Interpreting the results of cost-effectiveness studies

Abstract

In developed nations, health care spending is an increasingly important economic and political issue. The discipline of cost-effectiveness (CE) analysis has developed over several decades as a tool for objectively assessing the value of new medical strategies, by simultaneously examining incremental health benefits in light of incremental costs. The underlying goal of CE research is to allow clinicians and policymakers to make more rational decisions regarding clinical care and resource allocation. This review will provide the reader with an understanding of the theoretical underpinnings of CE analysis, the types of analyses commonly performed and reported in the medical literature, some important strengths and weaknesses of different analytical approaches, and key principles in the interpretation of CE results. Key principles reviewed include the impact of analytic perspective, the importance of proper incremental comparisons, the effect of time horizon, and methods for exploring and describing uncertainty. Illustrative examples from the cardiology literature are discussed.

Figure 1. The CE Plane

With some reference strategy occupying the origin of the graph, a cost-effectiveness (CE) study can plot the incremental costs (y-axis) and benefits (x-axis) of alternative strategies, relative to this reference, in 2-dimensional space. The area above the horizontal is cost-increasing, and to the right of the vertical, clinically beneficial. When a new strategy adds both benefits and costs (upper right-hand quadrant) or reduces both (lower left-hand quadrant), a CE ratio must be calculated to judge benefits relative to costs.

Figure 2. Quality-Adjusted Life Expectancy

To calculate quality-adjusted life expectancy, the time spent in a particular health state (typically measured in years) is multiplied by the utility weight (possible range of 0 to 1) for that health state, and these products are then summed over time. Quality-adjusted life expectancy is thus represented by the area under the hypothetical “curve” in this figure.

Figure 3. Absolute Versus Incremental CE

The incremental costs (y-axis) and effectiveness (x-axis, in quality-adjusted life years [QALYs]) for the 2 experimental arms of the COMPANION (Comparison of Medical Therapy, Pacing, and Defibrillation in Heart Failure) trial are plotted versus the control group of optimal medical therapy (27). In A, the reported separate cost-effectiveness (CE) ratios for cardiac resychronization therapy pacemakers (CRT-Ps) and cardiac resynchronization therapy defibrillators (CRT-Ds) versus the control group both appear to be attractive from a U.S. perspective. The CE theory, however, dictates that each alternative is compared to the next best. When this is done, as shown in B (28), the incremental CE ratio for CRT-D versus CRT-P appears much larger.

Figure 4. Results of Bootstrap Resampling in a Trial-Based CE Study

The joint distribution of projected lifetime differences in costs (y-axis) and life-expectancy (x-axis) based on the CURE (Clopidogrel in Unstable angina to prevent Recurrent Events) trial population were recalculated over 5,000 replications of the study data using the bootstrap resampling method and plotted on the cost-effectiveness (CE) plane. Each point in the scatterplot represents 1 bootstrap iteration. Data used, with permission, from Weintraub et al. (29).

Figure 5. CE Acceptability Curve

In this example, the likelihood that use of an embolic protection device during percutaneous coronary intervention of a vein graft (vs. no distal protection) is cost-effective is shown graphically across a range of theoretical cost-effectiveness (CE) thresholds. For each CE threshold (increasing from left to right) on the x-axis, the proportion of bootstrap iterations having a CE ratio at or below that threshold is plotted on the y-axis. As indicated by the arrow, 97.3% of the bootstrapped CE ratios were <$40,000 per year of life gained. Reprinted, with permission, from Cohen et al. (39).