February 2008 // Volume 46 // Number 1 // Tools of the Trade // 1TOT4

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Calculating the Economic Impact of Health Education Programs: Five Tools for Extension Educators

Abstract
Evaluation of Extension health/wellness programming often focuses on positive changes in participants' health practices and changed health status. Increasingly, stakeholders and funders are also requesting analyses of the economic impact of health education programs. In an era of heightened accountability, there is also pressure to compare program costs and benefits. Unlike financial management programs that have built-in economic indicators, health education program impacts must often be calculated indirectly. This article describes five methods to quantify the economic impact of health education programs: participant surveys, time value of money analyses, extrapolation from published cost estimates, cost-benefit analyses, and return on investment.


Barbara O'Neill
Extension Specialist in Financial Resource Management
Rutgers Cooperative Extension
New Brunswick, New Jersey
oneill@aesop.rutgers.edu


Health/wellness programming is an important component of many Extension family and consumer sciences (FCS) programs and includes topics such as childhood obesity, physical activity, and diabetes. Impact evaluation often focuses on positive changes in participants' health practices (e.g., increased daily exercise) and changed health status (e.g., reduction in weight or body mass index).

Increasingly, stakeholders are requesting analyses of the economic impact of health education programs in addition to changes in the health status of participants. There is also pressure to compare program costs and benefits. Unlike financial management programs that have built-in economic indicators (e.g., increased savings), health education programs impacts must often be calculated indirectly. Following are five methods to quantify the economic impacts of health education programs.

Survey Program Participants

One way to assess financial impacts of health education programs is to ask participants directly. Historically, health and financial literacy initiatives have proceeded on parallel tracks with separate literature, programs, and advocacy efforts (Vitt, Siegenthaler, Siegenthaler, Lyter, & Kent, 2002).

This is changing with the use of interdisciplinary programs such as Small Steps to Health and Wealth™ (SSHW), which encourages participants to make positive behavior changes to simultaneously improve their health and personal finances. On evaluation surveys that SSHW participants complete semi-annually are questions about how their health status has affected their finances and vice versa. Qualitative data about financial impacts of health education programs can complement quantitative impacts described below. Respondents are also asked to estimate a dollar value for improved health practices, which can be compared with time value calculations.

Time Value of Money Analyses

The time value of money has been described as "the single most important concept in personal finance" (Garman & Forgue, 2006, p. 16) and involves calculations of a lump sum or series of deposits in different time periods. Time value of money calculations can be used effectively to determine financial impacts of health programs.

One example is a present value calculation for economic impact of the delayed onset of diabetes resulting from an effective health education program. Delaying health care expenses is a major financial impact for both participants and employers. Present value is the current value of money that will not be spent on health care in a series of future payments. To do an accurate calculation, you need a reliable estimate of annual health care costs and lost wages for people with type 2 diabetes and conservative estimates of the number of positively impacted individuals and their average age relative to the mean age of diabetes diagnosis, which is now 46 (Koopman, Mains, Dia, & Geese, 2005). Add in a conservative discount rate and the calculation is complete.

Here is an example. Health care costs for a person with diabetes are $13,243, compared to $2,560 for people who don't have diabetes (Study Shows, 2003), a difference of $10,683. Suppose the average age of program participants is 40 and a 5% discount rate is assumed. If a realistic one-fifth (200) of 1,000 program participants, based on those who are at risk for developing diabetes and able to delay its onset with a healthy diet and exercise (Rice & McCorkle, 2005), push back the age of diabetes onset 6 years and avoid $10,683 of increased annual medical costs, the financial benefit is (N = 6 years, %i = 5, present value of annuity factor = 5.2421) $10,683 x 5.2421 or $56,001 per person x 200 = $11,200,271! Furthermore, it is estimated that people with diabetes complications pay almost $1,600 out-of-pocket for costs that are not reimbursed by insurance, such as deductibles and co-payments (The Surprisingly High Cost, 2007). A conservative future value calculation could also be done of participants' potential savings if money required for diabetes expenses not incurred is invested.

Extrapolation from Published Cost Estimates

Another way to calculate economic impact from health education programs is extrapolations from reliable estimates of the dollar savings of improved financial practices using a technique known as "shadow pricing" (Richardson, n.d.). For example, according to the U.S. Department of Health and Human Services, a 10% weight loss will reduce an overweight person's lifetime medical costs by $2,200 to $5,300 (Preventing Chronic Diseases, 2003). Using simple math with the lowest dollar figure of this range, if 500 participants each lost 10% of their body weight (e.g., 16 pounds from 160) following a health education program, the economic impact is $1,100,000.

A study by Andreyeva & Sturm (2006) found that regular physical activity by adults age 54 to 69 was associated with reduced health care costs of $483 annually. Additionally, studies have found effects of women's body mass on their socioeconomic status. Conley and Glauber (2005) found that a one percent increase in body mass index or BMI (e.g., from 25 to 25.25) results in .6 of a percentage point decrease in family income. Findings such as these can inform computations of economic impact.

Cost-Benefit Analyses

Cost-benefit analyses also provide perspective on the impacts of health education programs. The costs of program inputs (Logic Model, n.d.), such as staff and supplies, are divided into calculated economic benefits. The larger the dollar value of benefits relative to program costs, the better (O'Neill & Richardson, 1999). For example, using the weight loss program with $1.1 million of economic impact cited above, if it costs $200,000 to deliver the program, the cost-benefit ratio is 5.5 to 1 or $5.50 of economic benefit for every $1 spent to implement the program.

Return on Investment Calculations

Return on Investment (ROI) calculations are commonly used in the business world. The formula is:

In the above example, the ROI would be 4.5 ($900,000 divided by $200,000) x 100 or 450%. This means that, even after all program costs are subtracted, the program generated $4.50 in net benefits for every $1 invested. As with cost-benefit ratios, the higher the ROI multiple, the more impressive the economic impact.

Summary

It has been said that "money talks." This article described five ways to calculate the economic impact of health education programs. Framing improved health practices on program participants in financial terms can help improve accountability and meet demands of stakeholders for economic analyses.

References

Andreyeva, T., & Sturm, T. (2006). Physical activity and changes in health care costs in late middle age. Journal of Physical Activity and Health, 3, S6-S19.

Conley, D., & Glauber, R. (2006, May 19). Gender, body mass, and economic status. National Bureau of Economic Research Working Paper No. 11343. Retrieved May 19, 2006 from http://papers.nber.org/papers/W11343.

Garman, E. T., & Forgue, R. E. (2006). Personal finance. Boston, MA: Houghton Mifflin Company.

Koopman, R. J., Mains, A. G., Dia, V. A., & Geese, M. E. (2005). Changes in age at diagnosis of type 2 diabetes mellitus in the United States, 1988 to 2000. Annals of Family Medicine, 3(1), 60-63. Retrieved April 26, 2007 from: http://www.medscape.com/viewarticle/4988563_print

Logic model (n.d.). University of Wisconsin Extension. Retrieved April 27, 2007 from: http://www.uwex.edu/ces/pdande/evaluation/evallogicmodel.html.

O'Neill, B., & Richardson, J. G. (1999). Cost-benefit statements: A tool for Extension accountability. Journal of Extension [On-line], 37(4). Available at: http://www.joe.org/joe/1999august/tt3.html

Rice, C. A., & McCorkle, D. (2005, December). Planning effective programs with significant outcomes and economic impacts. Paper presented at the National Urban Symposium: Youth and Family Wellness, Dallas, TX.

Richardson, J. G. (n.d.). Developing cost and benefit estimates. North Carolina Cooperative Extension Service. Retrieved September 6, 2005 from: http://www.ces.ncsu.edu/AboutCES/Factsheets/benefits.html.

The surprisingly high cost of diabetes (2007, April 11). U.S. News and World Report. Retrieved April 26, 2007 from: http://www.usnews.com/usnews/health/articles/070411/11health.diabetes.htm.

U.S. Department of Health and Human Services. (2003). Preventing obesity and chronic diseases through good nutrition and physical activity. Preventing chronic diseases: Investing wisely in health. Washington DC: U.S. Department of Health and Human Services. Retrieved October 28, 2004 from: http://www.healthierus.gov/steps/summit/prevportfolio/PA-HHS.pdf

U.S. Department of Health and Human Services (2003). Study shows sharp rise in the cost of diabetes nationwide. Washington, DC: U.S. Department of Health and Human Services. Retrieved February 25, 2008 from: http://www.hhs.gov/news/press/2003press/20030227a.html.

Vitt, L. A., Siegenthaler, J. K., Siegenthaler, L., Lyter, D. M., & Kent, J. (2002, January). Consumer health care finances and education: Matters of values. Issue Brief Number 241. Washington DC: Employee Benefit Research Institute.