is a well-defined set of business performance metrics specific to the organization’s business objectives. These metrics should include:

  • An increase in return-to-work outcome.
  • A decrease in overall claims by employees.
  • Reduction in hidden claims.
  • Cost reduction with regards to injuries, etc.