Whether health care organizations (HCOs) purchase health management (HM) services from outside sources, or choose to be outside suppliers of such services for others, the question of how to pay or charge, as well as how much, is a major factor in achieving success.  How much to pay, compared to how much economic benefit HM yields for payors or employers, will largely determine whether it makes any sense to invest in HM in the first place, and in which specific HM challenges.

How much it would cost to choose one provider of HM services over another is equally a function of what competing providers charge and what they deliver in terms of economic benefit.  While HCOs or their clients may focus on effects of HM services on the health and life quality of the people affected, but few will consider HM services or providers that do not also yield a positive return on investment (ROI) as well, in terms of financial performance.  And since ROI is a function of what has to be paid compared to what financial amounts have to be invested, the paying/charging question is often paramount.

There are essentially four different approaches to charging and paying for health management (HM) services:

1.    Flat fees or per population member charges
2.    Charges based on the numbers of people “eligible” for specific HM services
3.    Charges based on the numbers of people who participate in specific HM programs
4.    Results-based charges

The choice of charging approach can make a dramatic difference in how HM providers and clients behave with respect to HM investments, and to the level of success achieved.  And this choice is greatly affected by the type of HM intervention that will be applied.

A Flat fee or a charge per member of an employee or insurance plan population, is the simplest, and the only one that can be quoted by HM providers, or predicted by HM clients, in advance of an HM intervention.  To employ a fee system based on the numbers eligible for HM services, or the number who participate in a given HM initiative, and certainly to base charges on the results achieved requires the kind of health risk assessment (HRA) of the population that is normally the first step of an HM intervention.  By contrast, a flat fee may be set regardless of the number of people in the population, or be affected by that number, and be set before there is any more information available than the number of its members.

The flat fee or per member approach makes sense only when the cost of the HM intervention to the provider thereof is more or less independent of the number of members of the population at risk who have the risk behavior, condition, or disease that particular HM interventions address.  It can also make sense when the HM program is a general health/well-being effort that everyone in that population will benefit from.

The fee per eligible member – per person found to have a particular risk behavior, risk condition, or chronic disease – makes sense in that only such people are logical prospects for HM interventions that address them, and can therefore become sources of related economic benefits to the HCO as payor, or to its client.  Of course, not all eligibles will participate in a given HM intervention, so not all will yield such a benefit, but the potential, at least, is there.

A fee per participant can make the most up front sense, but it may cause the HCO or its client to be far too conservative in its investment, seeking to enroll only those members who have the highest probability of returning a positive ROI and the highest ROI possible.  This can result in enrolling far fewer members than is the optimal number in terms of total economic impact, and merely the members that deliver the highest ROI ratio.

A charge or payment scheme that is based on the results achieved, whether through a warranty, a guarantee, or a risk/reward contract, is easily the riskiest for the HM provider, though may be the most popular among HCOs or outside clients investing in HM for the first time.  All three of the other payment/charge methods put the risk on the client, though HM providers that do not deliver the expected or at least an acceptable ROI should not usually expect to retain their clients.

Each of the four methods involves slightly different effects in terms of the HM investment decision.  Each of the four will be discussed in detail in a series of blog entries that will follow this one

Paying a flat fee for a particular HM program, or one that is based on the number of people in the population at risk, is the simplest of all charge methods.  It enables HM providers to predict their revenue, and HM prospects/clients to know what their costs will be before the HM program is purchased or implemented.  This means HM purchasers can compare the costs of competing options, as long as they use the same flat or per member fee approach.  It makes budgeting for clients simple as far as costs are concerned.

The predictability of costs is often what makes this approach attractive to clients, whether insurance plans or employers, and the predictability of revenue is attractive to providers, as well.  But the predictability of costs comes with an almost total unpredictability of results. Since these are definitely important in budget planning for clients, it can complicate the budget process overall.  In order to predict results, clients must be able to predict: 1) what the effects of participation in specific HM interventions will be; 2) how many individuals in the population might benefit from each intervention; and 3) how many of these will participate in each.

HM providers should be able to describe what the average effects of each of their interventions has been in the past, perhaps even promise or guarantee some minimum level of effects per participant.  But clients will usually know up front how many of their plan members or employees will be eligible for any particular intervention, unless they have already performed the claims analysis, screening, or health risk assessment (HRA) required to do so.

Moreover, predicting the number of eligible members that will participate in particular HM interventions is impossible up front, since what the client or provider offers in the way of incentives and rewards for doing so has a powerful impact on that.  Such a prediction is largely dependent on decisions regarding enrollment effort and incentives, rather than merely characteristics of the population at risk.  And since incentives and enrollment efforts add to costs, these decisions must be made before prospects can estimate their ROI, and providers determine their costs, depending on who is responsible for paying the incentives.  To complicate up front planning still further, incentives are only paid to members who participate in the HM intervention, and the number of members who will do so is difficult to predict.

On the other hand, charges that are based on flat fees or per employee rates are usually used by the lowest-cost HM providers.  This is because the only kinds of HM interventions that can be charged for in this way are those whose costs to the provider can be predicted up front as well, without knowing how many members of the population will participate in particular interventions.  This means the HM interventions must vary only modestly in costs to providers based on the numbers of population members that participate.

When HM interventions use expensive face visits or phone contacts with professionals as their basic HM intervention method, the costs for programs vary almost totally based on the numbers of people to be managed.  The number and duration of such the personal contacts involved per participant may vary based on the risk/reward potential of individuals or different segments in the population at risk, but this potential can only be estimated based on past provider experience up front. To improve predictability of the numbers of people who should participate in an HM intervention, the HM program must have already been implemented, at least as far as conducting a health risk assessment (HRA) of the population.

By contrast, even before HRAs are conducted, HM providers that employ computer-automated HRA analysis and HM coaching that consists of automatically customized recommendations, coaching and feedback to participants, can project their costs well enough to charge on a flat fee or per employee basis for each HM program they offer.  Once HRAs are completed, prospects can choose how many and which HM interventions to purchase, based on predictable costs and results.

For example, HealthMedia, Inc. of Ann Arbor, Michigan, is such an HM provider, offering HM programs to insurers, including Kaiser Permanente, and to employers.  It charges on a flat fee basis, with the flat fee adjusted for different population sizes.  The fee for a single HM program for a population of 1000 is $9000, which amounts to $9 per population member.  The fee for a single program for a population of 10,000 is $44,000, or $4.40 per member.  Fees are lower in total for smaller populations, but higher per member, and higher in total, but lower per member for larger populations.

HealthMedia also offers a discounted rate for added HM programs, with costs per member per program lower when multiple programs are offered.  But even with the figures cited above (supplied by e-mail on Aug 30, 2007) these fixed costs can be easily translated into predictable costs per participant once the numbers of people to be targeted/eligible and the predicted participation rates are estimated.  Based on just the numbers eligible, the number of participants needed to make an individual HM program attractive for a given insurer or employer can be calculated.

Flat/per member fees are the simplest payment approach, and make budgeting easier because costs to clients and revenue for providers can be, they fall short in terms of predicting likely benefits.  Predicting the reductions in sickness care costs and the potential increase in health care costs needed to achieve such reductions, for example, requires knowing how many members of the population are likely targets, will participate, and will change their health behaviors enough to make a difference. Predicting reductions in labor costs among employees, due to reduced absenteeism, presenteeism, and turnover — or increases in revenue due to improved quality, customer loyalty, and new business revenue – requires the same information.

The fixed/per member fee approach may be preferred for initial HM trials, but one of the other options may make more sense to at least some prospects, and particularly to clients once they know more about their members, and about the effectiveness of the interventions.  On the other hand, this approach often comes with the lowest fees around, so may be preferred by even “veteran” clients.