home email us! sindicaci;ón

Choosing the Best EHM Investments

by Scott MacStravic

Perhaps the biggest impact of looking at employee health management (EHM) rather than general population health management (PHM) is the difference it makes in what make the best investments. When the sole concern is reducing sickness care costs in an insured population, it makes pretty obvious sense to look at sickness risk factors and chronic diseases. But when the concern expands to include reducing all factors that impair or impede productivity and performance among employees, the scope of investments can expand dramatically.

For example, while chronic conditions such as diabetes, asthma, coronary heart disease, congestive heart failure, and chronic obstructive pulmonary disease may be the biggest causes of preventable sickness care costs in a population, they are likely not to be the best investments for employers. Other factors, such as depressed feelings, stress, smoking and alcohol addictions may be far greater impairment factors because of their higher frequency than chronic diseases in employees.

While it is possible to separate the impact of diseases on sickness care costs, merely by analyzing the diagnostic codes involved, it is anything but easy to identify the impact of individual impairment factors. When such factors are identified, they almost never occur alone, but are part of a set of factors that vary widely across individuals in their mix and severity of impact. Depression is a common co-morbidity for diabetes and heart disease, but stress is a common “co-impairment factor” for a wide range of others, including overweight/obesity, poor sleep, nutrition and fitness levels, as well as depressed and anxious feelings.

When productivity/performance impairment is found through objective measurement, or self-reported by employees, it usually comes in people who have multiple factors at the same time. Their overall impairment normally gets counted as linked to every factor reported, and counted multiple times. This multiple counting can be overcome by either dividing the total amount of impairment by the total of all prevalence figures for all the factors, or by separating out the individual factors in some way.

Dow Chemical Company, for example, asked each employee to identify which was the primary impairment factor affecting each, so as to count the effect of each factor only once. But this under-counts the overall impact of each factor, by not recognizing the potential that some add to the effects of others, even if not primary, while over-counting the effects of some which are most often labeled primary, but whose impact is exaggerated by what may be many secondary accompanying factors.

If the true effect of individual factors can be identified, along with the true effects of EHM programs targeting each such factor, employers would have a far better chance of selecting the most promising target factors and individuals for EHM investments. Moreover, EHM vendors could use the identification of the factor that has the greatest impact on individuals’ impairment in recruiting employees for participation in the program that will affect it the most.

As long as individual employees see themselves as benefiting predictably and significantly if they improve their productivity/performance, they should be as motivated to devote their efforts to the program that will achieve such an improvement. Particularly for employees who are paid, either wholly or in part, on the basis of their productivity/performance, it would make explicit economic sense for them to enroll in the EHM program that will simultaneously do them and their employer the most good.

Employers must always be kept from knowing which employees are impaired by which factors to what degree. They always have access to whatever productivity/performance data is already available through their ongoing employee reviews or data, but are prohibited from identifying confidential health information about their employees that may be responsible for lower than desired performance. But as long as employees give permission to EHM vendors, with the understanding that identifying the most powerful impairment factors affecting each and the most promising EHM programs for each, the employees stand to benefit as much as the employer.

Employers can use what they learn about the effects of particular factor-specific EHM interventions and the effects they have on overall employee productivity/performance to graduate the incentives they offer to employees that achieve specific health goals, such as quitting smoking, or reducing their blood pressure, sugar, and cholesterol, for example, or improving their nutrition, fitness and sleeping habits, controlling their stress or managing their chronic disease. As long as employees’ achievements can be verified, employers should be confident that they, too, are benefiting.

Difficulties will arise with respect to self-reported impairment and recovery, whenever there are incentives to be gained. It would be a simple matter for employees to report that they are sleeping better, exercising more, have their stress under control, eating better, have reduced their alcohol intake to no more than some set limit per day. But employers may prefer verification to paying off for good reports, alone.

Some verification is relatively simple: weight loss can be checked by a scale, smoking cessation by testing for nicotine, fitness by a test, etc. But many are not easily verified, while productivity/performance improvement, per se, should be verifiable at least to some degree. And as long as employees figure out a way to produce more and perform better, they should be eligible for rewards. The EHM provider need only make sure that enough employees improve enough through participation in the best interventions to make such improvement possible.

If employees learn that improving their stress management can increase their productivity by 10%, for illustration, and employers learn that stress is a major impairment factor for the entire workforce, employers can work on reducing stress levels they impose on workers, while helping workers cope with stress. This may involve a combination of an EHM provider’s stress management program, employer-sponsored training in time management, and improved scheduling of efforts so that demands and deadlines are reasonable rather than oppressive.

It is clear that predictive modeling is approaching the point where the most promising individual impairment factors will soon be able to be identified as directly and simply as can the most expensive sickness. Once this is achieved, the potential for enabling both employers and employees to make the best possible decisions about where to focus their investments of money and effort will be greatly improved, and thereby, the success of EHM investments in general.

No comments yet »

Your comment

<a href="" title=""> <abbr title=""> <acronym title=""> <b> <blockquote cite=""> <code> <em> <i> <strike> <strong>