Payers often conduct a budget impact analysis to assess the affordability of a new offering, such as a drug, medical device, diagnostic test, procedure, or service. The supporting models are based on assumptions, data, and calculations, and the insights that result help to inform formulary and medical policy decisions.
But payers do not always conduct a budget impact analysis. Many market access decisions follow heuristics, not insights flowing from a budget impact analysis. If these decisions had packaging, they would be labeled “Analytics not included.”
When payers believe a budget impact analysis is desirable, investments in the model are proportional to the perceived importance of the therapeutic area. Models for high-cost, high-prevalence conditions, such as hepatitis C, will attract greater investments of time and money than repurposed or tweaked models that often are used for a low-cost condition or a high-cost, rare condition.
Payer analyses include the cost of doing business
Payers always consider the costs involved in managing a new offering. Restricting access — or utilization management (UM), more broadly — is not free, although it may be budget-neutral or even yield savings. Some restrictions, like step edits, are inexpensive to implement. In contrast, some restrictions — like prior authorizations — can be quite costly, especially when the costs associated with appeals are factored in.
Because UM carries costs, those costs should be factored into the total budget impact of a new offering. Leading organizations seem to support this thinking. In 2012, an International Society for Pharmacoeconomics and Outcomes Research (ISPOR) budget impact analysis task force described access restrictions as “important features” of the health care system that can impact “use or reimbursement as well as uptake.” And while the ISPOR report noted the effects of UM, it curiously failed to identify the costs of UM itself. The Academy of Managed Care Pharmacy (AMCP) Format for Formulary Submissions — which references the ISPOR guidance — adds new draft language in version 4.0 to “include the economic impact of special handling, delivery, route and site of administration, REMS programs, and other administrative offsets that would be above and beyond the cost of the product.”
Payers implement restrictions only when they believe the cost of their restriction is lower than the savings that result. UM costs without an ROI will erode profit margins. And while the Affordable Care Act includes quality-improvement expenses in the medical-loss ratio (MLR) numerator, UM costs that do not lead to measurable quality improvements are not included in the MLR numerator. As a result, payers have good reasons to pick UM battles carefully.
Manufacturer analyses — low risk, low reward
Manufacturers frequently look for ways to enhance the value of their offerings. What better way than to offer payers a budget impact analysis? Though the AMCP offers guidance on how to submit an analysis with a dossier, manufacturers are not required to do so. Still, many do, knowing that the predictable and relatively small cost of these investments make them low risk.
There is little evidence, however, to suggest that a manufacturer’s budget impact analysis is an effective means for improving access to its offering. Payers generally discount or ignore manufacturer-sponsored budget impact analyses, for several reasons. The sheer volume of models presented to payers produces a numbing effect. Many models do not resonate with payers because they focus on brands and therapeutic areas not on payers’ radar. Payers are also skeptical about the objectivity of manufacturer-sponsored models, which always suggest that the sponsor’s offering will have a favorable budget impact.
A manufacturer-sponsored black box model creates uncertainty about the applicability of a model to a payer’s population or local market dynamics. On the other hand, a transparent model increases the likelihood that a payer will conclude that the assumptions, data, or calculations do not apply to it. Manufacturer-sponsored models, then, typically fall on a continuum ranging from “uncertainty of applicability” on one end to “certainty of inapplicability” at the other. Pick your poison.
Even when the model’s underlying assumptions, data, and calculations are both transparent and “open,” or modifiable, fully understanding the behavior of a manufacturer-sponsored model may take payers nearly as many hours and resources as it would take to build or revise a model in-house. This explains why large sophisticated payers prefer to conduct their own budget impact analysis.
Payers typically view manufacturers’ efforts to produce these models with some level of frustration. Rather than a manufacturer spending money on a budget impact analysis, payers would prefer the manufacturer to simply lower the cost of the offering. While the intent of a manufacturer-sponsored budget impact analysis is to add value to an offering, negative payer reactions are a potential unintended consequence, not to mention an undesirable one.
Manufacturers should focus upstream, not downstream
When it comes to a budget impact analysis, one might ask, “Is the juice worth the squeeze?” Payers will typically get it right and squeeze just the right amount of juice out of each model. Manufacturers, however, will likely get it wrong. Unless a manufacturer has information the payer would value and doesn’t already possess, then it is well advised to resist pressure to develop a budget impact analysis.
If a manufacturer wants to provide payers with convincing evidence that an offering can positively impact their budgets, then endpoints with associated measurable cost offsets (e.g., reductions in ED visits, hospital admissions, readmissions and length of stay) should be rigorously captured during trials and program evaluations.
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