The biggest challenge in considering and planning health management (HM) investments is the estimation of the return on investment (ROI) that will result. This estimation is required not simply to decide whether or not to invest, but to design the particulars or how to spend the investment in terms of the HM program. In sickness care, quality standards and safety requirements make a relatively uniform approach for all patients with the same disease or injury essential, and performance is measured based on how well all care meets standards. In HM, by contrast, the care for individuals, or at least segments which share similar risks and savings potential, should have their interventions tailored to the ROI potential of each.

While it is possible to deliver HM interventions that meet uniform standards, this will automatically run the risk that the uniform, “one-size-fits-all approach will either not work with a significant portion of participants in the HM program, or cost too much even if it does work, perhaps both. Fortunately, there is a relatively simple “numbers needed to succeed” (NNS) analysis that can be employed to gauge the amount of investment that makes sense for individuals or segments, based on their risks and potential for reduction therein.

The key elements in the NNS analysis are the predicted reduction in risks of “adverse events”, and the predicted costs of these events. In the simplest cases, where HM is applied to insured populations, the risks and costs relate to sickness care utilization and expense. When HM is applied to employee populations, however, it makes sense to include all health-related costs and economic effects, including sickness care, disability and workers compensation insurance, productivity and performance impairment effects and their economic consequences.

To illustrate, a recent study of a case management intervention for heart disease patients, conducted at Stanford University in Palo Alto, California, found that this intervention added an average of $1250 to “usual care” by primary physicians, with the additional nurse and dietician care involved adding an average of 14 hours of face visit time for participants in the intervention group, compared to the control group. It estimated the economic value of each avoided adverse event for this population, namely hospitalization for heart attack, at $40,000. [ “Stanford Study Highlights Cost-Effective Method of Lowering Heart Disease Risks” Business Wire.com Aug 20, 2007]

To determine how much of a reduction in the incidence of such events is necessary to break even on the investment, the costs of the intervention, $1250 is divided by the cost of the adverse event, $40,000 in this case. Since $40,000 divided by $1250 = 32, there will have to be one adverse event cases avoided for every 32 participants in order to reduce sickness care costs enough to achieve a breakeven ROI. This amounts to a risk reduction percentage of 100/32 = 3.125%. The intervention has to have at least that degree of success in order to achieve breakeven.

In the Stanford example, the actual risk reduction percentage achieved by the intervention was only 1.6%, a statistically significant reduction, but one that falls far short of even a breakeven financially significant result. Had there been more costs that would be avoided by each avoided adverse event – for example a combination of lost work time and disability costs, the savings per avoided event would presumably have been higher. The savings required per event would be $1250 divided by the 1.6% reduction in cases, or $1250/.016 = $78,125. If the people participating in the program were paid $60,000 per year, the average compensation for hospital workers, for example, the extra $38,125 would represent 63.35% of their annual compensation, so would be an improbable degree of lost productivity.

On the other hand, if the value of the lost productivity were significantly greater than the average compensation of workers, which is normally the case for any profitable enterprise, the value of restored productivity or performance that was not lost could be greater than the amount of compensation indicates. For example, there is often a “multiplier effect” for the absence of a highly skilled worker. This effect has been calculated as 1.4 for hospital nurses, for example. This means that the absence or impaired productivity of one nurse is equivalent to the loss of 1.4 nurses’ worth of performance.

And if the value of such performance were, for example, 2x the compensation costs, the total value of performance gained through HM, i.e. the lost value avoided, would be 1.4 x 2 = 2.8 times the compensation of the impaired nurse. This would mean the lost time/performance would only have to be $38,125 divided by 2.8 x $60,000 or 38,125/168,000 = 22.69% lost productivity. Such an amount is at least possible combining the days of absence and degree of impairment when at work (“presenteeism” that might result from having had a heart attack.

For example, the degree of impairment reported by people who were recovering from a heart attack in one analysis was only about 14%. On the other hand, impairment for employees who suffered from congestive heart failure, while only 0.2% of the over 200,000 workers analyzed, had associated impairment of 22%, indicating that a prevented case could have the level of impairment reduction required to make such an expensive HM approach pay off. [ “Stanford Study Highlights Cost-Effective Method of Lowering Heart Disease Risks” Business Wire.com Aug 20, 2007]

More likely, however, would be a lower-cost intervention. If an intervention costing only $500 per participant could yield even a 1% reduction in cases costing $40,000 in sickness care costs, plus perhaps $10,000 more in impaired productivity/performance value, it would break even, since $50,000 divided by $500 = 1%. This would only be a breakeven return, however, so either costs would have to be reduced with similar benefit, or additional cost savings or other economic benefit would have to be found, perhaps in turnover avoided, for example, since replacing someone can easily cost 25% of the compensation value of the person replaced.

In any case, the NNS analysis is a useful tool in HM investment consideration and planning of specific interventions. It is far more “hard-headed” than sickness care is subject to, and a new approach for any healthcare providers considering it as either an internal investment for their own employees or an external program to market to employers. The economic benefit and NNS analysis become essential in both, and each initiative considered by providers should be able to compete on economic benefit with other sources of HM services, as well.