As noted above, for activity-based wellness programs it is permissible to seek verification, such as a statement from the individual's personal physician, that a health factor makes it unreasonably difficult for the individual to satisfy, or medically inadvisable for the individual to attempt to satisfy, the generally applicable health standard. On the other hand the final rules states that:.
As compared with the earlier proposed rule, "One key change was that individuals cannot be overly burdened with requirements in order to benefit from a wellness incentive, nor can they be required to complete the wellness program in an inappropriate time frame," said Austen Townsend , an employee benefits attorney in the Washington, D.
Separately, the U. Department of Labor is actively auditing plans for compliance and could bring a civil action against an employer to enforce these requirements. That will help employers that are considering non-traditional wellness incentives that might not meet every technical detail in the regulations. The federal departments said they anticipate issuing future subregulatory guidance to provide additional clarity on wellness programs and potentially proposing modifications to this final rule as necessary.
Sign Up Now. You may be trying to access this site from a secured browser on the server. Please enable scripts and reload this page. Reuse Permissions. Page Content. Monetary Incentives Monetary incentives covered by the statute and final rule include rewards—such as a discount or rebate of a premium contribution, a waiver of all or part of a cost-sharing mechanism including deductibles, co-payments or co-insurances—and penalties such as a surcharge or other disincentives.
The final rule implements PPACA provisions that: Increase the maximum permissible reward or penalty under a health-contingent wellness program offered in connection with a group health plan and any related health insurance coverage from 20 percent to 30 percent of the total annual cost premiums of individual-only coverage. Increase the maximum permissible reward or penalty to 50 percent of the cost of individual coverage premiums for wellness programs designed to prevent or reduce tobacco use.
Alternative Health Standards The final rule requires that health-contingent wellness programs be reasonably designed and uniformly available to all similarly situated individuals.
In addition: These final regulations also do not require plans and issuers to establish a particular reasonable alternative standard in advance of an individual's specific request for one, as long as a reasonable alternative standard is provided by the plan or issuer or the condition for obtaining the reward is waived upon an individual's request.
For example, according to an analysis by Seyfarth Shaw LLP: An activity-based program must allow a reasonable alternative method for obtaining the reward or waive the applicable standard for any individual for whom it is medically inadvisable to attempt to satisfy the standard or unreasonably difficult due to a medical condition to satisfy the standard.
An outcome-based program must offer a reasonable alternative method for obtaining the reward to or waive the applicable standard for a much broader group. It must allow any individual who does not meet the initial standard based on the measurement, test or screening to use an alternative standard. Wellness Benefits. You have successfully saved this page as a bookmark. OK My Bookmarks. Please confirm that you want to proceed with deleting bookmark. Delete Cancel. You have successfully removed bookmark.
Delete canceled. Please log in as a SHRM member before saving bookmarks. OK Proceed. Your session has expired. Incentives were classified into one of four incentive types on the basis of inclusion of health contingent elements in the incentive design. An element was a specific activity or achievement that was associated with an incentive award.
Participation-based incentives had no health contingent elements, but included incentives for participation in wellness programs. Hybrid partial outcome-based incentives included health contingent elements that were worth less than the total available outcome and participation incentive amount.
Outcome-based incentives contained health contingent elements equal to the total available outcome and participation incentive amount. No incentive indicated that there were no incentives available for either health contingent elements or for participation in wellness programs. Other independent variables were included in analyses to control for potential confounding effects.
These variables included person-level demographics such as age, gender, and relation type employee or dependent , which were derived from eligibility files.
Median income and population density in an individual's residential zip code were matched from U. An indicator was included to show whether an email address, by which communications could be sent to each individual, was available. Employer-level variables included an industry categorization, the number of health promotion program communications that the employer sent per eligible employee, and a continuous culture of health index. Bivariate relationships between incentive type and each covariate were examined.
Chi-squared tests were used to test for correlations between the distributions of categorical covariates and incentive type. Analysis of variance ANOVA was used to test for differences in the means of continuous covariates between incentive types. Multivariate logistic regression models were used to estimate the association between incentive type and both wellness program participation and achievement of health improvement targets in each analytic group in order to control for observed differences in other covariates that may influence program participation or health status improvement.
The explanatory variable of interest was incentive type. Participation-based incentives were used as the reference group because this was the largest group and was considered current practice. Control variables included in each model were age, gender, relation type, median income in zip code of residence, population density in zip code of residence, availability of email communication, an employer-level count of the number of promotional messages sent per employee, employer industry, an employer-level culture index, dollar value of incentives, and other incentive characteristics.
Regression models of achievement of health improvement targets included program participation as a covariate. Each regression model included a random effect for the incentive group. Standard errors were estimated using bootstrapping with repetitions to account for clustering of individuals within incentive groups. Incentive groups were used as the clustering variable because of differences in how employers treat individuals in each incentive group.
A separate logistic regression model was estimated for both program participation and achievement of health improvement targets within each of the three elevated baseline measures groups yielding a total of six regression results. Commonalities across regression results for participation or health target achievement were highlighted as findings.
All statistical analyses were conducted using Stata There were demographic differences between the four incentive type groups. The most notable differences were observed among the full outcome-based incentive group. This group was significantly older, lived in lower income and more rural zip codes, and was more likely to work in manufacturing than other groups.
The full outcome-based incentive group had more incentive dollars available but was less likely to be able to roll over incentives or earn partial incentives. Individuals with participatory incentives were more likely to be female than other groups. Overall wellness program participation rates were About Among program participants in the elevated baseline non-HDL cholesterol group, Among program participants in the elevated baseline blood pressure group, No significant differences were observed between any of the incentive type categories.
Larger incentive amounts were associated with greater odds of participation as were female gender and the ability to receive email communications. Eligible dependents exhibited lower odds of participating in programs than employees. Participation was not associated with baseline biometric values and only in the BMI sample was it significantly associated with age. Participation was also not associated with the employer-level measure of the number of messages sent or the employer-level culture index measure.
Again, no significant difference in the odds of achieving health improvement targets was observed by incentive type categories. Several factors that were associated with participation such as incentive amount and the ability to receive email communications were not associated with achievement of improvement targets.
The program participation indicator was only significantly associated with achieving improvement targets in the BMI sample. Age and gender were consistently associated with achievement of health improvement targets.
Females were more likely to achieve health improvement targets. Age was consistently nonlinear with reduced odds associated with age and slightly higher odds associated with the age-squared term. Higher baseline measure levels were associated with greater odds of health status improvement in the BMI and non-HDL cholesterol samples but not in the blood pressure sample. This study offered a direct comparison of the effectiveness of participation-based and outcome-based incentives in worksite wellness program settings.
This study found that, among groups with elevated baseline health status measures, there were no significant differences in the odds of program participation among different incentive types when controlling for communications, individual demographics, and other incentive characteristics such as incentive amounts.
There was also no statistically significant difference in the odds of health improvement between the various incentive types when controlling for potential confounders. As mentioned in the Introduction, outcome-based incentives are conceptually similar to performance-based pay systems designed to align incentives with a desired outcome. Although the desired outcome in a pay-for-performance system is typically related to business goals such as increased client retention, the desired outcome in an outcome-based incentive model is health status improvement.
Applying these principles to outcome-based incentives illustrates several potential reasons that outcome-based incentives may not be associated with greater participation or health improvement. Employers using outcome-based incentives appear to have clearly defined and communicated health targets, but individuals may or may not agree with these targets or may not understand what to do to reach them.
In addition, employees may feel that the targets are arbitrary and irrelevant to work performance not aligned with individual or organizational values. Employees may not possess the knowledge, skills, abilities, and self-efficacy required to meet established health status targets.
There may be opportunities for employers or wellness providers to better apply learning from the pay-for-performance world to wellness incentives. In addition, the presence of RAS may have dampened effects of outcome-based incentives. RAS in the study population consisted largely of participation in a wellness program.
Given the RAS, outcome-based incentives are effectively participation-based for those who do not meet established targets at baseline the population of interest in this study. In this light, it may be unsurprising that no difference was observed. This differs from the expectations of many employers who view outcome-based incentives as analogous to performance-based pay and expect greater accountability and therefore better outcomes.
Several of the estimated odds ratios appear to be counter-intuitive. Holding all other factors constant, no significant association was observed between the client-level culture index and worksite wellness program participation. The directionality of estimated odds ratios suggested that higher culture scores were associated with slightly lower odds of wellness program participation, whereas other studies have found positive associations between culture and wellness program participation.
It may also be the case that the employer-level shared perception captured in the variable was not representative of the study population, those who had repeat biometric health screenings and elevated baseline metrics. Another example of a seemingly nonintuitive finding is the lack of correlation between the number of messages sent per eligible participant and wellness program participation. The ability to communicate to an individual via email was associated with a greater likelihood of wellness program participation, but the employer-level number of communications sent per eligible participant was not.
This may be due to the way communications were targeted. Lack of prior participation was a common criterion used to determine who should receive additional communications. Individuals who participated early in the program year likely would have received fewer messages than otherwise similar individuals who did not participate or who postponed participation. The no-incentive group showed higher odds of program participation than other incentive types, though not significantly so.
This may be due to the focus of the analytic sample on individuals who had completed health screenings in 2 consecutive years and had an elevated baseline metric. Individuals who were motivated enough to complete screenings in both years without having incentives in place may have been more self-motivated than other groups that had incentives in place. It should also be noted that nonincented groups in the study population typically consisted of spouses or non-benefit enrolled individuals who may not the primary target of the program, but may be aware of available offerings.
This suggests caution in generalizing these findings beyond a repeat screening population and indicates a need for future work explicitly modeling selection into the repeat screening cohort.
Although this study was not designed to evaluate whether worksite wellness programs lead to behavior change or health improvement outcomes, the estimated odds ratio on the participation covariate hints that they may.
For all three samples, the odds ratio was greater than one, though it was only significantly greater than one in the elevated BMI estimation sample. The very broad definition of participation, at least one interaction regardless of program focus or intended outcome, is likely insufficient to estimate program effects. Future work should examine a range of participation definitions.
There are limitations to the current study that should be noted. This analysis was not intended to evaluate the effectiveness of health improvement programs, but rather to examine whether there was any differential impact in the presence of outcome-based incentives or participation-based incentives.
This analysis relies on a 1-year observation period. It is possible that differential impacts of various types of incentives may become apparent over a longer time horizon. Future work looking at longer time periods is needed to determine whether differences emerge over time. This analysis relied on data from a narrow set of individuals who chose to complete two biometric health screenings and who had baseline values above a particular level.
Reliance on a self-selected set of repeat screening participants limits the generalizability of findings. Additional modeling to explicitly account for this selection effect would be valuable. Another factor that may limit generalizability is that all data were drawn from a single wellness provider. Reliance on data from a single wellness provider may not only result in more consistent incentive and participation data but may also limit generalizability.
Future work should examine whether outcome-based incentives are more effective among specific populations, in specific settings, or when particular conditions are present. For example, individuals who have healthy metrics at baseline may respond more positively to outcome-based incentives than individuals who are outside of recommended ranges at program onset.
There are also several limitations to the measures that were available for this study. Future work should examine how well this correlates with other culture measures. Another limitation relates to the inability to control for differences in motivation or stages of change.
These measures were not available for the study period. Future work should consider whether motivation or stages of change are impacted by outcome-based incentives and whether controlling for differences in motivation could yield different estimates of the impact of outcome-based incentives.
Definitions of health improvement targets and participation used in the study represent another potential limitation. The health improvement target definitions were selected to be representative of those used by study employers, but they do not match exactly what was in place for each employer. Future work should consider whether the health improvement targets selected might impact the effectiveness of outcome-based incentives.
Likewise, the definition of participation was intentionally chosen to be broadly consistent with an intent-to-treat approach. Future work should examine whether outcome-based incentives might have a differential impact on the quantity or quality of participation achieved. When person-level demographics, communications, culture, incentive amounts, and other incentive characteristics were controlled for, no difference in program participation or the achievement of health improvement targets was observed between participation-based and outcome-based incentives.
Current policy and employer interest in outcome-based incentives is based on assumptions that linking incentives directly to outcomes of interest will be more effective than linking incentives to participation that may lead to that same outcome. This study does not definitively support nor disprove that hypothesis. Future work is needed to understand more completely the impacts of outcome-based wellness incentives and the conditions and settings in which outcome-based incentives may be most effective.
No outside funding was solicited or received to support this work. All authors are employed by RedBrick Health, the wellness provider from which data were obtained for the analysis. RedBrick Health supports a variety of different incentive models and does not have an interest in supporting one type of incentive over others.
The interest of this paper is in spurring research to further understanding of which types of incentives may be most effective. National Center for Biotechnology Information , U. Journal of Occupational and Environmental Medicine. J Occup Environ Med. Published online Jan Nathan A. Barleen , BS, Mary L.
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