درک ارزش پزشکی و غیر داروئی از آزمون های تشخیصی

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.