The opportunity: the discrete effects of price on payer access
The pharmaceuticals market is distinctive with respect to the relationship between price and demand. Unlike many competitive
markets in which there is a "smooth" demand curve—where a small change in price may result in corresponding decreases or increases
in volume ("demand elasticity")—the pharmaceuticals market has a more discrete demand response to price. Access decisions
are highly concentrated, with a relatively small number of payers controlling the bulk of pharmaceutical benefits. As prices
change, payers may or may not change the access level of a product (access includes dimensions such as copayment tiers, restrictions
such as prior authorizations and step-therapy requirements, and sometimes non–reimbursement of the product). Typically, payers
have different thresholds at which they consider access changes—and these thresholds can vary with the characteristics of
the therapeutic area, such as size of the category, severity of patient conditions, therapy options available and their cost,
etc. One payer may consider restricting access when price increases by 8 percent, while another may consider such action at
a somewhat higher price increase. Of course, most payers are concerned with their net costs, so price protection and other
contracts that provide rebates for preferred or non-disadvantaged formulary access mitigate the impact of list price increases
to some, but not all, benefit plans. Understanding the tipping points for individual payers is critical to correctly gauging
how to avoid "hitting the cliff" with price actions.
Finding the cliff
Determining the threshold price increases, or "cliffs," at which key payers respond with access changes is critical for optimizing
on-market pricing. This can be done through careful analysis of the historical formulary actions of payers, primary market
research, and sensitivity analysis of the impact of price changes under different assumptions. We have found that a hybrid
of qualitative and quantitative primary market research techniques, combined with analysis of historical list price data and
formulary outcomes, has been highly effective in identifying payer access thresholds and evaluating list price strategies
for specific brands and market situations.
To demonstrate the practical applicability of these methodologies, consider an example, product A, based on a real on-market
pricing study. In the study, we used interviews with payers to test threshold price increases generally, to identify levels
at which they might trigger a thorough review of pricing of all therapies in the category, and to determine specific responses
to price increases for product A. (We found it most effective to test a variety of attributes together with price to avoid
any bias that may result from focusing on price alone.) We found that increases in price resulted in no access response up
to a level of 9 percent annual price increase. Figure 2 illustrates how this translates directly to increases in revenue and
profit up to "the cliff." From the plan's perspective, price increases need to reach some threshold (both in absolute terms
and relative to price changes of competing products) where the cost and administrative burden of changing the formulary are
outweighed by savings realized from imposing restrictions intended to lower utilization of the product in favor of other,
lower-cost therapy options.
Figure 2: Research and analysis of access, revenue, and profit by annual price increase.
Analysis of the results suggest that the manufacturer can take a price increase of 8 to 9 percent per year without hitting
the cliff. It is possible to validate the research using historical data. Comparing the research results on payers' stated
behavior against historical data on actual payer responses (both in the category and in similar categories) the robustness
of the results can be established and the pricing strategy can be implemented with confidence.
As illustrated in Figure 2, which draws on primary market research with payers and can be validated with analysis of historical
formulary changes, increases in price translate directly to increases in revenue up to the "cliff." However, above this threshold
value, an access downgrade more than offsets the gains of the higher price. From the payer plan's perspective, price increases
need to reach some threshold (both in absolute terms and relative to price changes of competing products) where the cost and
administrative burden of changing the formulary are outweighed by savings realized from imposing restrictions intended to
lower utilization of the product in favor of other, lower-cost therapy options. We have found that there are opportunities
to increase price profitably based on research and analysis designed specifically to find the cliff for a particular brand.
However, decision makers need to keep in mind that the optimal price increase is typically somewhat lower than what would
be suggested by the "average" tipping point of payers, due to the asymmetry between risk and payoff as price increases approach
the cliff. Simulation analysis that accounts for the range of uncertainty of estimated payer thresholds can be particularly
valuable to ensure that hitting the cliff is avoided for even a small number of payers that may have significant impact and/or
influence in the market.
is a Vice President in Analysis Group's Menlo Park office. He can be reached at
is Managing Principal and is based in the firm's Boston office. He can be reached at