3 Ways that Data Can Positively Influence a Catastrophic Claim
When employers, carriers and TPAs commit to utilizing predictive analytics, they are better positioned to identify claims with severity risk earlier. This allows for early intervention, mitigation and better overall outcomes. All parties involved benefit, including the injured worker, their family and the employer.
August 29, 2022
Data can help mitigate the costs associated with a catastrophic claim, but more important, it can be an extremely effective tool in developing strategies for the injured worker’s care. Tracking the progress of like claims with the same characteristics can help identify why one resource may work better than another and recognize which resource might work best for similar injuries. Predictive analytics may not predict future results, but the data can certainly help make more informed decisions in care, leading to better outcomes for injured workers.
“As the science continues to mature, the accuracy of predictive models will improve, providing better forecasting that is more effective at identifying those at-risk claims for intervention,” said Patrick Hiles, Vice President – Workers’ Compensation Claims at Safety National. “Knowing that analytics help with strategy and mitigation efforts, the industry will continue to invest in building future model iterations with further predictive power and value.”
These are just a few ways that data can impact a catastrophic claim and provide a drastically better outcome for the life of an injured worker.
1. Engaging in Early Intervention & Advocacy
Enabling the best possible outcome for a catastrophically injured worker requires early intervention, but without knowing the severity of the injury, how do you assess the employee’s needs? Early understanding and predictive modeling can identify claims with either slow-emerging developmental or immediate severity, ensuring the appropriate care. This data can estimate long-term risks and identify the resources needed to manage the claim. Early intervention also allows for earlier advocacy, knowing that the injury will likely impact an employee’s family and livelihood.
2. Assigning Medical Resources
Data that provides a better understanding of the injured worker’s pain perception, coping skills, return to work expectations, current diagnosis and existing treatment plan can ensure that they receive the appropriate medical management and course of treatment. These analytics can help determine the right specialists for treatment and which nurses have the expertise to properly engage with adjusters, employers and injured workers to ensure the best possible care while helping the claim progress. Overall, these resources can provide a better prognosis in the long term and benefit all involved stakeholders.
3. Identifying Individual Risk Factor Trends
Essential details like age, prior injuries and co-morbidities can aid in more accurately determining the severity of the claim. Individuals with preexisting health conditions, like diabetes, high blood pressure, previous drug or opioid addiction, and psychosocial challenges, should be identified early. Factoring these comorbidities into the treatment plan can provide opportunities for the most optimal outcomes. Understanding these factors can also allow insurers to appropriately incentivize risk reduction.