The CEA Registry Blog

May 1

by CEA Registry Team 5/1/2017 9:51 AM  RssIcon

 Cost-effectiveness analysis (CEA) has been a major approach of evaluating the value of medical technology. The general idea is that if a technology is considered cost-effective (i.e., an incremental cost-effectiveness ratio (ICER) is lower than a specified cost-effectiveness threshold), the technology should be available for use in the health care. However, critical assumptions in the ICER are the use of an average treatment effect and complete adoption in practice. These assumptions are unlikely to be realistic – First, heterogeneity in treatment effect may exist; Second, heterogeneous effectiveness may lead to the differential adoption across subgroups; Third, the design of different policies (e.g., value-based insurance design) may also influence adoption behaviors in practice.   

In our new paper in Medical Decision Making, we proposed new metrics from ‘policy’ evaluation perspective by introducing weighted average ICERs that incorporates subgroup-specific adoption rates and heterogeneous effectiveness. We also extended this framework to consider parameter uncertainty to link with existing value of information metrics. This new framework will be useful to estimate the realized value of technologies based on how they will actually be used in practice.  Also, the proposed metrics may have a potential to improve the decision-making process by producing metrics that are better aligned with the specific policy decisions rather than just focusing on the evaluation of treatment alternatives.
 
Reference
Kim, D. D. and A. Basu "New Metrics for Economic Evaluation in the Presence of Heterogeneity: Focusing on Evaluating Policy Alternatives Rather than Treatment Alternatives." Medical Decision Making 0(0): 0272989X17702379.

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