The evidence on disease management (DM) at least the “scientific” evidence involving controlled trials and rigorous analysis, has been consistently discouraging. In the latest example, involving a meta-analysis of 317 separate studies, the authors concluded that while the evidence consistently indicated positive effects on care process quality, there was no conclusive support for either improving health outcomes or saving money, once the costs of DM, itself, was included. There was evidence that DM for congestive heart failure reduced hospitalizations among participants, but increased outpatient and prescription drug care costs for depression participants. [S. Mattke, et al. “Evidence for the Effect of Disease Management: Is $1 Billion a Year a Good Investment?” American Journal of Managed Care Dec 2007 670-676]

Like essentially all its preceding examples of rigorous reviews of DM effects, this one dealt only with medical/hospital care costs, not with the impact on other “indirect” costs of DM participants, for example, the known productivity and performance impairment costs for patients with chronic conditions. Nor did it examine DM intervention models that tended toward the low end of costs, since most DM programs tend to be at the moderate to high end, i.e. involve personal phone coaching, or office, even home visit interventions. By examining only higher-cost “treatments” and medical/hospital cost effects, studies have far less probability of demonstrating net cost savings.

By contrast, there seems to be ample credible evidence, though rarely meeting rigorous scientific standards, often because of the lack of randomized control trials, that DM works for employers. Random trials are unlikely to be used, since in order for employers to invest in DM, they must have high confidence already that it works, and when they do, it makes more sense to involve as many participants as possible in the DM intervention, rather than randomly assign as many as half of those eligible to a control group of “usual” or no treatment. But chances are, employers’ confidence in DM is based more on the fact that chronic diseases are major causes of productivity and performance impairment, which can add greatly to overall labor costs rather than looking solely at medical care costs.

For example, one DM supplier, HealthMedia, Inc. in Ann Arbor, Michigan, has reported the degree of productivity impairment linked to seven chronic diseases (counting both hypertension and high cholesterol as “diseases”). Employees in its over 200,000-employee database with one or more of these chronic conditions reported significant levels of impairment, combining absences and reduced performance at work. There is no way, however, to conclude that such impairment was entirely due to these conditions, since employees tend to have multiple causes of impairment unrelated to the conditions.

The specific amounts of impairment affecting those who had chronic conditions included:

• Diabetes – 4.19% of employees; 14.7% impairment
• Hypertension – 17.75%…………..11.8%
• High Cholesterol – 17.62%….. ….11.2%
• Asthma – 8.9%………………………9.2%
• Past Heart Attack – 0.73%………..14.0%
• Coronary Artery Disease – 0.65%..14.1%
• Congestive Heart Failure – 0.22%..19.4%

The overall impact of these conditions, measured based on the impairment among the 44% of employees who had one or more such condition, amounted to 11.6% average impairment. This reflects the fact that the largest numbers of employees who had one or more of these conditions had hypertension, high cholesterol, or asthma, all of which had relatively low associated impairment, while those with higher impairment included much smaller numbers of employees. The 11.6% impairment would represent a “cost” in terms of lost productivity, of at least 11.6% x $50,000 = $5800 per year for each employee affected, counting only the “wasted” compensation paid to each where the average annual compensation is $50,000 per year.

The true costs of lost productivity seems likely to be higher, as far as employers are concerned. For one thing, there is what is called the “multiplier” effect of individual employees’ absence or impairment on the team, unit or department where each works. This can range from as low as 1.00 (no effect) for completely and easily replaceable workers such as short-order cooks, to as high as 11.4 (equal to the loss of 11.4 employees) for construction engineers. The average multiplier across all workforces has been estimated as 1.28 to 1.35, though each employer should base its multiplier on the kinds of workers each has, e.g. higher for “knowledge” workers and key professionals. [“Multiplier Effect: The Financial Consequences of Worker Absences” Knowledge@Wharton, Dec 14, 2005, and S. Nicholson, et al. “How to Present The Business Case for Health Care Quality to Employers” Applied Health Economics and Health Policy 4:4 2005 209-218]

Moreover, the value of workers to employers, the contribution each makes to the employer’s financial performance, is sure to be greater than the annual compensation for each. One study found that the knowledge value alone of professionals at pharmaceutical firms ranged from as low as 1.03 to as high as 7.28 times as great as the average annual compensation paid, and averaged 2.20. [P. Strassman “How Much Is an Employee Worth? Microsoft.com/business/peopleready Jan 14, 2006]

If the average impairment per worker with a chronic condition were as much as $5800 in compensation, times an average multiplier of 1.315 (halfway between 1.28 and 1.35), times an average value of 2.2x the compensation level, the total economic loss to employers would be $5800 x 1.315 x 2.20 = $16,779 each for the 44% of workers who had one of the conditions analyzed. But this amount clearly includes impairment due to other factors, such as lack of sleep, emotional problems, poor diet and fitness, stress, obesity, etc. So the real measure of importance is how much is productivity impairment reduced, i.e. is productivity improved by available DM interventions.

HealthMedia reported on two different DM programs, one just for diabetes, and the other focusing on medications and lifestyle change compliance in general for the other six conditions. The results for diabetes reflected an average improvement of 2.00% per participant in DM, while that for the other six conditions reflected an improvement of 1.88% per participant. This would amount to the “recovery” of 2.00% x $50,000 = $1000 for diabetes, and 1.88% x $50,000 = $940 for the other conditions. With a prevalence of 4.19% for diabetes, the higher improvement with diabetes would not be as valuable as that for the other conditions, since the prevalence of the other conditions combined was five to ten times greater, overall. [E. Baas “Achieving and Measuring Productivity Improvement” (Slide Presentation) HealthMedia, Inc. Oct 25, 2007]

If the true value of recovered productivity were estimated using the team and value multipliers, it would amount to almost three times as much, i.e. close to $3,000 per participant. And this represents clear value, without any double counting as prevails when estimating the costs of individual conditions, when each participant is involved in one and only one DM program. It is likely that the value of recovered productivity will be far greater than the value of reduced healthcare expense alone. It might be better if future reviews of the “evidence” on DM included this value, rather than focusing solely on savings to insurers in reduced medical costs.