value of a health outcome that, at least in theory, can encompass all aspects of a
health improvement.
Patients can benefit from companion diagnostics because these can reduce the
patient’s uncertainty about the likelihood of successful treatment and generate the
“value of knowing” as a result. The value of knowing may also be estimated using
contingent valuations to obtain willingness-to-pay estimates that can be, for
instance, used in cost-benefit analysis. As argued before, the value of receiving
both the knowledge about the likely result and the best possible advice carries great
merit and has value for patients and for physicians, and it may be desirable to
express this value using a common metric, such as willingness to pay. It may be
interesting to further explore this issue empirically. Diagnostic or predictive tests
that do not accompany a particular treatment also have been shown to carry value.
Neumann et al. ( 2012 ) showed that the willingness to pay for predictive tests is
positive, even in the absence of direct treatment consequences of the test. The
positive estimates of willingness to pay for predictive tests reflect both health- and
nonhealth-related benefits, hence suggesting that conventional cost-effectiveness
analysis that is primarily concerned with health-related benefits probably underes-
timates the value of testing.
Tailoring therapy and determining the optimal treatment strategy will increas-
ingly require adhering to and understanding of patient’s preferences and increasing
patients’participation, hence creating a more participatory health care system, even
irrespective of the development in personalized medicine. This is especially the
case in situations where companion diagnostics will signal that available medical
treatments will be unlikely to bring health improvements. The increasing relevance
of patients’preferences in designing treatment strategies brought, among else, by
increasing certainty in treatment outcomes facilitated by companion diagnostics
may additionally foster the development and use of broader measures of health,
beyond a QALY, that are better able to capture broader benefits. Economic eval-
uations may be increasingly called upon to model and account for a large amount of
patients’direct preferences about different treatment options.
Since personalized medicine generally can be considered as innovative and
technologically advanced, a part of the value attached to it may stem precisely
from its innovative character. Given the potential benefits that the development of
personalized medicine products carries, policy makers might need to further
develop a decision-making system that increasingly fosters innovation. Although
innovation and new technologies are conventionally seen as a major source of cost
inflation within health care systems, they are also a very important for improving
the quality of care and health more generally. To determine the real value of
innovation and ensure that there are sufficient incentives for private investment in
the development of socially valuable innovations, a well-structured policy regard-
ing the social value of a health technology is required, and the relationship between
value and price determined, and the incentives for private sector investment
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