OBJECTIVE: Certain modifiable risk factors lead to higher health care costs and reduced worker productivity. A predictive return-on-investment (ROI) model was applied to an obesity management intervention to demonstrate the use of econometric modeling in establishing financial justification for worksite health promotion. METHODS: Self-reported risk factors (n = 890) were analyzed using chi2 and t test methods. Changes in risk factors, demographics, and financial measures comprised the model inputs that determined medical and productivity savings. RESULTS: Over 1 year, 7 of 10 health risks decreased. Of total projected savings ($311,755), 59% were attributed to reduced health care expenditures ($184,582) and 41% resulted from productivity improvements ($127,173), a $1.17 to $1.00 ROI. CONCLUSIONS: Using an ROI model to project program savings is a practical way to provide financial justification for investment in worksite health promotion when risk reduction data are available.
OBJECTIVE: Certain modifiable risk factors lead to higher health care costs and reduced worker productivity. A predictive return-on-investment (ROI) model was applied to an obesity management intervention to demonstrate the use of econometric modeling in establishing financial justification for worksite health promotion. METHODS: Self-reported risk factors (n = 890) were analyzed using chi2 and t test methods. Changes in risk factors, demographics, and financial measures comprised the model inputs that determined medical and productivity savings. RESULTS: Over 1 year, 7 of 10 health risks decreased. Of total projected savings ($311,755), 59% were attributed to reduced health care expenditures ($184,582) and 41% resulted from productivity improvements ($127,173), a $1.17 to $1.00 ROI. CONCLUSIONS: Using an ROI model to project program savings is a practical way to provide financial justification for investment in worksite health promotion when risk reduction data are available.
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