In most cases, sickness is a discrete variable, that is, people are either sick or not sick, and the purpose of sickness care is to return patients to the non-sick state, otherwise, they are not “cured”. With chronic illness, patients are not cured at all, merely “controlled”, by some combination of their own and their providers’ efforts. In other cases, such as severe trauma and catastrophic disease, patients are not cured, but “rehabilitated” to as high a level of normal, non-sick functioning as is possible given their condition.

The point is that in most cases, patients can be described as in one of two possible discrete states: sick or cured, perhaps controlled or rehabilitated. This does not mean that no further effort is required to maintain their non-sick state, or to prevent recurrences, crises, complications or worsening of their status, but when these occur, they will again be labeled as sick, and as “patients” rather than “people”.

In health management (HM) — of individuals, populations, employees, insured plan members or government plan beneficiaries, the targets for effort and attention, as well as the source of HM’s economic benefit, relate not to moving people from sick to nonstick, but along a continuum that ranges from perfectly healthy to having some risk behaviors or conditions of concern to having a somewhat controlled chronic condition. As long as HM participants are non-sick with some acute problem, crisis or complication, they are still not patients.

Providers may deem them patients, of course, as long as they are on the books as a member of a physician’s panel, for example. But from the perspective of HM providers, including physicians, of course, and of employers, insurers, and government agencies, they are people, who may also be participants in some particular HM program or special initiative. And while they are participants, as well as because they are, such people may be moving along the continuous dimension that runs from perfect health to death, or at least to sickness. This makes their health a continuous variable.

The significance of this in HM is that people may respond to HM interventions in any way from not at all to minimally, modestly, significantly, dramatically, etc. as high as it is possible to do so. Their response, in terms of participating in coaching sessions, monitoring their conditions, changing their behaviors and lifestyles, complying with medications, etc. will also fall somewhere on a similar continuum. And as a result of their responses, their health status will usually progress in the positive direction along a wide range of continuous dimensions, such as weight, blood pressure, sugar or cholesterol levels, bone density, etc.

And as a consequence of this positive health status change, participants will deliver benefit to HM sponsors, as well as to their own health/life quality, along yet another set of continuums. The immediate consequences along the sponsor “benefit” continuum may involve reduced sickness care use and expense, for commercial and government insurers, as well as employers. For employers in particular, they may also involve reduced disability and workers compensation costs, absenteeism and presenteeism. For the least myopic employers, consequences may also include improved retention, quality, customer satisfaction, market share and revenue, as well as profits, also continuous variables.

When the effects of HM investments are continuous variables, it is usually impossible to say that any particular HM participant has “succeeded”, since this requires a discrete distinction between successful and unsuccessful participants. HM providers or sponsors may select some arbitrary (but usually not capricious) point along the continuums of response and deem that sufficient to call it a “success”, but this does not mean that participants who made progress short of success did not deliver any benefit. In fact, it will often be the case that a participant who started of at a lower level of the continuum of behaviors or conditions but makes a dramatic improvement short of success will yield far greater benefit than another who was only a bit short of the success level to begin with and improved only to that level.

So while we can talk about and measure “success rates” for purposes of counting successes, and perhaps paying success incentives, we should not ignore that there may be a continuous degree of positive change and benefit across almost all participants, perhaps even every one of them. Even participants who do nothing more than take the health risk assessment (HRA) or screenings and get action-oriented feedback, may well improve along some health dimension and as a result deliver some benefit, despite never participating in a particular HM initiative. Similarly, others may participate actively, alter their lifestyles, improve their health, etc. but not deliver any measurable benefit to the sponsor.

For these reasons, rather than concentrate on the success rate, i.e. some percentage of participants who achieve some arbitrary point on a given continuum, the most accurate way to describe the results of an HM intervention and overall program is to calculate the average benefit delivered by everyone who can be counted as having participated at all. Separate calculations can be made for those who did no more than take the HRA or screening tests vs. those who participated but did not complete the initiative vs. those who completed, etc. in order to track how much each degree of participation added to the average benefit. But the total value of the HM initiative or program should reflect the total benefit across everyone who participated in some meaningful way.

If there are no added costs for participation, per se, e.g. if the HM provider charges on a per population basis, and the sponsor does not offer incentives that have to be paid to participants, it will make no difference how many there are in terms of the costs to sponsors, though it may add to costs for providers. But when there are costs or charges incurred specifically for participants, the evaluation of results should probably differentiate degree of participation, to see if those who merely take an HRA, or participate for a few weeks deliver enough benefit to justify the costs. If not, then further investments in persuading or offering incentives for those who complete or make some defined amount of change may be needed to achieve an optimal result.

Fortunately, there is always available, though often difficult to implement, a simple “solution” that will automatically take care of most problems related to the fact that HM deals in continuous variables. If the employer adopts a pay-for-performance system for compensating employees, all those so compensated will automatically have their health and productivity/performance levels measured, and rewarded as they improve. If such improvements are due to health improvements, this should show up in the analysis of both how much participants have improved their health in order to achieve better performance. But as long as the productivity/performance dollar value of changes made by employees is measured and rewarded, the employer will be able to determine immediately whether investments have paid off.

Of course, P4P systems usually add to employers’ costs, whether or not they are tied to HM interventions. But they rarely increase costs as much as they increase the value that employers gain. For example, when a windshield repair firm switched to P4P vs. hourly wages, it found productivity increased by 44% in the first year of the new system, while overall employee compensation increased by only 10%. Employers have always known how to ensure that the firm gains an adequate if not lion’s share of any increased value that employees deliver. And employees have usually been satisfied with a fair share.

While it serves some internal measurement, planning and evaluation purposes to identify discrete points along the continuums that reflect HM results, it is the average of the continuous benefit dimension for sponsors, and the individual personal benefit for each participant that ultimately makes the most difference. Both the average sponsor benefit and the individual participant benefits should be the dominant focus of HM planning, management, and evaluation, reflecting the underlying continuous variables that represent the reality of HM effects. A few discrete “fictions” may be useful, but the continuous nature of HM’s effects should always be recognized and reflected in its use.