For instance, the best predictive health analytic solutions are powered by machine learning algorithms that forecast members likely to develop these conditions.

Early identification of risks allows employers to implement preventive strategies, slowing or halting disease progression.
Outreach programs, care navigation partners, condition-specific programs, or expert medical opinion services can be tailored to support at-risk members, providing them with the necessary guidance and resources to maintain their wellbeing.

Moreover, predictive analytics can identify individuals with poorly managed chronic conditions or those with multiple co-morbidities.

For example, by analyzing data on inpatient admissions, readmissions, or emergency room visits for chronic conditions like diabetes, hypertension, angina, or asthma, employers can pinpoint members who are struggling to manage their conditions effectively. This signals that these members are at risk for adverse outcomes and further disease progression.
Predictive health analytic features can flag these risks, enabling employers to implement targeted intervention strategies to slow disease progression and better manage employees with complex clinical profiles.

Strategizing health & wealth: Leveraging predictive analytics to optimize benefit impact

Predictive analytics can also play a crucial role in optimizing benefits spend and mitigating financial risks. By combining the power of financial and clinical data, predictive modeling tools can stratify an employer's population from low to high risk, offering a comprehensive view of their workforce's health needs – from those thriving in wellness to those grappling with acute conditions, chronic diseases, multiple comorbidities, or complex illnesses.

Instant Insights /

Harnessing the power of predictive analytics to contain benefits costs

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