I think that the Heisenberg Uncertainty Principle is the one of the few things I remember from freshman-year physics in college, which was also my only venture into the physical sciences at that level. Heisenberg responded to a particularly hubris-full colleague who commented that if we could identify the position and velocity of every particle in the universe, we could perfectly forecast the totality of mankind’s future. Heisenberg demonstrated that it is impossible to simultaneously know both – one can be know perfectly, but the more perfectly you know one, the less perfectly you can know the other.

The same uncertainty applies to a major challenge in employee health management (EHM); identifying both the full extent of productivity impairment in an employee population due to identified impairment factors, and the amount of impairment attributable to each factor. In reality, while it is a feasible and relatively simple task to identify the amount of overall impairment in a population, it is next to impossible to identify how much of it is due to any single cause. And as a result, if EHM providers or their clients look at the sum of impairment due to a number of different factors, they will get a highly exaggerated and unrealistic picture of what the problem and potential solutions amount to.

To illustrate, I will use the reported impairment amounts and factors o copied from the webinar slides offered by one EHM supplier. [E. Baas “Achieving and Measuring Productivity Improvement” HealthMedia.com Oct 25, 2007] These slides showed breakdowns of productivity impairment found in a comprehensive health risk assessment (HRA) that includes questions enabling the estimation of productivity impairment. Overall impairment was linked to seven different impairment conditions or behaviors, plus seven different chronic diseases or risks. The total amount of impairment linked to each impairment condition amounted to 9.6% per person per year for those who completed the health risk assessment (HRA) upon which both impairment levels and impairment/health factors were based.

The single HRA gets the total information on each participant therein, and ends up with an overall impairment level characteristic of each individual, plus the variety of impairment factors and risk/disease conditions each has. Since the impairment is collected as an overall percentage, every time the effect of a given impairment factor is reported, the same impairment percentage is included for each individual based on each’s level of the impairment factor. And since each individual either does or does not have a factor such as smoking, or a different level of a variable condition such as stress or depressed feelings, the same overall percentage of impairment is reported across the total of all participants for each factor.

This is not true for the individual chronic risk/disease conditions, since the amount of impairment for each person with the condition is reported separately. But since individuals often have multiple conditions (over 20% of the population in HealthMedia’s data base had two or more), by counting the impairment linked to each such condition ends up counting the same impairment level many times for at least 20% of employees. The total impairment of the workforce is the same, regardless of what levels of impairment individual factors are linked to.

To illustrate, 44% of the total population with one or more chronic conditions contribute had an average of 11.6% impairment, while those without any chronic condition had an impairment of 8.1%. Those with at least one chronic condition contributed 44% x 11.6% = 5.1% the overall workforce impairment, while those with no such condition contributed 56% x 8.1% = 4.5%. The two combined add up to 5.1% + 4.5% = 9.6=% for the workforce, on average, as is true with all impairment factors.

For example, the amount of impairment linked to the numbers of health risks, for those with three or more risks, was slightly higher than the overall level for the workforce, i.e. 9.73%. But this was because employees who had 2 or fewer risk factors, representing 13.01% of the population in the database, had less than the average impairment levels, so when the lower impairment among these employees is included, the average for the workforce goes down to the same 9.6% found overall and with other factors.

If all the impairment due to all factors were added up, this would greatly exaggerate the actual total impairment of the workforce, which is, in reality, only 9.6%. HealthMedia also chose to deduct from the overall impairment level an amount it deemed to be “normal”, namely 6.1%, leaving a reducible overall impairment of only 3.5%. Still, for a workforce that averages annual compensation of $50,000 (probably average for firms that are investing in EHM), that represents $1750 on average per FTE. Moreover, individual employees showed impairment levels as high as 30%+overall, or 24%+ above the normal level, so potential improvements for some individuals could be as much as $12,000 each.

If the individual impairment levels above the 6.1% average were totaled, using HealthMedia’s figures, the apparent total impairment amount would add up to roughly $9500 per employee in the workforce, equal to 19%, when the real amount, after deducting the “normal” level, is actually only 3.5%, i.e. the true overall average impairment per employee of 9.6% minus the 6.1% normal amount. Since the total impairment tends to limit the total potential return from EHM interventions, only the overall average impairment amount can reasonably describe this potential, and at that, only if all impairment can be reduced to the normal level, or eliminated entirely.

Fortunately, the unavoidable double, triple and more counting of the impairment due to individual risk, disease, or impairment causes is not germane to choosing which make the best prospects for investment. While the total impairment supposedly due to each impairment factor is the same as for all other factors, and the total potential is the overall or average impairment level, 9.6% in the HealthMedia example, this is sure to be the limit to ROI for EHM investments. But it is the effectiveness of individual EHM programs in reducing the overall workforce impairment that counts, not the theoretical potential or size of individual problems.