Article on wellness program

However, Wein noted that ways exist for a company to implement a program without causing a massive cost for the organization. Employees go to the health coaches and our resilience coaches not to just waste time, they come in for very productive conversations. Dec 14th, Nolan Beilstein. A study found individuals with high physical work demands had a significantly lower working life expectancy than those with low physical work demands.

One of the main goals for the wellness program team is pinpointing areas that require focus. Moreover, we found that participants did not have lower preintervention spending than nonparticipants, although there was selection on other dimensions. Unlike the Illinois study, this intervention was implemented at the worksite level rather than varying across individuals within the same worksite , perhaps better facilitating changes in workplace culture and providing greater social supports for behavior change.

This intervention was also fielded in a different population, set of geographies, and employment setting, making it difficult to isolate the causes of any differences in findings. These findings stand in contrast with much of the prior literature on workplace wellness programs, which tended to find positive and often large returns on investment through, for example, reductions in absenteeism and health care spending. This study has several limitations. First, although this population was diverse, results may not generalize to other workplace settings or populations.

Second, the ability to detect treatment effects was limited by statistical power, despite prespecified strategies to maximize power. This challenge was augmented by our very conservative approach to multiple-inference adjustment, which grouped a wide array of outcomes rather than narrowly construing related outcomes.

It was further limited by employee turnover that restricted the workers present to participate in end-of-study primary data collection, although the mean duration of employment was similar among the 3 groups of the trial Figure , suggesting that entry and exit from the sample was due to natural exogenous employment turnover, not the wellness program.

Third, not all employees contributed data for every outcome. Survey and biometric data were available only for individuals employed at the month mark who chose to participate in primary data collection. However, there was no evidence of differential selection into completing the survey and screening.

Claims data were available only for employees with Cigna coverage, although no data were missing in this sample. Overall, all available data on employees were analyzed; rates of missing data were similar between groups and may thus have affected the precision of estimates but do not seem to have adversely affected the validity of the findings. Fourth, this study was unable to disentangle effects of particular elements of the wellness program, nor assess the effects of a differently configured wellness program.

Rather, it evaluated the program as a package, with implementation that varied only idiosyncratically in small ways across worksites. Such design features are in fact common in most wellness programs. Among employees of a large US warehouse retail company, a workplace wellness program resulted in significantly greater rates of some positive self-reported health behaviors among those exposed compared with employees who were not exposed, but there were no significant differences in clinical measures of health, health care spending and utilization, and employment outcomes after 18 months.

Correction: This article was corrected on April 16, , for data errors in the Abstract and Figure and for omissions to the Additional Contributions section. Author Contributions: Drs Song and Baicker had full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis. Concept and design, acquisition, analysis, or interpretation of data, drafting of the manuscript, critical revision of the manuscript for important intellectual content, statistical analysis, obtained funding, administrative, technical, or material support, and supervision: Both authors.

Conflict of Interest Disclosures: Dr Song reported no disclosures. Dr Baicker reported receiving personal fees from Eli Lilly outside the submitted work and reported serving on the board of directors of Eli Lilly. We thank David Molitor, PhD, and Julian Reif, PhD, University of Illinois at Urbana-Champaign, for guidance on the statistical software for multiple inference adjustment they created in the University of Illinois wellness study, which was used in this study, without financial compensation.

Chan School of Public Health, for research assistance and project management. Chan School of Public Health, for research assistance. Data Sharing Statement : See Supplement 3. Our website uses cookies to enhance your experience. By continuing to use our site, or clicking "Continue," you are agreeing to our Cookie Policy Continue. View Large Download. Table 1. Characteristics of the Study Population a.

Table 2. Table 3. Table 4. Table 5. Supplement 1. Protocol and Statistical Analysis Plan. Supplement 2. Online Section 1: Program Background eMethods 1.

Description of Program Modules eMethods 2. Initial Power Calculations eMethods 3. Statistical Analysis Section 2: Figures eFigure 1. Location of Treatment and Control Worksites eFigure 2. Timeline of the Workplace Wellness Intervention eTable 2. Summary of Outcome Data Collected eTable 3. Pre-Specified Outcomes eTable 4. Characteristics of the Study Population eTable 5.

Average Participation Rates by Module eTable 6. Alternative Definitions of Participation eTable Exposure Weights Only eTable Non-Participants in Program Modules eTable Supplement 3.

Data Sharing Statement. Kaiser Family Foundation. Published October 3, Accessed February 19, Pollitz K, Rae M. Workplace wellness programs: characteristics and requirements. Published May 19, Accessed October 4, A review of the U. RAND Corporation. There were no significant effects on self-reported tobacco use, physical activity intensity, or mood after 12 or 24 months.

The intervention had no significant effects on height, weight, waist circumference, body mass index, blood pressure, cholesterol, or glucose level Table 3. There were also no significant changes in diagnoses of hypertension, diabetes, or hyperlipidemia after 12 or 24 months Table 4. Likewise, no significant effects were found for office visits, inpatient visits, or emergency department visits. Additional analysis also found no significant effects for primary care physician visits eAppendix 5 and eTable 25 in Supplement 3.

Compared with women, men had higher effects on claims-based diabetes diagnoses after 12 months 2. This individual-level RCT of a 2-year comprehensive workplace wellness program demonstrated that the program significantly improved employee beliefs about their own health and increased the proportion of employees reporting that they have a primary care physician.

However, no significant effects were found on biometrics, medical diagnoses, or medical use after 24 months. Our study was powered to detect clinically meaningful effects across these 3 domains. These results complement recent RCT evidence that workplace wellness programs affect some self-reported outcomes but have limited effects on clinical or administrative outcomes. Prior findings showed that the iThrive program increased self-reported lifetime health screening rates and improved employee perceptions of management, but did not significantly affect administrative measures of medical spending.

Our measures of health beliefs, elicited using self-reported subjective probabilities, are a contribution to the literature on wellness interventions. Employees in the treatment group believed they had lower chances of poor biometric health, suggesting that they expected their participation in the wellness program to improve their health. However, there was no significant effect of the program on biometrics or medical use, and prior findings showed no significant effects on administratively measured health behaviors.

Many of these prior studies used observational research designs, which can result in significant selection bias even after controlling for many covariates. This study has several limitations. The results may not be generalizable to other workplace settings with different populations or different wellness programs. Also, the outcomes were measured during the first 24 months after randomization. We do not know whether the significant effects on self-reported outcomes persisted beyond 24 months, or whether detectable effects on biometrics, medical diagnoses, or medical use emerged beyond 24 months.

Finally, data were not available for all study participants. Medical diagnoses and use outcomes were obtained only for participants enrolled in Health Alliance. Biometric and self-reported outcomes were obtained only for participants who completed the onsite screening and survey in or However, Health Alliance enrollment was well balanced between the treatment and control groups Table 1.

Baseline characteristics of participants who completed the onsite screenings and surveys were well balanced between the treatment and control groups eTables 2 and 3 in Supplement 3. The balance between treatment and control groups suggests that bias from missing data is unlikely to be substantial.

Among employees of a large employer, a comprehensive workplace wellness program significantly changed a set of beliefs about biometric outcomes and significantly increased self-reports of having a primary care physician, but no significant effects on clinician-measured biometrics, medical diagnoses, or medical use were found after 24 months. However, we add to a growing body of evidence from RCTs that workplace wellness programs are unlikely to significantly improve employee health or reduce medical use in the short term.

Front and back sides of invitation postcard sent on July 6, Invitation email sent to university employees on July 11, Health screening form used by clinicians to record health measures. Email invitation for the online health risk assessment. One-year follow-up survey reminder sent on August 2, Description of and statistics for the Fall wellness activities.

Description of and statistics for the Spring wellness activities. National Center for Biotechnology Information , U. Published online May Author information Article notes Copyright and License information Disclaimer.

Corresponding author. Received Feb 20; Accepted Mar Copyright American Medical Association. All Rights Reserved. This article has been cited by other articles in PMC. Supplement 2: eAppendix 1. Sample Selection and Study Overview eAppendix 2. Datasets eFigure 1. Overlap Among Datasets eFigure 4. Front and back sides of invitation postcard sent on July 6, eFigure 5.

Invitation email sent to university employees on July 11, eFigure 7. Text of the confirmation email sent to study participants who successfully completed the online baseline survey eFigure 8. Front and back sides of the postcard mailed to participants selected to participate in iThrive, week of September 8, eFigure Login page for the iThrive website eFigure Main home page for the iThrive website eFigure First and second pages of the online appointment application used to sign up for a health screening eFigure Example of a reminder email sent out by the online appointment scheduler eFigure Example of a reminder email sent by the research team to participants one day prior to their health screening eFigure Health questionnaire filled out by participants at the health screening eFigure Health screening form used by clinicians to record health measures eFigure Health coaching guidelines eFigure Postcard given to participants on site after they completing their health screening eFigure Email invitation for the online health risk assessment eFigure Email invitation for Fall wellness activities eFigure Email invitation for Spring wellness activities eFigure Front and back sides of invitation postcard sent on July 6, eFigure One-year follow-up survey invitation sent to study participants on July 10, eFigure One-year follow-up survey reminder sent on August 2, eFigure Text of screening invitation email sent to study participants on August 14, eFigure Text of reminder email sent to study participants on September 21, eFigure Two-year follow-up survey invitation sent to study participants on July 9, eFigure Text of screening invitation email sent to study participants on August 13, eFigure Copy of health screening form used by clinicians to record health measures eTable 1.

Dates, locations, times, and number of health screenings performed in eTable 2. Employers who use incentives for screening activities report significantly higher participation rates than those who do not 63 percent versus 29 percent for HRA completion and 57 percent versus 38 percent for clinical screenings. Using a simulation model, we find that the incentive amount for HRA completion had a significant effect on HRA completion rates.

Data from the RAND Employer Survey indicate that smoking cessation is the behavior that is primarily targeted with incentives tied to health standards. For other behaviors e.

Smoking is also the only health risk behavior for which achieving the goal is rewarded with a higher incentive than participation in a program. Similarly, four out of five case study employers penalized smokers, but only two had incentives tied to other health standards. The peer-reviewed literature indicates that financial incentives may attract individuals to enroll or participate in smoking cessation programs and increase initial quit rates, but they generally do not achieve long-term behavior change Cahill and Perera, ; Osilla et al.

See Figure 7. NOTES: The graph represents information from employers with at least 50 employees that offer a monetary incentive for participation in a lifestyle management intervention or for improving health behaviors. Among employers with lifestyle management interventions, 77 percent target smoking, 79 percent target weight and obesity, and 72 percent target fitness.

With respect to effectiveness, our analyses of employer data in the CCA database imply that incentives for HRA completion and program participation can significantly reduce weight and smoking rates and increase exercise.

However the size of these effects is small and unlikely to be clinically meaningful. Five factors to promote wellness program success emerged from our case study analysis and the literature review:. Effective communication strategies: All five organizations in our case studies employ strategies to communicate wellness program information to employees, ranging from face-to-face interaction to mass dissemination.

Employers cited the importance of broad outreach and clear messaging from organizational leaders, especially for those organizations with a large and geographically dispersed workforce. Opportunity for employees to engage: Those included in the case study discussions revealed that making wellness activities convenient and easily accessible for all employees are strategies that employers use to raise the level of employee engagement.

Some focus group participants cited limited access to wellness benefits because of wait times and rigid work schedules. Leadership engaged at all levels: Evidence from case studies suggests that for programs to be a success, senior managers need to consider wellness an organizational priority to shift the company culture. Buy-in from direct supervisors is crucial to generate excitement and connect employees to available resources. Use of existing resources and relationships: All organizations in our case studies leverage existing resources and build relationships, often with health plans, to expand offerings at little to no cost.

Continuous evaluation: Organizations from our case studies approach wellness with a continuous quality improvement attitude. Though no employers from our case studies conducted formal evaluations, all five solicit feedback from staff with the goal of improving future wellness programming. Three employers conducted needs assessments to develop an understanding of the wellness needs of their workforce. This project represents the most comprehensive analysis of worksite wellness programs to date and evaluates current program participation, program effects, and the role of incentives.

Our project combined a literature review, a national survey of employers, case studies of workplace wellness programs, and statistical analyses of medical claims and program data to assess the current use of workplace wellness programs in the United States, to estimate the effect of programs on employee health and health care cost, and to evaluate the role of incentives in program engagement.

We find that that workplace wellness programs have emerged as a common employer-sponsored benefit that is now available at about half of U. Large employers are more likely than small employees to offer a wellness program and also tend to offer programs with a greater variety of options. Most employers are committed to long-term support of wellness programs, regarding them as a viable strategy to contain health care costs, thereby ensuring the affordability of health coverage.

In spite of their popularity among employers, the impact of wellness programs are rarely formally evaluated. Consistent with prior research, we find that lifestyle management interventions as part of workplace wellness programs can reduce risk factors, such as smoking, and increase healthy behaviors, such as exercise.

We find that these effects are sustainable over time and clinically meaningful. This result is of critical importance, as it confirms that workplace wellness programs can help contain the current epidemic of lifestyle-related diseases, the main driver of premature morbidity and mortality as well as health care cost in the United States. An important question for further research is how program design and implementation can improve program effects. Our estimates of wellness program effects on health care cost are lower than most results reported in the literature, but we caution that our approach estimated the isolated effect of lifestyle management interventions, whereas many published studies captured the effect of an employer's overall approach to health and wellness.

Although we do not detect statistically significant decreases in cost and use of emergency department and hospital care, the trends in health care costs und use of high-cost care for program participants and nonparticipants diverge over time. Therefore, there is reason to believe that a reduction in direct medical costs would materialize if employees continued to participate in a wellness program.

Lacking access to proprietary information on program cost, we could not estimate program effects on overall cost of coverage directly, but judging by published program cost data, the programs would be cost-neutral after five program years Baicker, Cutler, and Song, Since limited employee engagement is regarded as an important obstacle to program success, employers are using incentives to increase employee engagement, as the RAND Employer Survey and other surveys suggest.

Modest incentives also seem to increase participation in and impact of lifestyle management programs. The use of incentives tied to health standards remains uncommon.

The RAND Employer Survey shows that nationally, only 10 percent of employers with 50 or more employees that offer a wellness program use any such incentives, and only 7 percent link the incentives to premiums for health coverage. For this subset, maximum incentive amounts average less than 10 percent of the employee premium for health care coverage. The one health risk factor for which results-based incentives are more common and involve higher amounts is smoking, as suggested by both the RAND Employer Survey and our case studies.

We need to caution that our survey results may be subject to response bias, as some characteristics of respondents and nonrespondents differed significantly. Further, both the external and internal validity of the results based on the CCA data may be limited.