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Predictive Analytics Continue to Evolve in Workers' Compensation

by User Not Found | Oct 07, 2015

Four years ago, we began our predictive analytics program by calculating an individual risk score to measure the potential of a claim becoming a high-cost pharmacy claim. Our clinical services team of pharmacists and nurses used these risk scores to prioritize claim intervention efforts following a needs-based triage approach that combined the numbers from the algorithms with the experience of the clinician.

These beginnings evolved into a predictive analytics program predicated on statistical models and the workers’ compensation industry’s largest set of pharmacy data. Data includes specific pharmacy transactional information, basic claim demographics, and incorporates nationally available medical and population database metrics. We measure and weigh these data in statistical models built on decades of experience to show which predictors most strongly correlate to long-term pharmacy cost. It is these generated predictions that allow our clinicians to apply the right clinical resources to the right claims earlier in the claim life cycle, enabling better outcomes both clinically and financially.

Learn more about the evolving use of predictive analytics in workers’ compensation in the article, Data Diving to Improve Comp, recently featured in Risk & Insurance.

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