HCMS Human Capital Risk Index® (HUI) Outperforms Competitor


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HCMS Group recently had the opportunity to compare its integrated risk score, the Human Capital Risk Index® (HUI), against a traditional risk score that only includes health plan data. The HUI’s use of a broader set of integrated lost time metrics (including disability data) produced a prediction of high cost and risk that averaged out to be nearly twice as strong when compared to the competitor risk score.

The full study includes background information, tables, graphics, and detailed findings. Click here to read the full study.

Figure 1: Employee HUI and Competitor Risk Score Comparison

* The metric displayed is the coefficient of determination (or R2) as measured from the linear relationship between HUI (or the Competitor Risk Score) and total cost.
** The metric displayed is a pseudo R2 as measured from the logistic relationship between HUI (or the Competitor Risk Score) and the likelihood of being high cost.
R2 is a statistical measure used to access the predictive power of a given model with a range of 0-1; the higher the number, the more powerful and accurate the prediction.

 

HCMS Group’s Human Capital Risk Index® Background Information

The HUI is more comprehensive than other risk measurements due to the scope of integrated data (health, disability, workers’ compensation) and is closely correlated with health benefit costs. The HUI also uses three distinct algorithms to calculate risk—one for employees, one for adult dependents, and one for child dependents. This customization to the specific population group also contributes to a higher level of predictive power.

The HUI is weighted by the following elements:

  •   Clinical diagnostics and patterns of utilization captured in medical claims
  •   Pharmacy classes and patterns of utilization captured in pharmacy claims
  •   Short-term and long-term disability claims information
  •   Workers’ compensation claims information

 

Have any questions about this study? Leave a comment and an HCMS Data Analyst will reply.


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