Quantifying benefit–risk preferences for medical interventions: An overview of a growing empirical literature
Hauber, A., Fairchild, A., & Johnson, F. (2013). Quantifying benefit–risk preferences for medical interventions: An overview of a growing empirical literature. Applied Health Economics and Health Policy, 11(4), 319-329. DOI: 10.1007/s40258-013-0028-y
Decisions regarding the development, regulation, sale, and utilization of pharmaceutical and medical interventions require an evaluation of the balance between benefits and risks. Such evaluations are subject to two fundamental challenges—measuring the clinical effectiveness and harms associated with the treatment, and determining the relative importance of these different types of outcomes. In some ways, determining the willingness to accept treatment-related risks in exchange for treatment benefits is the greater challenge because it involves the individual subjective judgments of many decision makers, and these decision makers may draw different conclusions about the optimal balance between benefits and risks. In response to increasing demand for benefit–risk evaluations, researchers have applied a variety of existing welfare-theoretic preference methods for quantifying the tradeoffs decision makers are willing to accept among expected clinical benefits and risks. The methods used to elicit benefit–risk preferences have evolved from different theoretical backgrounds. To provide some structure to the literature that accommodates the range of approaches, we begin by describing a welfare-theoretic conceptual framework underlying the measurement of benefit–risk preferences in pharmaceutical and medical treatment decisions. We then review the major benefit–risk preference-elicitation methods in the empirical literature and provide a brief overview of the studies using each of these methods. The benefit–risk preference methods described in this overview fall into two broad categories: direct-elicitation methods and conjoint analysis. Rating scales (6 studies), threshold techniques (9 studies), and standard gamble (2 studies) are examples of direct elicitation methods. Conjoint analysis studies are categorized by the question format used in the study, including ranking (1 study), graded pairs (1 study), and discrete choice (21 studies). The number of studies reviewed here demonstrates that this body of research already is substantial, and it appears that the number of benefit–risk preference studies in the literature will continue to increase. In addition, benefit–risk preference-elicitation methods have been applied to a variety of healthcare decisions and medical interventions, including pharmaceuticals, medical devices, surgical and medical procedures, and diagnostics, as well as resource-allocation decisions such as facility placement. While preference-elicitation approaches may differ across studies, all of the studies described in this review can be used to provide quantitative measures of the tradeoffs patients and other decision makers are willing to make between benefits and risks of medical interventions. Eliciting and quantifying the preferences of decision makers allows for a formal, evidence-based consideration of decision-makers’ values that currently is lacking in regulatory decision making. Future research in this area should focus on two primary issues—developing best-practice standards for preference-elicitation studies and developing methods for combining stated preferences and clinical data in a manner that is both understandable and useful to regulatory agencies.