Measures of cost-effectiveness are used to compare the merits of diverse medical interventions. A novel drug for metastatic melanoma, for instance, can be compared with statin therapy for primary prevention of cardiovascular events, which in turn can be compared against a surgical procedure for pain, as all are described by a single number: dollars per life-year (or quality-adjusted life-year) gained. Presumably, this number tells practitioners and payers which interventions provide the most benefit for every dollar spent. However, too often, studies of cost-effectiveness differ from one another. They can be based on data from different types of studies, such as randomized controlled trials, surveys of large payer databases, or single-center chart reviews. The comparison treatments may differ. And the treatments may be of unproven efficacy. In these cases, although the results are all expressed in dollars per life-year, we are comparing apples and oranges. In the following discussion, I use three key contemporary examples to demonstrate problems central to cost-effectiveness analysis. Together, these examples show that cost-effectiveness, arguably our best tool for comparing apples and oranges, is a lot like apples and oranges itself. I conclude by proposing some solutions.
Language: en
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