medicine may not be fully realized before certain obstacles to its adoption are
removed. Obstacles in public policy may range from an uncertain regulatory
framework (related to, e.g., assessment or reimbursement procedures), issues sur-
rounding the legal protection of patients’genetic data, the lack of comprehensive
health care information technology systems, and more. Our ability to perform
economic evaluations and outcomes research and inform decision makers about
the marginal benefits, costs, and overall cost-effectiveness of personalized technol-
ogies may prove another obstacle in the adoption and reimbursement of personal-
ized technologies. This debate is the focus of the current chapter.
This chapter aims to bring an overview of some of the methodological issues
related to the economic assessment of personalized medicine and the related out-
comes research, which are only recently started to be addressed. We put forward
examples of economic evaluations of personalized medicine products and highlight
some of the areas in which future methodological work may be required. We aim to
contribute to a growing debate on economic evaluations of personalized medicine
products.
The first section of this chapter presents the main concepts, ideas, and elements
of economic evaluations. The second section focuses on the differences between the
economic evaluations of drugs versus companion diagnostics and provides some
recent examples of cost-effectiveness studies in the area. The third section high-
lights the issues important for economic evaluations of companion diagnostics and
the areas in which these issues may be particularly relevant. Although we cannot
fully address all the methodological challenges that economic evaluations may face
in the light of personal medicine development or highlight all the potential obsta-
cles, we aim to contribute to a growing debate that addresses (and supports) the
development of innovative ways of health care delivery and drug development—
called personalized medicine.
2 Economic Evaluations in a Nutshell
The most common types of economic evaluations of health technologies are the
cost-effectiveness analysis (CEA) and its subform, the cost–utility analysis (CUA).
Both types of analysis evaluate (at least) two alternative interventions in terms of
their incremental benefits and costs and summarize the result in an incremental
cost-effectiveness ratio (ICER). The ICER thus represents the additional costs per
additional health unit produced by one intervention in comparison to a relevant
comparator (usually standard care or status quo). The main difference between the
two types of evaluations is the method used to describe the health benefits produced
by a health technology. In CEA, the benefits are measured in natural units such as
lives saved or life years gained, and the task of an economist performing the
evaluation is to estimate the cost per unit of outcome achieved—the cost per life
saved, for instance. CEA, however, does not permit a direct comparison of costs and
benefits acrossinterventions yielding different outcomes (for instance, cases
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