Al Lewis, JD

Al Lewis wears multiple hats, both professionally and also to cover his bald spot. As founder of Quizzify, he has married his extensive background in trivia with his 30 years experience in healthcare to create an engaging, educational, fully guaranteed and validated, question-and-answer game to teach employees how to spend their money and your money wisely. As an author, his critically acclaimed category-bestselling Why Nobody Believes the Numbers, exposing the innumeracy of the wellness field, was named healthcare book of the year in Forbes. As a consultant, he is widely acclaimed for his expertise in population health outcomes, and is credited by search engines with inventing disease management. As a validator of outcomes, he consults to the Validation Institute, part of an Intel-GE joint venture.

Recently, the economics of wellness were summarized in this blog. It turns out there is a reason no one has 

 for showing wellness saves money: it doesn’t.

Today is part 2 in the series, covering the health hazards of wellness. As with the 

, it will largely link to other studies and claims made by the perpetrators themselves.

Actual, well-documented, harms to an exposed population

Flouting of established clinical guidelines

“Hyperdiagnosis” leading to unneeded medical care

Incorrect or potentially harmful advice that employees are told to take

Actual, Well-Documented Harms to an Exposed Population

There is only 1 data point demonstrating actual harm to a population exposed to wellness.  That may be because a significant amount of data is required for such a demonstration. Further, the data must be incontrovertible. The vendor is Wellsteps, and the population is the Boise School District. It is incontrovertible because it is the vendor’s own data presented by the vendor itself. Hence, there is nothing to controvert—no one is challenging it.  

It showed a substantial deterioration in health status of Boise’s teachers, measured both subjectively and objectively. 

What is distressing about this outcome, as regards the wellness industry as a whole, is that is Wellsteps is not an outlier. Quite the opposite, Wellsteps won the wellness 

 in 2016, precisely for this work with Boise. If this program is the best, one can only imagine how much harm is does by vendors who are not the best—especially, those who are not willing to disclose their data. As the leading wellness promoter, Ron Goetzel, PhD, acknowledges, 

“many unsuccessful programs are not reported.”

 This figure includes “thousands,” he says, while only 100 (presumably including Wellsteps, since he runs the committee that bestowed the award upon them) are deemed by him to have succeeded.

I have worked with hundreds of patients over the 13 years during which I have worked with people with eating disorders. In the past 2 years, I have seen a number of patients who were quite negatively impacted by the wellness programs at their place of work.

Employees rarely put their names on first-person reports of wellness program harms, fearing retaliation from supervisors. However, the Bazelon Center collected quite a number of them, while maintaining confidentiality, from employees with eating disorders. 

 who provided some of these case studies, 

Here are summaries of detailed case studies:

Jane, an executive with anorexia, begs not to be weighed

… and then begs, unsuccessfully, not to have her weight announced. Relapses.

John, with bulimia, had to get his physician

 to intervene with human resources to leave him alone … and will have to do it all over again next year.

Mary, who has anorexia, walked into a workplace

 flooded with weight-loss “challenges” and biggest-loser leaderboards. She ended up quitting her job after several months of unrelenting messaging.

, was under control until she was docked “wellness points” for eating too much fat (under doctor’s orders). She began purging again.

 was asked “if obesity ran in her family,” and other questions that she, quite reasonably, interpreted as, “You’re fat.” This was done in a public place.

Kate, who has struggled with weight all her life

, was “coached” by an advisor who said: “I used to be as big as you are until I got bypass surgery.”

 many more first-person stories of wellness harms:

My husband’s [health maintenance organization] gave me a choice of either going to Weight Watchers or doing a minimum amount of walking every day. While I had cancer. And if I didn’t do it, my husband and I were going to be charged thousands of dollars more out-of-pocket each year. Luckily, my husband found a new job while I was in the hospital having my double mastectomy.

I am a triathlete and ultrarunner. My [blood pressure] tends to run dangerously low unless I eat a ton of salt. After a bunch of tests and doctor’s appointments, because I kept feeling like I was going to pass out any time that I wasn’t moving, I was just told to eat more salt. But then I was dinged on our automated questionnaire because it said I eat too much salt.

Frankly, this is really a bad idea, as it can create all kinds of bad habits and damaging activities by the participants, as they starve, 

 and supplement themselves in an effort to win. On the other hand, winning can make you feel GREAT! So, let’s go over some strategies to help you win!

It’s fairly well-established (though not proven) that weight cycling, aka yo-yo dieting, is likely to be harmful. However, what is certainly harmful is companies paying people large sums of money to binge before the initial weigh-in and then crash diet until the subsequent one. 

 devoted to the topic, starting with a cigarette label-type warning:

This is not a hypothetical. A large chunk of the oilfield services industry “competes” to see who can binge the most and then crash diet the most. Schlumberger 

, every year. The amount of weight lost by the winning teams far exceeds the rate of healthy weight loss 

The United States Preventive Services Task Force (USPSTF) and Choosing Wisely provide guidance on when to start screening, how often to get screened, and for what blood values. The rates are designed to balance false positives against true positives, and also to consider the potential for harm and remediating the harm in an undiagnosed condition.

Only blood pressure is recommended as an “A” annually for everyone. Other blood values are recommended far less frequently, starting at age 35 for males and age 45 for females. Some values, like glucose, are recommended to be done more frequently on certain people than others. All this assumes that a physician or other licensed, educated, qualified health professional is conducting the screens.

By contrast, wellness vendors are not licensed, regulated, or supervised by any government authority. They are not only allowed to flout guidelines, but, indeed, it is part of their business model:

The more vendors test, the more money they make. Consider, for example, Interactive Health. It boasts of 

 and recommends that everyone of every age get an HbA1c test. As a result of this overscreening, Interactive Health finds that 45% of employees need to go to the doctor for a new condition every year.

admits that the USPSTF rates its product a “D”

The state of Connecticut required female employees between the ages of 35 and 39 to get a mammogram. The USPSTF doesn’t even rate mammograms for women of that age bracket because it had not occurred to them that anyone would require women to get one. 

40 that the USPSTF doesn’t recommend starting routine screenings until age 50.

The state of Nebraska’s award-winning program 

 for colonoscopies, and sent 7 mailings to all state employees of any age, featuring a model way too young to be indicated for a routine colon screening.

While overdiagnosis is the observed and somewhat inevitable byproduct of the good-faith attempt to diagnose a condition, the term 

“hyperdiagnosis” is the deliberate, often breathless, reporting of large numbers of allegedly sick employees

. To continue with the Nebraska example, the program sponsors announced that they had made “life-saving, cost-saving catches” of 514 cases of cancer, among perhaps 3000 employees who were screened (the exact number of screened employees has not been forthcoming). This epidemiologically impossible figure was 

touted as one of the program’s successes

. In reality, virtually all of these people were falsely informed they had cancer, presumably triggering all the financial and emotional harms and consequences one would expect. (Later, the state program’s vendor 

 should not have been told they had cancer.)     

, Interactive Health is the leading practitioner of hyperdiagnosis. Lacking (or, worse, having) an understanding of the math of false positives, it wants to test everyone in an organization, and then send 45% of employees to the doctor.

What Interactive Health fails to understand is the rate of false positives. To use a hypothetical example: a test that is 90% accurate for detecting a hidden disease that 1 in 1000 people have will produce a false positive rate of 99%. Here’s the arithmetic: 100 people will test positive—the 90% accurate test is also 10% inaccurate&mdash;but only 1 of those 100 will have the condition.

$1 million dollars to prevent a heart attack

, and that’s why Interactive Health keeps finding employees with “newly discovered conditions.” 

Incorrect or Harmful Advice on Health Risk Assessments       

Medical professionals give harmful or incorrect advice all the time. What makes health risk assessment (HRA) advice uniquely harmful is that:

it is not offered in conjunction with a medical professional;

often it is obviously or at least arguably wrong; and

employees are given a “choice” of listening to the advice or losing money.

The 2 most widely used HRAs are Cerner and Optum. Here is an example of advice right off the front page of Cerner’s brochure:

This blood pressure is not “higher than what is ideal.” Quite the contrary, the revealed “pulse pressure” of 20 (110 minus 90) strongly indicates advanced heart failure. This employee should be rushed to the emergency room. (More than likely it was a false positive, because wellness vendors are not required to understand what they are doing. One vendor offers 

, half what the Four Seasons gives housekeepers. The franchisees typically have a background in “

municipality administration, finance or sales

Cerner also is way out of date on dairy fat, which turns out to be 

 which Cerner overlooks under “make healthier choices.”

It’s also possible that these findings are wrong, but something this controversial should not be represented as factual in advice that employees are required to read in order to avoid financial penalties.

Optum also offers highly questionable dietary advice:

In addition to lowfat dairy, Optum also recommends avoiding extra fats and oils, despite that fact that olive oil is healthy enough to possibly be 

However, the major hazard in Optum’s HRA is the advice that people with chronic pain go get on their doctor’s pain program. This advice is specifically given in states such as Ohio, Indiana, and New Hampshire, where pain programs have historically been synonymous with opioids.

The purpose of this article and this series is to facilitate research for journalists, law makers, and regulators. (

A companion article explores the ethics of unlicensed vendors in this unregulated field

.) What is curiously unique about this series is that it is entirely based on material provided by the industry itself. This article doesn’t “challenge the data” the industry provides. Quite the contrary, it embraces the data. The data, as seen above, consists of a series of self-incriminating business practices, screenshots, and outcomes intended to raise the questions: “Why is there a law encouraging this corporate behavior? Should the forthcoming regulations continue to protect employers who do this to their employees?”

To a large degree, this series answers these questions, as well, not just with self-incriminating business practices, screenshots, and outcomes, but also backed with 

, whose lack of claimants or even applicants speaks volumes about the industry’s faith in its own marketing claims.

Articles

The health hazards of workplace wellness programs fall within 6 categories.

Workplace Wellness Can Be Hazardous to Your Health

Prior to 2010, it had been widely assumed that the health and financial benefits of workplace wellness (risk assessments, biometric screening, and coaching) were so substantial that the Affordable Care Act (ACA) provision allowing employers to tie large 

 to wellness program participation, or to measured improvements in health outcomes, was not even debated before being passed into law. It was “

the one part of ACA that everyone agreed on”

 [including this author], as Senator Lamar Alexander, R-Tennessee, quite accurately stated.

This consensus assumption was based on 2 pieces of evidence. The first was Safeway’s claim that wellness reduced its health spending 40%, a claim that garnered so much publicity that the wellness provision of ACA became known as the “

 during the period in which the savings from it were claimed.

The second was a meta-analysis showing that programs at large companies had averaged more than $3 

, a finding later invalidated by one of the principal investigator’s own subordinates.

Subsequent to ACA enactment, small-scale findings by researchers and practitioners outside the industry have universally found financial benefits or health 

. This plethora of “micro” case evidence, combined with the unpopularity, intrusiveness, equity concerns, and (in some cases) 

 of workplace wellness, calls for a “macro” review to determine whether wellness has indeed saved money for the United States through reducing hospital admissions attributable to events such as heart attacks, diabetes, stroke, and hypertensive events—wellness-sensitive medical admissions, or WSMAs, that the industry claims to address&mdash;that should theoretically be avoidable through these programs.

If, indeed, wellness reduces hospital admissions, Healthcare Cost and Utilization Project (HCUP) data over a sufficiently long period should reveal gradually increasing separation—mirroring the dramatically increasing spending on wellness over that period&mdash;between the rate of WSMAs in the exposed population versus the nonexposed population of similar age, which was not insured privately.

This difference-of-differences should, by the end of the study period, be substantial enough to either show savings or at least be “on track,” via an increasing difference-of-differences in admissions to project a future breakeven.

This easily replicable and totally transparent analysis was conducted, as follows, in 2 parts. Both parts required accessing 

 from 2001 to 2014, which tallies nearly all hospital admissions in those years and is designed to facilitate analyses such as this.

The first part of the analysis was to discern separation between the study population and the control population.

To do that, overall (nonmaternity) admissions were split into 3 categories. The first was what HCUP calls “privately insured” (meaning mostly <65 years old employees or dependents, but with individually insured admissions, too). The second group consisted of admissions paid for by Medicaid. The third group was people who were uninsured or self-paying. In total, those groups should capture virtually the entire nonexposed <65 years old population.

These control populations are notable for lacking consistent access to preventive care and having generally worse socioeconomic status than the insured population. Therefore, their WSMAs should underperform the privately insured population. This 

 confounding bias means that, had there been significant separation, attribution to wellness (versus social determinants of health) could be arguable.

Next, the International Classification of Diseases, Ninth Revision, codes for WSMAs were separately accessed. These codes were (inclusive of all 5-digit codes) 250xx for diabetes, 410xx for acute myocardial infarction, 434.91 for stroke, and 401xx for hypertensive events. Tallying WSMAs is a widely accepted approach in wellness. The past chair of the Health Enhancement Research Organization (HERO, the wellness industry promotional association), Ron Goetzel, PhD, agrees: “The idea of analyzing claims for conditions likely to be most readily influenced by 

Measurement and Evaluation Guide recommends it. 

The WSMAs were split into the same 3 categories. The WSMAs were then divided by the number of total admissions for all categories. Four specific reasons dictated why total admissions would make a better denominator than a simple rate per 1000 population. First, during these 14 years many factors affected all admissions—better therapies, a move to outpatient care, increased adoption of high-deductible health plans (HDHPs), re-coding from admissions to observation days, and increased cost of hospitalizations would be among them.

Second, if there is a systematic error in the HCUP data collection, it would presumably affect all admissions equally and therefore this methodology would moot it. For instance, between 2005 and 2006 the population rates all inflected, for unknown reasons, but the inflection does not affect this methodology because it took place in all 3 populations.

Third, the populations themselves are not static, as people change payers. For example, people who were previously uninsurable could, following ACA passage, sign up for coverage either through Medicaid or the exchange. If those people are, plausibly, sicker than average, they will have more all-cause admissions than average. Making total admissions the denominator is, in some sense, a risk adjustment. Of course, the risk adjustment could go the other way too, as some of the previously uninsured had chosen not to buy insurance. They would have both low all-cause admissions and low WSMAs. Likewise, people in HDHPs could be expected to have lower rates of all admissions. Since the numerator and the denominator move together, contamination of the cohorts is therefore an unlikely confounder.

The actual data is appended to Figure 1 (see Results section), and the spreadsheets themselves are available upon request.

The second part was a “number needed to decrease” analysis. The difference-of-differences—the change in the number of admissions over the period versus the control&mdash;was compared with the change in spending on wellness programs over that period.

Over this 14-year period, in which the wellness industry grew from being too small to merit a published 

estimate of its size to $7.8 billion a year

, there was no corresponding reduction in WSMAs in the increasingly exposed population of privately insured people on an absolute basis (2014 vs 2001) or compared with the benchmark of total nonexposed populations under age 65, as Figure 1 shows. (Medicare, though not useful as a control due to age, trends much more positively than either despite having zero access to workplace wellness.)

Those 3 control populations—the uninsured, Medicaid, and self-pay/other&mdash;could logically be expected to do worse, owing to, presumably, worse social determinants of health. Yet the year-over-year and endpoint-to-endpoint difference is not great enough to support any hypothesis other than that no input or exogenous shock or demographic change over that period had any substantial differential impact on trend.

Figure 1. Privately insured WSMAs as a % of all admissions vs Medicaid/uninsured/self-pay vs Medicare

The second part was a “number needed to decrease” analysis. The difference-of-differences was compared with the change in spending on wellness programs over that period.

The number of relevant admissions in 2014, according to HCUP, was 398,790. HERO estimates that 

, for a total of $9 billion in spending. By contrast, the workplace wellness industry grew to $7.8 billion by 2014. No one knows what the industry size was in 2001 because it wasn’t tracked. As a plug figure (and changing this assumption would not materially affect the conclusion), assume $1 billion. For employers to break even on wellness through savings on admissions (and before considering the list of healthcare costs that HERO acknowledges 

), the 2014 admissions figure at $22,500 per admission would have to have fallen by more than 300,000, creating a trendline that would approximate that shown by the black dotted line in Figure 2.

Figure 2. Approximate WSMA decline required to break even on wellness spending

This study is intended only to show a major magnitudinal and directional result, not a precise impact of wellness. Hence limitations affecting precision would not affect the magnitude or direction of the result.

One limitation is that the percentage of Americans older than age 65 who are employed full- or part-time has 

increased from 13% to 19% over the period in question.

 Some number of them would still be “privately insured.” However, because the Medicare WSMA trend is so positive, the bleed of seniors (in the ratio of WSMAs to all their admissions) into the privately insured subset should make the latter trend more favorable.

A third limitation is that while virtually all people subject to wellness would be in the privately insured cohort so that sensitivity is close to 100%, specificity can’t be estimated because this industry’s opacity makes exact wellness program enrollment figures difficult to discern—and wellness programs vary from 

employer to employer and by employer size

. One consequence of this limitation is that the lower the figure one assumes for specificity (penetration of wellness programs), the greater the excess of spending on wellness programs over spending on WSMAs in the subset of the population subject to these programs, to the point where even elimination of all WSMAs in the penetrated population could not result in a breakeven.

For example, if half the privately insured population is exposed to wellness, the $7.8 billion in spending would substantially exceed the $4.5 billion in WSMAs.

This is consistent with practice: as noted in the discussion below, a typical spending level of $100 to $150 per employee per year would far exceed savings even in award-winning programs.

It is important to recognize that [wellness] should increase the use of certain services, such as preventive and screening services, certain chronic medications, and outpatient visits. It is even possible to see a rise in ER and urgent care visits as well-informed patients learn to get urgent medical care.

A fourth limitation is that other medical expenditures could decrease. However, there is no evidence of that. Typically, programs require more checkups and other 

A final limitation is that wellness may “pay for itself” in some other way, such as employees having higher productivity or fewer absences. That is beyond the scope of this analysis, but wellness programs aimed squarely at cardiometabolic risk reduction should see some impact on relevant WSMAs.

This “macro” finding meshes with the case study literature published within the last 5 years, results self-reported by HERO and leading vendors, and wellness industry promoters’ own comments.

Four of those case studies were observational. 

 of the Barnes Hospital wellness program revealed a reduction in hospitalizations but no savings. Further, the baseline rate of WSMAs (using approximately the same definition used in the current analysis) was roughly 24 per 1000 employees per year or 27% of all admissions—both figures being many times the national average. This makes it possible to attribute some or all of the reduction in hospitalizations to regression to the mean. 

 of the Connecticut state employee program revealed an actual claims cost increase, which the authors attributed to more annual checkups and other preventive care, included required mammograms for women under 40. 

 of 373,578 medical records correlated lower risk factors with higher spending.

Many studies, including the widely cited 

 estimating a 3.27-to-1 ROI, “show savings” by comparing participants to non-participants. However, a 

controlling for the impact of self-selection by would-be participants, found no impact on health behaviors or outcomes in the first year.

 It concluded that the participant-vs-non-participant study design was itself invalid.

Jones’ conclusion regarding the invalidity of that study design is consistent with observational findings: In the 3 instances in which it was possible to compare participants vs nonparticipants study designs with a known benchmark, the 

entire separation could be attributed to the study design

. For example, in 1 case, would-be participants showed roughly a 20% favorable separation in costs versus nonparticipants after 2 years, even though 

there was no program to participate in during that period

. All 3 studies were conducted by wellness industry promoters, ruling out investigator bias.

Jones’ finding is also consistent with the wellness industry trade publication’s acknowledgement that “

randomized control trials show negative ROIs [return on investments]

The only randomized control trial published

 subsequent to that meta-analysis also found little to no impact of incentivized weight loss, implying no savings and a negative ROI.

The principal finding of this study is also broadly consistent with the 

 that wellness avoided less than $12 per employee per year in reduced hospitalizations, before program fees (typically 5 to 12 times that figure) and other costs are considered.

The finding is consistent with the results achieved by the most recent winners of the wellness industry’s award for program achievement. The 2015 winner 

 in the health status of the participants, mooting any claims of savings.

The finding is also consistent with the Kaiser Family Foundation’s review of health risk assessments, where it was found that company-wide completion rates for this tool, considered a pillar of wellness, correlated with 

, and at the individual level, completion also 

The finding is also consistent with commentary in the lay media, 

The finding is also remarkably consistent with the admissions of HERO’s own principals, such as “Only … 100 programs [have succeeded while] 

thousands … are not getting good outcomes

,” and that even those programs “done right” achieve only a “

1% to 2% improvement,” after “2 to 3 years

Because wellness has not demonstrated any meaningful cost savings or outcomes improvement and even award-winning programs are associated with deteriorations in health, the ACA policy allowing financial coercion by employers to force employees into unlicensed, unregulated, wellness programs should be reconsidered.

bill currently awaiting a floor vote in Congress

Preserving Employee Wellness Programs Act

 financial coercion by employers, overriding the prohibition against involuntary medical exams and inquiries in the Americans with Disabilities Act. It would also allow employer programs to access 

. Even evidence from DNA testing vendors does not 

Quite the opposite: employees should be allowed to opt out of these “voluntary” wellness screening programs with no financial forfeiture. Screenings should also be scheduled, and blood panels chosen, according to age-adjusted clinical guidelines, instead of requiring often-inappropriate screening blood values at inappropriate annual intervals for everyone, which increases the likelihood of expensive and hazardous overdiagnosis and overtreatment—and does not reduce relevant hospitalizations by a meaningful amount.

1. The principal investigator of that study, Damon Jones, PhD, is an associate professor at Harris School of Public Health, where Katherine Baicker, PhD, is a dean—a relationship likely unique in the annals of health services research that allows investigator bias to be ruled out.

2. See Figure 4 on page 9 of The McKesson Koop Award 2015 C. Everett Koop Award application, listing the “before” and “after” results of biometric screenings. The deteriorations in 3 of the biometric indicators almost exactly offset the improvements in the other 2 even without considering that dropouts lost to follow-up might tip the scales in the negative direction.

Since wellness programs have not demonstrated any meaningful cost savings or outcomes improvement, the Affordable Care Act policy allowing financial coercion by employers to force employees into unlicensed, unregulated, wellness programs should be reconsidered. And, yet, a bill currently awaiting a floor vote in Congress would allow greater financial coercion by employers.

In Light of Wellness Program Findings, Employees Should Be Able to Opt Out of Wellness Screenings

Some tourist attractions feature an “A” tour for newbies and then a “behind-the-scenes” tour for those of us who truly need lives. For instance, I confess to having taken Disney’s Magic Kingdom underground tour, exploring, among other things, the tunnels through which employees travel so as not to be seen out of costume in the wrong “Land.”

Likewise, there have been many reviews of the 

 by the National Bureau of Economic Research (NBER), the first-ever randomized control study of a wellness program. This, however, is the first review to go beyond the “A” tour of the headlines.

By way of background, the headline is that the mainstream wellness program the investigators examined at the University of Illinois did not noticeably move the needle on employee health. They didn’t address return-on-investment (ROI), because there obviously was none. Achieving a positive ROI would require moving the health risk needle—not just by a little, but rather by enough to significantly improve the health of many employees. Then, since wellness-related events, such as heart attacks, would not otherwise have befallen these employees immediately, this improvement would have to be sustained over several years before there was a statistical chance of some events being avoided.

Finally, the magnitude of this improvement would have to be great enough to violate the rules of arithmetic, because it is not mathematically possible 

to avoid enough medical events to break even on wellness

 to avoid a heart attack through a screening program.

This finding, therefore, represents an existential threat to conventional wellness programs.

No surprise, then, that while virtually all the reviews of this study have been positive, wellness apologists have tried to discredit it 2 ways. First, they would say: “Yes, but it’s only 1 year.” That is true, but there is no reason to expect a “hockey stick” improvement in Year 2, when in Year 1 employees didn’t even increase their visits to the gym in Year 1, which would have been the easiest behavior improvement. 

: “We don’t see anything trending towards savings.”

Next, detractors would, ironically, say: “Everyone knows savings don’t start in the first year.” And yet the Koop Awards—the award given to the best-in-country wellness program by a group of wellness promoters that licensed the name of former Surgeon General C. Everett Koop, MD, (which 

 later in his life)—almost invariably go to programs that show massive first-year savings by comparing active motivated participants to non-participants. In one award-winning case, 

Detractors would also say: “This study was misdesigned because they lumped nonparticipants and participants together. Obviously, nonparticipants would have no interest in this program.” That, of course, is a feature of this study design, not a bug. This study design controls for motivation, in order to isolate the program effect from the self-selection bias, such as the bias evident in that very same award-winning study.

All these negative reviews took place in LinkedIn groups that are generally closed to the public, and also to wellness critics. Despite multiple requests to comment, the Health Enhancement Research Organization (HERO, the wellness industry trade association) has offered no rebuttal, response, or even acknowledgement of the existence of this study. Perhaps it fears that its comments will draw more attention to the original, not just from trade publications, but also from 

 media outlets, neither of which have been supportive of workplace wellness.

The study could be criticized on 1 key point, a flaw that no detractor spotted. The 2 groups were compared on the basis of change in total cost, rather than (or in addition to) the change in the total number of wellness-sensitive medical events (WSMEs). The “gold standard” methodology of tallying WSMEs is described in my book, 

HERO’s own outcomes measurement guidebook

 (chapter 2). It is required by the Validation Institute for 

outcomes validation for employee- and member-facing

 organizations by the Validation Institute. 

The reason to focus on WSMEs is that being screened for heart disease and diabetes, providing information on one’s diet and exercise, and having access to a gym could not be expected to reduce total costs, but rather just the cost of avoided WSMEs. Wellness programs aren’t going to get “medical costs to decrease significantly for neoplasms and digestive systems [

], and for blood and blood-forming organs,” though 

a widely cited study made that exact claim

__________________________________________________________________________

 The separation of participants (green line) and non-participants (orange line) took place in 2004. The program started in 2006. By the time the program started, participants had already “saved” almost $400, without even having a program to participate in.

The behind-the-headlines tour of the NBER study yields the most important conclusion

The focus on the headlines has obscured the most important conclusion from this study, which is that the entire participant vs nonparticipant methodology is invalid. Until now, that methodology had been 1 of the 2 methodologies the industry uses to reliably “show savings” in virtually any circumstance.

Of the 2, the participant vs nonparticipant methodology is the only one that arguably needs scientific proof along with mathematical invalidation. The mathematical invalidation has already been 

. That study was a meta-review of 3 participant vs nonparticipant studies, which had a known benchmark—including the 1 highlighted above where the “benchmark” is that a wellness program can’t show savings before it exists. Therefore, the known benchmark is 0% savings on participants, invalidating the participants vs nonparticipants result showing almost 20% savings.

The best confirmation of any initial conclusion is an analysis reaching a similar or identical conclusion—but conducted using a completely different approach, by completely different researchers, with no relationship to the original researchers, and no confirmation or investigation bias.

This study satisfied those criteria. It was a prospective randomized control study aiming for a scientific outcome, as opposed to the previous study, a retrospective meta-review focused on arithmetic. Along with invalidating the methodology generally, the researchers specifically invalidated 78% of the studies that comprised the 

A new study represents an existential threat to conventional wellness programs. Here's a behind-the-scenes look at the study's findings.

Author | Al Lewis, JD

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