Phone coaching saves $311,755 in health costs

Use this method to compute your own ROI

Demonstrating a program's return on investment (ROI) is more important than ever.

"To sell a program, you need to talk about more than just health outcomes. Business people are also looking for an economic calculation for how it might impact their bottom line," says Ron Goetzel, PhD, research professor of health policy and management at Emory University's Rollins School of Public Health and vice president for consulting and applied research at Thomson Reuters.

Researchers followed 890 employees enrolled for 12 months in a telephone-coaching program for obesity management, and measured 11 key health risk variables including nutrition, fitness, current smoking, former smoking, stress, cholesterol, blood pressure, alcohol abuse, depression, glucose, and body weight.1 At the end of one year, the study found statistically significant reductions in seven health risk factors, including a 21.3% decrease in poor eating habits and 15.1% reduction in poor physical activity. The program saved $311,755, mostly from reduced health care spending costs and improved productivity.

Claims-based ROI studies typically require time and financial resources or skills that are not available or not justified, based on the scale of the intervention, says Kristin M. Baker, MPH, the study's lead author. "Thus, an evidence-based ROI model, such as the one presented in this paper, is an ideal tool for occupational health professionals to use to determine prospective or retrospective ROI in an efficient manner," she says.

Come up with a good estimate

You can use a similar method to establish a potential ROI for a risk reduction program in your workplace. "If you are able to determine what the actual parameters are, then you can plug in that data along with demographic population to come up with an estimate of cost savings. You can then subtract the investment cost to predict the ROI," says Goetzel, one of the study's authors.

If you don't have that information, though, Goetzel says you can make a guess and come up with a good estimate. "Let's say 30% of the population is obese, and you think the program will be able to reduce obesity rates by one percentage point a year. So you would go from 30% obese to 25% obese in five years. You can plug that into the model, along with demographic information, age, gender, and medical costs. It will then predict how much savings you can expect over that five-year period."

The model used by the researchers can do this for 11 risk factors. "This is not easy to do. The foundation for our model is research we did over the last 10 or so years, using a large database that connects risk factors, demographics, and expenditures." Goetzel says.

Even if you don't have access to this type of detailed data, you can begin with studies that link certain risk factors to higher costs. Show how much more it costs to have a stressed or obese employee, for example.2 "You need that basic information to do this kind of calculation," Goetzel says. "But you can do that kind of estimate on your own. Then, refer to research that shows you are able to change risk profile in the workplace.3 And if you change risk, then you save money."


  1. Baker KM, Goetzel RZ, Pei X, et al. Using a return-on-investment estimation model to evaluate outcomes from an obesity management worksite health promotion program. J Occup Environ Med 2008, 50:991-997.
  2. Goetzel RZ, Anderson DR, Whitmer RM, et al. The relationship between modifiable health risks and health care expenditures: An analysis of the multi-employer HERO health risk and cost database. J Occup Environ Med 1998; 4:843-857.
  3. Heaney CA, Goetzel RZ. A review of health-related outcomes of multi-component worksite health promotion programs. Am J Health Promot 1997; 11:290-308.