Objectives
To develop a framework for defining the potential value of diagnostic testing, and discuss its implications for the health-care delivery system.
Methods
We reviewed the conceptual and empirical literature related to the valuing of diagnostic tests, and used this information to create a framework for characterizing their value. We then made inferences about the impact of this framework on health insurance coverage, health technology assessment, physician–patient relationships, and public health policy.
Results
Three dimensions can effectively classify the potential value created by diagnostic tests: 1) medical value (impact on treatment decisions); 2) planning value (affect on patients' ability to make better life decisions); and 3) psychic value (how test information affects patients' sense of self). This comprehensive framework for valuing diagnostics suggests that existing health technology assessments may systematically under- or overvalue diagnostics, leading to potentially incorrect conclusions about cost-effectiveness. Further, failure to account for all value dimensions may lead to distorted payments under a value-based health-care system.
Conclusions
The potential value created by medical diagnostics incorporates medical value as well as value associated with well-being and planning. Consideration of all three dimensions has important implications for technology assessment and value-based payment.
Health policy experts have called for a “value-based” US healthcare
system in which providers would compete for patients on
the basis of price and quality, and payments would be based on
value provided rather than costs [1]. Although the impact of such
a system is uncertain, some have suggested that it could reduce
overall US health expenditures by as much as 30% without
adversely affecting medical outcomes [2]. Others note that valuebased
approaches could encourage employees to choose healthier
lifestyles, higher-quality providers, and more effective treatments
[3]. They may also help to rationalize drug benefits [4] and
enhance patients’ compliance with chronic medications [5]. As
one observer recently noted, “ ‘value-based’ is the preferred
health care prefix of our era [6].”
The success of a value-based system hinges on valid definitions
and measures of value across the spectrum of health-care
services. This has largely been taken for granted, but there is not
yet a shared meaning of “value” or systems in place capable of
measuring it. Consider, for example, the current debate over
advanced diagnostic imaging. Physicians cite new imaging techniques
as an example of truly essential medical innovation [7,8];
however, some policymakers have questioned its value [9,10],
and rapid growth in spending for diagnostic services in the Medicare
program has led to congressionally mandated reimbursement
cuts [11]. This disconnection between those convinced of
imaging’s value and those questioning it underscores the challenges
of implementing a US value-based health-care system.
For surgical or pharmacological treatments, the concept of
value is relatively straightforward. Life expectancy and quality of
life have been measured—albeit with some controversy—using
standard health technology assessment techniques [12]. But as
Fryback and Thornbury have noted, these value measurement
techniques are more difficult to apply to diagnostics because their
clinical impact depends upon the sequelae of clinical interventions.
In other words, diagnostics affect treatment decisions, and
treatment decisions affect outcomes [13]. Asch et al. further
observed that clinical impact alone is an insufficient measure of
value for diagnostics because diagnostics also have the potential
to affect patients’ sense of psychic value whether or not they
affect treatment [14]. For example, a diagnostic test for dementia
may have relatively little impact on treatment or outcomes, but
may have a substantial effect on the patient’s psychic value.
This article has several objectives that contribute to the literature
on the value of diagnostic tests. First, it seeks to highlight
the potential value of diagnostic testing for medical decisionmaking.
Second, the particular dimension of value on which we
focus is the value of diagnostic testing in resolving patients’
uncertainty about their medical conditions. This dimension of
value—what we term the “value of knowing”—has been largely
ignored in the cost-benefit literature. But it is important to recognize
this dimension of value, both for more accurate economic
evaluations of health-care treatments and technologies, and for
appropriate design of health insurance policies. A third aim is
to discuss the implications of this framework for policymaking,
health technology assessment, optimal insurance design, the
physician–patient relationship, and public health policy. Finally,
we explore the obstacles to measuring the value of diagnostics,
and offer some possible strategies for overcoming them.
There are many challenges in incorporating all dimensions of
diagnostic value—medical, planning, and psychic value—into
health-care technology assessments. Nevertheless, failure to do
so runs the risk of biasing economic evaluations, leading to the
misallocation of health-care resources. This problem will only
become more widespread as the number of new diagnostic tests
proliferates. Thus, it is now critical to consider strategies that promote more and better evidence on the value of knowing, and
to use this information in health-care technology assessments.
These strategies include promoting and financing research on the
value of knowing, and educating government and payers that the
value of knowing may really matter to patients.
In terms of research, more empirical evidence is needed. Such
evidence may be obtained using a willingness to pay, willingness
to accept framework, as outlined by Rizzo and Lee [18]. Ideally,
this effort should be disease-specific, and should recognize consumer
heterogeneity; that is, consumers will likely place differential
value on “knowing for knowing’s sake” because they differ
in terms of their attitudes toward risk, time preference, the extent
to which they will worry about adverse future outcomes, and
other dimensions. Obviously, funding will be required to realize
this research agenda. Given the public interest in quantifying this
outcome, public funding sources may play a key initial role in
helping to refine methodologies to ascertain evidence on the
value of knowing and promoting initial surveys that are designed
to assess the value of knowing for specific diseases and tests.
Psychic value from knowing may also be present in other
types of medical services apart from diagnostic tests. For
example, seeing a specialist may be reassuring even if it has no
effect on treatment. Similarly, a placebo effect from a drug may
confer psychic value although it does not improve medical
outcomes.
Enabling the transformation to a broad value-based system
will require well-grounded measurements of the value of all
health-care services, including diagnostics. Building on the conceptual
framework presented here, it should be possible to
measure the value of diagnostics with better accuracy than
current methods permit. Doing so can support more effective
payment policies, technology assessments, clinical decisions, and
public health campaigns.