The use of cost-effectiveness methods to support policy decisions has become well established, but difficulties can arise when evaluating a new treatment that is indicated to be used in combination with an established backbone treatment. If the latter has been priced close to the decision maker’s willingness-to-pay threshold, this may mean that there is no headroom for the new treatment to demonstrate value, at any price, even if the combination is clinically effective. Without a mechanism for attributing value to component treatments within a combination therapy, the health system risks generating negative funding decisions for combinations of proven clinical benefit to patients. The aim of this work was to define a value attribution methodology, which could be used to allocate value between the components of any combination treatment.
The framework is grounded in the standard decision rules of cost-effectiveness analysis and provides solutions according to key features of the problem: perfect/imperfect information about component treatment monotherapy effects and balanced/unbalanced market power between their manufacturers.
The share of incremental value varies depending on whether there is perfect/imperfect information and balance/imbalance of market power, with some scenarios requiring the manufacturers to negotiate a share of the incremental value within a range defined by the framework.
It is possible to define a framework that is independent of price and focuses on benefits expressed as quality-adjusted life-year gains (and/or quality-adjusted life-year equivalents for cost savings), a standard metric used by many health technology assessment agencies to evaluate novel treatments.
This research addresses the challenges of evaluating combination treatments in healthcare, particularly in oncology, where multiple medications are used together. As the understanding of diseases has advanced, combination therapies have become more common because they often work better than single treatments alone. However, traditional cost-effectiveness methods struggle to assess the value of these combination therapies, which can lead to negative funding decisions and limit patient access to beneficial treatments. The aim of this study was to create a framework that helps determine how to allocate value among the different drugs in a combination treatment.
The proposed framework operates under established cost-effectiveness analysis principles, focusing on the benefits measured in quality-adjusted life years (QALYs). It recognizes that the value attributed to each component of a combination treatment can vary based on the availability of information about their individual effects and the market power of their manufacturers. For instance, if one drug is well-established and the other is new, the established drug might hold more pricing power, affecting how value is shared.
The study highlights that combination treatments can be evaluated differently depending on whether there is complete or incomplete knowledge about the effects of each drug. When there is good information, value can be fairly allocated based on their individual contributions to health outcomes. However, when information is lacking, negotiations between manufacturers become crucial to determining how value is divided. This is important because it impacts the ability to price these combination treatments effectively and ensures that patients can access innovative therapies.
Additionally, the research emphasizes the need for cooperation among all stakeholders, including drug manufacturers, healthcare decision makers, and payers, to establish fair pricing and improve access to effective treatments. By introducing this framework, the study aims to foster discussions that could lead to better negotiation strategies and ultimately ensure that patients benefit from the latest combination therapies.
In conclusion, this framework offers a starting point for addressing the complexities of establishing the value of combination treatments, aiming to facilitate patient access to essential therapies, while also ensuring that healthcare systems can sustainably manage costs.