Systematic Review of the Impact of Worksite Wellness Programs

Objectives:

To analyze the impact of worksite wellness programs on health and financial outcomes, and the effect of incentives on participation.

Methods:

Sources were PubMed, CINAHL & EconLit, Embase, Web of Science, and Cochrane for 2000-2011. We examined articles with comparison groups that assessed health-related behaviors, physiologic markers, healthcare cost, and absenteeism. Data on intervention, outcome, size, industry, research design, and incentive use were extracted.

Results:

A total of 33 studies evaluated 63 outcomes. Positive effects were found for threefourths of observational designs compared with half of outcomes in randomized controlled trials. A total of 8 of 13 studies found improvements in physical activity, 6 of 12 in diet, 6 of 12 in body mass index/weight, and 3 of 4 in mental health. A total of 6 of 7 studies on tobacco and 2 of 3 on alcohol use found significant reductions. All 4 studies on absenteeism and 7 of 8 on healthcare costs estimated significant decreases. Only 2 of 23 studies evaluated the impact of incentives and found positive health outcomes and decreased costs.

Conclusions:

The studies yielded mixed results regarding impact of wellness programs on healthrelated behaviors, substance use, physiologic markers, and cost, while the evidence for effects on absenteeism and mental health is insufficient. The validity of those findings is reduced by the lack of rigorous evaluation designs. Further, the body of publications is in stark contrast to the widespread use of such programs, and research on the effect of incentives is lacking.

(Am J Manag Care. 2012;18(2):e68-e81)Because of the emphasis the Affordable Care Act places on worksite health promotion, employers have increasingly offered worksite wellness programs, but little research has evaluated the current impact of these programs.

• We analyzed a total of 33 studies published since 2000 that evaluated the characteristics, impact, and incentives of worksite wellness programs.

• Studies suggest mixed impact on health-related behaviors and cost, with insufficient evidence for effects on absenteeism and mental health.

• Lack of rigorous evaluation designs reduces the internal validity of these findings.

Employers have increasingly offered worksite wellness programs to employees and their families to decrease their cost of providing healthcare coverage and improve their employees’ productivity. The goals of these programs are to promote healthy lifestyles and prevent disease with educational (eg, diet counseling) and motivational (eg, provision of incentives for lifestyle changes) approaches. ¹ In 2009, 58% of US employers offered at least 1 wellness program.² In 2010, consumer participation in programs rose from 19% to 22%.³ This trend is likely to accelerate, as the Patient Protection and Affordable Care Act emphasizes prevention.⁴ The law provides wellness program start-up grants for small firms, establishes a 10-state demonstration program to reward program participation, and establishes technical assistance for evaluating programs. The law also gives employers greater latitude in rewarding staff for healthy lifestyles by raising the rewards for program participation. The limit, set at 20% of the cost of coverage, will increase to 30% in 2014, and the secretaries of Health and Human Services, Labor, and the Treasury will jointly have the authority to raise it as high as 50%.

Reflecting their growing importance, several reviews of worksite wellness programs and their components have been published. Baicker et al⁵ assessed the impact of 32 programs on medical costs and absenteeism that were published since 1982 and found that programs typically return 3 dollars for every dollar invested, which is consistent with other research suggestive of savings.^1,6-9 Other studies have found positive effects as well,^10-12 including evidence for certain components of wellness programs (eg, health risk assessment).¹³

Despite these findings, a review is needed on the current impact of wellness programs to examine how employers have responded to current policy and programmatic priority changes. We conducted a systematic review of wellness programs to understand:

• What are the characteristics of the worksite wellness

programs?

• What impact do programs have on outcomes?

• What types of incentives are provided for program uptake and what is their impact?

This review contributes to the evidence base in several ways. We considered outcomes beyond medical cost and absenteeism to include behavior change and health effects. Only studies with a comparison strategy were included, to maximize validity of the findings. We also limited our scope to studies about comprehensive programs that were published after 2000 to yield a more accurate reflection of current programs. Finally, we looked at the use of incentives for program uptake.

METHODS

Data Sources

Appendix

We conducted a keyword search covering PubMed, CINAHL & EconLit (EBSCO), Embase, Web of Science, and Cochrane from January 2000 through June 2011 (see the ). Additional articles were identified through reference searches of recent literature reviews or meta-analyses.

Article Selection

Articles were included if they had a control or other comparison group and evaluated outcomes of comprehensive worksite wellness programs (ie, multiple wellness components focused on health promotion or disease prevention). We excluded opinion and theory articles, reviews, articles without a comparison group, non-English language and non-US articles, articles published before 2000, and articles that focused exclusively on disease management.

Two investigators (KCO, KVB) independently evaluated articles for inclusion based on title and abstract review, and then full text review. A third investigator (SM or CS) served as tie breaker in case of discrepancy.

Data Extraction

We extracted type of intervention, setting, and research design from each study. Programs and worksites were classified by type, size, and industry.¹⁴

We categorized the quality of the design using methods adapted from previous meta-analyses^15,16: controlled trials with random assignment, prospective studies with nonrandomly assigned comparison groups, and observational designs with internal comparison groups (eg, participants vs nonparticipants).

RESULTS

Identification of Evidence

We identified 1546 articles from our search and 9 through bibliography searches of review articles (Figure). We excluded 1492 upon title and abstract review. A total of 62 full-text articles were assessed for eligibility; 29 were not eligible (eg, noncomprehensive programs, international, no comparison), yielding a final sample of 33 articles.

Sample Characteristics

Of the 33 studies, 22 reported company size (Table 1); 8 studies were done in medium-sized companies, while only 1 reported on a small worksite. Of the 33 studies, 29 reported the industry. About half were conducted in companies that provided services, which is comparable to the distribution of industries in the overall economy.

Program modality varied substantially, as 31 studies reported multiple delivery methods (23 reported 3 or more). The most common modality was self-help or educational materials and/or individual coaching or counseling.

Program Outcomes

Table 2

A total of 63 outcomes were evaluated between the 33 studies (). The most common were exercise (n = 13), diet (n = 12), and physiologic markers (n = 12). Others reported on healthcare cost (n = 8), smoking (n = 7), alcohol use (n = 3), absenteeism (n = 4), and mental health (n = 4). The majority of studies (64%) used self-reported data for at least 1 outcome. About three-fourths of the observational designs reported beneficial outcomes compared with about half of the randomized trials.

Program Impact

Table 3

provides a detailed description of the outcomes and data measured in each study.

Exercise. Thirteen studies evaluated exercise and 8 (62%) found improvements in physical activity. Of these 8 studies, 3 were randomized control trials (RCTs)^21,39,43 and 5 utilized a control group with nonrandom assignment³⁴ or observational designs.^25,27,31,41 All 4 that utilized observational designs showed positive effects on exercise, whereas only 3 of the 7 RCTs found a beneficial effect. Only 1 of these 3 RCTs had a follow-up period longer than a year and a sample size larger than 100.²¹

Of the 8 studies with positive effects, 4 showed substantial changes, such as employees being twice as likely to exercise²⁷ and increasing walking by 103 minutes a week.⁴³ Two others had smaller effects^21,25 such as improved exercise frequency, but no improvements in aerobic activity.²¹ Two studies did not report the magnitude of the impact.34,41 Half of the 13 studies had follow-up periods of less than 1 year, and the maximum follow-up period was 4 years.

Diet. Of the 12 studies that evaluated diet, 6 (50%) found improvements in diet^{21,22,26,27,34,41} including higher fruit and vegetable consumption and lower fat and energy intake. Of these 6, 3 utilized an RCT,^21,22,26 2 of which had a follow-up period longer than a year.^21,49 One study had a nonrandom comparison group⁴¹ and 2 had an observational design.^27,41 A total of 2 of the 3 studies with observational designs and 1 of the 2 studies with a nonexperimental comparison group found improvements in diet, while fewer than half of the studies with RCTs found significant effects. Overall, effects were small, such as an increase of 0.7 servings of fruits and vegetables per day21 or an average of 0.2 fewer fast food meals per week.²⁶

Physiologic Markers. Twelve studies evaluated physiologic markers such as body mass index (BMI), cholesterol levels, and blood pressure. Six of these found improvements in 1 or more outcomes, including BMI or weight,^{19,31,34,41,44,45} diastolic blood pressure,⁴¹ and body fat mass.⁴⁴ Effects included decreases in BMI by 0.04 kg/m2 among program participants,³⁴ 4.3% reduction in BMI,⁴¹ and 1% reduction of diastolic blood pressure.41 Of these 6 studies, 3 used an RCT^19,44,45 and 3 used a nonexperimental comparison group³⁴ or an observational design.^31,41 None of the RCT studies showing a positive effect had a sample size larger than 100. The 6 studies that did not report a positive impact were RCTs (n = 3) and observational studies (n = 3).

Smoking. A total of 6 of 7 studies found higher quit rates^29,35,40,46 or less tobacco use.^27,41 Two found that approximately 10% more individuals in the intervention group quit smoking compared with the control group^29,40 and another reported participants were almost 4 times more likely to reduce smoking than nonparticipants.²⁷ All RCTs reported positive effects,^29,35,40,46 as did 2 observational studies.^27,41 Of the 4 RCT studies showing higher quit rates, 3 had a follow-up period longer than 1 year. Sample sizes in all studies ranged from about 420 to 1130 in each group.

Alcohol Use. Three studies evaluated alcohol use as an outcome using an RCT design. Two compared a motivational interviewing—based intervention with a no-treatment control group,^18,23 and 1 study evaluated a counseling-based treatment program compared with a no-counseling control group.²⁹ Of the 3 studies, 2 reported reductions in alcohol^18,23 such as decreased drinking on weekends and frequency of intoxication²³ and 0.4 fewer days of alcohol consumption per week.¹⁸ One study found no impact,²⁹ which may be attributed to the small sample size and a 3-year follow-up.

Healthcare Cost. Eight studies evaluated the impact of wellness programs on healthcare cost and all but 1 study¹⁷ found significant decreases. Effects included a reduction in direct medical cost between $176 and $1539 per participant per year.^30,37,38 Other studies took a broader view and found $613 savings when including disability cost savings⁴⁷ and $180 savings when combining healthcare cost and absenteeism. ⁴⁸ Of the 7 studies finding a cost reduction, only 1 study utilized an RCT, which had a follow-up period longer than a year.³⁷ The other studies utilized a nonrandom comparison group^30,32,36,38 or observational designs.^47,48 The study finding no impact on cost also had an observational design.¹⁷

Of the 8 studies, 5 conducted return on investment (ROI) analyses and found returns between $1.65 and $6.00 saved for every dollar invested.^30,36-38,48 These studies included the RCT,³⁷ 3 nonrandom control designs with a follow-up period between 4 and 7 years,^30,36,38 and an observational design with a 7-year follow-up.⁴⁸

Absenteeism. Four studies evaluated absenteeism costs, as defined by the estimated cost of missed workdays. Each of these studies found significant effects, expressed as an ROI of $15.60 per dollar spent,¹⁷ $1350 saved per employee in short-term disability costs,²⁷ 0.1% point risk reduction in illness days,³¹ and $180 saved per participant per year when including healthcare cost.⁴⁸ All 4 studies used observational designs.

Mental Health. Four studies evaluated program impact on perceived mental health²⁰ and stress.^22,27,41 Butterworth et al²⁰ used a nonrandom control design and found that employees receiving the intervention improved their mental health by 3 points on the 12-Item Short Form Health Survey, while control participants had no improvement. Cook et al²² used an RCT and found no significant differences on stress. Ozminkowski et al⁴¹ used an observational design and found that individuals receiving the intervention had a 6.1% risk reduction for stress. An observational study²⁷ found that individuals in a telephone-based health promotion program were 2 times as likely to practice stress management compared with nonparticipants.

Use of Incentives

Table 4

Incentives to encourage program enrollment and participation were common; 23 (70%) of the studies offered incentives (). A total of 10 studies offered incentives for participation, 5 for survey completion, 2 for program enrollment, and 6 for a combination of enrollment, participation, and/or survey completion. Two evaluated the impact of incentives on health-related standards. Herman et al³¹ compared the impact of a virtual wellness program on participants who received a $150 incentive for logging minutes exercised compared with those who did not. Compared with the nonincentivized group, incentivized participants had improvements in health-related behaviors and body weight but not smoking rates. Merrill et al³⁶ found offering financial incentives encouraged employees to participate in wellness activities, but they did not include a nonincentivized comparison group.

DISCUSSION

We analyzed a total of 33 studies published since 2000. Our goals were to examine the characteristics of current wellness programs, evaluate the impact these programs had on outcomes such as health-related behaviors and medical costs, and assess the use and potential impact of program incentives.

Most programs were conducted in the services industry and in medium-sized to large businesses. Most programs utilized self-help and educational materials, and focused on improving health-related behaviors like diet and exercise. Consistent with previous research,^1,6-12 we found that studies mostly report positive impact on outcomes, but only half of these studies utilized an RCT design. Finally, we found that 70% of the programs offered incentives, but only 2 evaluated the impact of these incentives on health behavior outcomes and participation.^31,36

Wellness programs were multifaceted in their delivery and evaluation. It is common for programs to use a combination of self-help and counseling to target several health behaviors. ⁴⁹ All but 2 studies had multiple delivery methods and more than half evaluated several outcomes. Combinations of approaches and outcomes were too heterogeneous to detect patterns by outcome. Future research is needed comparing the impact of different types of approaches or modalities (eg, Web vs printed materials).

While most studies found improved outcomes, our results confirm the concern that programs are often not evaluated with strong research designs.⁵⁰ When evaluations used observational designs, positive effects were found for three-fourths of the outcomes, whereas positive effects were found for only about half of the outcomes evaluated with RCTs. Without an RCT design, a causal effect between the program and outcome cannot be drawn reliably, and nonexperimental designs are more prone to selection bias. Additional limitations of these studies include small sample sizes and short follow-up periods. Only 2 studies had more than 120,000 participants, while others had as few as 50 to 2000 participants. Follow-up was 2 years or less for 70% of the studies, and studies with shorter follow-up tended to show more positive results. For example, 19 of the 29 studies (66%) that reported at least 1 significant finding had follow-up assessments of 2 years or less.^{9,17-23,25,26,31,35,37,39-41,43,44,46} Use of self-reported findings in 21 of the 33 studies may also impact validity, especially if participants were aware of program assignment.

Fifty-five percent of the studies focused on programs that targeted health-related behaviors. About half found improved diet- and exercise-related outcomes, but the effects were small, especially for dietary behavior, or not reported explicitly. Further, fewer than half of RCTs on diet and exercise reported favorable findings. Studies on substance use mainly focused on tobacco use as opposed to alcohol or drug use. While all 3 studies evaluating alcohol outcomes were RCTs, very few studies evaluated programs for early substance use problems.^18,51 Of the 7 tobacco studies with RCTs, 6 had reasonably large samples and meaningful effects. However, these positive effects should be interpreted with caution because findings were either not significant at longer follow-up⁴⁰ or not for all employees (eg, hourly and not salaried workers).⁴⁶ Studiestypically used nonparticipants as a comparison, increasing the risk of selection bias, although 1 study used propensity score matching to adjust for this bias.³⁰ Future studies should control for observable differences between wellness program participants and nonparticipants, and use additional calculations to interpret the strength of program impact.

Despite the volume of studies on healthcare cost and absenteeism published prior to 2000,⁵ only 8 studies met our criteria. Most studies were excluded due to the lack of a comparison strategy. Only 5 studies provided a calculation of ROI, in contrast to previous research^1,5-9 that found a solid body of literature providing evidence for cost savings. This is important because those reviews included predominately older studies, and it is unclear whether the type of interventions and scale of opportunities are comparable to what is observed today. Only 1 of the 7 studies showing costs savings utilized an RCT, making it difficult to determine whether reduced costs and associated behavior change can be fully attributed to the programs. Further, evidence of program impact on absenteeism is limited because all 4 studies used observational designs.

To summarize, the published studies included in our review since 2000 provide mixed evidence for a positive impact of workplace wellness programs on health-related behaviors, substance use, physiologic markers, and healthcare cost, and there is insufficient evidence for effects on absenteeism and mental health. Use of weaker evaluation designs in more than half of the studies limits the strength of the evidence.

We found that incentives were offered in 70% of the studies, but only 2 studies evaluated the impact of incentives on participation and outcomes and 1 of them did not have a nonincentivized comparison group. No studies evaluated unintended consequences of incentives. Thus, the literature does not allow us to assess unintended effects of incentives (eg, on availability and affordability of coverage). Typical incentive amounts were small, ranging from $5 to $150, and some programs tiered incentives depending on level of engagement. Those amounts are well below incentive levels that are commonly used today, which are typically $200 to $400

per person per year.⁵² Further, companies do not appear to be offering incentives close to the ceiling amount specified by the HIPAA Nondiscrimination Requirements.^53-55 Further research is needed on the effect of different levels of incentives on outcomes and health behaviors.

Our study has several limitations. First, we included only English-language studies and their chosen outcomes published in peer-reviewed journals, which may lead to bias because successful interventions are more likely to be published. Second, it is difficult to generalize our conclusions because wellness programs were very heterogeneous, outcomes were not systematically operationalized, and calculations of effect sizes were not consistently reported. Lastly, many studies relied on self-report with the potential of differential recall and reporting.

In conclusion, published evaluations of worksite wellness programs yielded mixed results. The number of publications that met our inclusion criteria is in stark contrast to the widespread use of such programs. Recent industry surveys indicate that employers plan to continue expanding their use of wellness programs.⁵⁶ Thus, a dynamic and innovative industry appears to have outpaced the underlying evidence, a phenomenon already observed for disease management programs. ⁵⁷ Given the great interest in these programs and the emphasis the Affordable Care Act places on worksite health promotion, further research is needed. Future studies will need strong evaluation designs, sufficient follow-up, and adequate power to detect meaningful differences. Lastly, better evidence is needed to understand the impact of incentives for program participation, behavior change, and risk factor reduction.

Acknowledgments

The authors thank Wilma Tilson, PhD, Anja Decressin, PhD, Keith Bergstresser, PhD, and Elaine Zimmerman, PhD, for their stimulating and constructive comments on an earlier draft. The manuscript expresses the views of the authors and not official policy of the Department of Labor (DOL) or the Department of Health and Human Services (DHHS).

Author Affiliations: From RAND (KCO), Santa Monica, CA: RAND (KVB, CS, SM), Boston, MA; RAND (JWL), Pittsburgh, PA; RAND (CE), Arlington, VA.

Author Disclosures: The authors (KCO, KVB, CS, JWL, CE, SM) report no relationship or financial interest with any entity that would pose a conflict of interest with the subject matter of this article.

Authorship Information: Concept and design (KCO, CS, JWL, CE, SM); acquisition of data (KVB, CS, JWL); analysis and interpretation of data (KCO, KVB, CS, SM); drafting of the manuscript (KCO, KVB, CE, SM); critical revision of the manuscript for important intellectual content (KCO, CE, SM); obtaining funding (SM); and administrative, technical, or logistic support (KVB, CS, JWL).

Funding Source: This manuscript was developed under contract DOLJ089327414 to the Employee Benefits Security Administration, DOL, and the Office of the Assistant Secretary for Planning and Evaluation, DHHS. The study reflects the opinion of the authors and not official policy of DOL or DHHS.

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