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Updated: May 16, 2026

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Reducing the incidence of short-term disability: testing the effectiveness of an absence prediction and prevention
Larry Melton1, Robert Anfield, Gail Kane
1Department of Analytics, Cigna, Raleigh, NC, USA. Larry.Melton@Cigna.com
Objective:
This multi-employer, prospective, randomized, controlled trial validated a quantitative model to identify employees at high risk of short-term disability (STD) and evaluated the impact of a health advocate nurse-led intervention on STD incidence.
Methods:
Following prospective randomization, the control group received usual and customary services while the intervention group received usual and customary plus additional services from Cigna.*
Results:
At the 12-month assessment, 16.8% of the intervention group had documented STD claims compared with 19.8% of the control group (P = 0.06). Duration of STD and return to work rate were not statistically different.
Conclusion:
While not statistically significant, these results suggest that the intervention for employees at high risk of STD achieves practical and clinical significance by achieving absolute and relative reductions in risk of STD of 3% and 15%, respectively.
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