The relevance of value in establishing the positioning of medicines is the new normal for pharmaceutical marketing. Pharmaceutical companies have customers who are highly constrained by whether healthcare system funding is sustainable long term. Remember, payers think epidemiologically and in multiple years of costed care so industry needs to assess how that can be understood for product value. The pharmaceutical industry is constrained by its ability to generate revenues from medicines sales to cover the costs of research and development.

These two collide in the decision making process to adopt, or not, a medicine. The payers broadly have to balance the sustainability of their budgets with a potentially innovative medicine that will improve care outcomes. The pharmaceutical companies have to construct the value case to demonstrate these care outcomes. That probably means at least two things among many;

1. Stop pricing drugs by the pill or pack, and start pricing valued outcomes for a defined set of patients over a number of treatment years, and
2. Forget about trying to ‘time’ the market for product launch. The right time is set by payer budget cycles and their drug investment and disinvestment decisions. And, oh yes, the evidence.

By the way, my approach does differ from the journey model of Ed Schoonveld in important respects, by identifying the structured, and gated, decision processes involved; that why medicines aren’t sold, but bought.

Let’s first look at the colliding priorities. The diagram shows that payers are concerned with the value of a medicine in minimising treatment risk for the treated population. A company is seeking the value of the medicine by maximising the size of the treatment population that they believe benefits. As you grow the treatable population beyond the evidence, risk rises; for payers, reducing that risk is addressed through evidence.

This is a collision of notions of ‘uncertainty’ in decision making and folks on the industry side should be used to requests for more evidence and novel access arrangements such as conditional reimbursement with evidence generation, and so on. As in any model of competing interests seeking a common price, the intersection of these two notions of uncertainty is defined by a price at which both parties will agree the price pays for the uncertainty it quantifies (i.e. it quantifies uncertainty in a certain way). The intersect quantifies risk, and sets the size of the treatment population that can benefit for that price.

The resulting curve may be thought of the ‘community effectiveness curve‘ depicting the optimal balancing of risk for the treatment community and a proxy for price agreement along that curve. This, by the way, is a better way to identify price corridors for people who still think that way.

This structured process is what this article is about.

Here is the gated decision process for payer decision making. While payers may not formally see themselves going through this in a linear way, they are thinking these thoughts, in this order.

From the payer perspective, information needs to be specific to the decision gate and having the wrong information at the wrong time (e.g. the right information at the wrong gate) will just frustrate folks and probably irritate decision makers.

The diagram is read left to right, and a ‘yes’ answer to a question is needed in order to move through the gate. Getting a ‘no’ means the information supplied failed to make the case.

The following is a quick tour of the underlying logic. By the way, I call this a gated process as there are criteria for satisfying the conditions for passing through the gate; it is, I believe, unhelpful to decision making to characterise them as hurdles, as this suggests they are imposed to make life difficult. They are, actually, simply the structure of decision making.

Looking at this from a behavioural perspective, i.e. psychology informing decision making, each gate means this:

• To get through the first gate, the payer is confronted with existing treatment options and asks why do I need another, or why change? Unfamiliarity may also be at work, with novel treatment benefits that lack comparators. Evidence of unmet need might be helpful along with good epidemiology to demonstrate the possibility of better outcomes.
• Satisfied that a new therapy may be warranted, there is the question of risk and benefit compared to current treatment. While a new therapy might be indicated (yours?), the associated risk may be unacceptable compared to not using it. The benefits really do have to hold under increased uncertainty for a payer to agree to increased treatment risk. I suggest this is where discussion of standards of care begin to be quantified, having been introduced at the first gate. Payers often are not as aware as they should be on the current standards of care evidence in misdiagnosis, medical error and patient dissatisfaction.
• Then having agreed that this uncertainty and its associated risk are acceptable, we are confronted with the cost and efficacy issue. Now we are beginning to price that risk. Good analysis of the costs of care and mis-care are useful, again because payers are not often aware of whole system costs (i.e. the costs of a treatment pathway) either because they are using using a fee schedule linked to DRG type classification or haven’t proofed their capitation models.
• Success in pricing that risk moves to the question of the medicine in the context of total treatment costs and whether the treatment costs themselves for the patient population can be managed or will the scaling of the costs overwhelm the system for this treatment population versus all other options. Companies may see themselves as just suppliers of medicines for a price, and not a partner in the total system. But understanding the cost drivers along the whole treatment pathway, not just the costs a new medicine may drive, becomes an important element in final value pricing. If you have a medicine that reduces associated costs, or avoids certain costs (think the Triple Aim, here), then the determinants of value are much clearer. It may be that a biomarker is a value-add from one perspective but only if it reduces medical error and misdiagnosis, without increasing costs, so precision patient identification becomes important. If you’ve got this far, though, you’ll have already shown you can demarcate the treatment population, including the responder subset with a degree of precision.
• Finally, the payer thinks about the future and whether there will be new medicines coming along that might address the same treatment population, alter risk differently, improve outcomes, avoid costs, with better patient adherence, and so on. Given, broadly, a medicine is alone in its treatment class for months, rather than years, payers may choose to delay decision making or consider options you’ve ignored that may trade off future costs and present priorities. This may be where a payer will be thinking disinvestment or product substitution and the determinants of that are critical in this final phase. Here’s a scenario: Why might a particular medicine not be a preferred medicine on a hospital formulary? The answer is simple: don’t have production problems where supply cannot be guaranteed. The lesson is that this is where the long game gets played out.

For those of you who read Kahneman’s “Thinking Fast and Slow”, or similar, there are decisional heuristics at work here. And across that gated process, you are contending not just with highly structured evidence informed quantitative information, but also how humans can be influenced by how human’s think they think. This has a raft of factors such as confirmation bias, hyperbolic discounting, choice overload, loss aversion, endowment effect, anchoring, mental accounting and social proof. It will pay to be attentive to when you present what information and the frame of mind decision makers are in. The reason this is important is that that regulators and payers in different countries, hospitals or regions can make different decisions from the same evidence, so something else is going on.

And so, a comment on pricing. To short-circuit this challenging gated process, it is common simply to cut the price, i.e. discount. Discounting is a quick win trick that only works if payers are trying to reduce present costs, which they all are. However, payers with their eye on the future are more likely to be interested in pricing arrangements that address uncertainty over time and so will be amendable to arrangements such as coverage with evidence development or outcomes guarantee. If they are focused on whole system issues, they will be interested in care pathway (cohort/whole system) pricing for instance. If, though, the future costs are a priority, think about capitation arrangements, or simple price/volume but be mindful that this last is like selling products door-to-door in the 1950’s.

I happen to think care pathway pricing of carefully demarcated patient populations with costs taken over say 5 years is a better pricing model for both parties. Value can be demonstrated on both sides along with evidence of such things as improved adherence (to reduce waste by non-responders) or diagnostic decision support aids to address misdiagnosis and sources of medical error or reduce time to the correct diagnosis, in the case of rare diseases for instance.

This article is designed to emphasise product value determination under conditions of uncertainty to arrive at a sustainable long-term relationship.