It occurred to me, after writing the sixth round in this series, that a discussion of which option would work best in which circumstances might add some value. The fact that all methods of health management (HM) pricing can be compared to each other, by both providers and clients, means that there is always a choice that could be made among them, by either or both. But there are situations where one or a combination of them might work better.

The flat fee for a population, which is then easily translated into costs per insured plan member or employee, is probably best for the initial step in managing health, namely the risk assessment process. Since medical claims from insurance data are generated to enable providers to obtain payment from payors, they are rarely accurate or complete when it comes to identifying even the sicknesses that cause sick care costs, much less the behaviors and conditions that cause impairment in employee productivity and performance. Conducting a health risk assessment (HRA), using any combination of surveys, tests and scans, should be done whenever employed populations are involved, and is useful even when insured populations or only sickness care costs are the focus of the HM effort.

A fixed fee for an HRA, together with incentives and employer or insurer efforts to promote participation therein should promote something close to 100% participation, since without information on the risk behaviors, risk conditions, chronic diseases and impairment factors affecting employees, the rest of any employee health management process will be flying blind. HRAs for unemployed populations can be much shorter than for employed, so should not need as much promotion or incentives to promote total participation. They should add to claims information by asking about participants’ readiness to change, motivations, goals, etc. which will be important in designing and implementing HM interventions.

Flat fees can also be helpful in keeping costs down, since they are can be safely used only by lowest-cost HM providers whose own costs do not increase much as participation rates increase. And they are the only fees that enable prediction of costs by HM sponsors before participation is predicted or known. When increasing participation adds significantly to providers’ and sponsors’ costs, flat fees make little or no sense, however.

2. Per Eligible

Since the numbers of people eligible to participate does not equate to the numbers who will eventually deliver value to HM sponsors, the only reason to use this pricing method is to promote participation promotion efforts by sponsors. If fees are set based on the numbers eligible, then it will not cost sponsors anything extra to achieve as much as 100% participation. Of course, HM providers whose costs increase significantly based on numbers of participants will likely base their per eligible charges on the costs of 100% participation, so sponsors could pay far more than it is worth if they accept per eligible fees without knowing they can achieve high participation.

Whenever sponsors benefit by achieving high participation, the use of incentives becomes more likely, and costs per participant will increase. This means that achieving close to 100% participation in order to maximize participation might not optimize ROI, since the costs per participant will rise with incentives. Particularly for new clients of HM providers, per eligible pricing should probably be avoided, since insurers or employers new to HM are unlikely to know what high participation might cost them, or how high a level they might achieve without incentives. If ‘veteran’ clients feel they can get lower fees through charges per eligible, then achieve close to 100% participation at acceptable costs, they may prefer this form of pricing, but HM providers should not under such circumstances.

3. Per Participant

This form of pricing makes the most sense when HM intervention costs increase significantly per participant, since only participants figure to deliver any benefit to HM sponsors. (Experience with the effects of taking an HRA alone are mixed at best, with the level of benefit from even those where measurable benefit is gained being pretty low.) Of course, it also adds the greatest motivation to HM providers to promote participation, in order to maximize their revenue. The problem arises whenever participants vary in terms of their risk-reward probabilities and benefit potential.

When there is great variation across participants, it makes sense for the HM interventions applied to different risk/reward segments — such as minimal, low, average, good and high – to vary in prices along with costs to both providers and clients. Of course, in order to get good predictive information on populations at risk, additional costs for predictive modeling (PM) and analysis will be incurred. And since HRAs to be used for such analysis tend to be longer, incentives for taking HRAs will often have to be greater as well, adding still further to costs.

However, good predictive modeling, offered by PM specialists such as MedAI.com in Orlando, Florida, can greatly improve the identification of relative risk/reward potential across individuals, and thereby enable sponsors and providers alike to tailor their interventions and cost accordingly. This can easily reduce overall HM intervention costs enough to make up for added incentives for HRA participation, and costs for PM analysis.

4. Risk/Reward

This method of pricing, almost always used as an add-on to one of the preceding three basic pricing options, can add value for both providers and clients. Providers can use it to promote confidence among new prospects or first-time clients that they will obtain the results they are after. This means that HM providers should gain more clients by using this approach than they would if there were no confidence-building risk/reward element in pricing – warranties, guarantees, or pay for performance.

When provider/client relationships include high levels of mutual trust, this approach may work for as long as the relationship lasts, though normally past experience will supply enough confidence in clients to reduce the need for and effect of risk/reward arrangements. In any case, the promised results in such arrangements should be adjusted from year to year in most cases, since HM effects tend to increase with time, particularly among stable populations with low turnover. And the determination of risk/reward arrangements can get very complex when there are a variety of risk-graduated interventions for participants in the same HM category, as well as many different HM categories of interventions being applied.

Both providers and clients would be better served if they dealt with pricing arrangements as mutual challenges, sitting on the same side of the table to solve the problem, rather than relying on either simple set-price-yes-or-no decisions, or adversarial negotiations. HM relationships should be intended, by both providers and clients, as lasting ones, rather than one-time purchases, since HM benefits tend to increase over time, while its costs can often decline.
And like all elements of the HM relationship, pricing should be subject to mutually beneficial adjustment, in both amount and approach, over time. In particular, it should be open to risk/reward-based graduation of charges based on tiered intensity, type, frequency, and other elements of specific interventions, when these are found to be the optimal approach to delivering value. Many HM providers that once employed one standard approach, such as Healthways, Inc. in Nashville, have expanded their array of interventions to include more options in order to match their interventions to the risk/reward potential of different segments of the populations they serve.

The Duke Prospective Health Program, offered by Duke University Health to employees and dependents who are members of its self-insured health plans, graduates the support it provides to HM participants. All get basic education/information support, but those with higher risk/reward potential may also be eligible for personal coaching and case management services. Matching the HM intervention and charges to different levels of risk/reward potential is likely to be the best approach to optimizing HM results and ROI, though figuring out the best matches requires both time and expense