An Attribution of Value Framework for Combination Treatments

Value Health. 2025 Jan;28(1):72-80. doi: 10.1016/j.jval.2024.08.012. Epub 2024 Oct 29.

Abstract

Objectives: 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.

Methods: 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.

Results: 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.

Conclusions: 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.

Keywords: combination therapies; combination treatments; healthcare; pharmacoeconomics; pricing.

MeSH terms

  • Cost-Benefit Analysis*
  • Decision Making
  • Decision Support Techniques
  • Drug Therapy, Combination
  • Humans
  • Models, Economic
  • Quality-Adjusted Life Years