into trouble with the law). It is quite plausible that the health care organization may not perceive the intervention as worthwhile from its narrow perspective, whereas from a social perspective the intervention is highly cost-effective (see Chapter 11 for a discussion of implementation issues). Addressing the disjunction between those who bear the costs of an intervention and those who experience its benefits may require coordinated planning of interventions and, if possible, aligning of incentives across service systems.
Cost-benefit analysis (CBA) and cost-effectiveness analysis (CEA) are two methods of economic analysis used to assess whether an intervention is desirable from an economic perspective; put simply, they evaluate whether the benefits derived from the intervention are worth the cost invested in the intervention. The principal distinction between the two techniques lies in the measurement of desired outcomes. In CBA, all such outcomes are valued in monetary units (dollars), permitting a direct comparison of the benefits produced by the intervention with its costs. When benefits exceed costs, the intervention is said to be cost-beneficial. When benefits fall short of costs—and assuming that one is comfortable that all important positive outcomes have been captured in monetary terms—the conclusion is that the intervention is not worth undertaking. CBA is the ideal form of analysis given that it allows a comparison of desired outcomes (benefits) and undesired outcomes (costs) in the same metric. This permits a precise conclusion about the desirability of the intervention. Is the intervention “worth it”?
CEA, in contrast, is used when one or more major desired outcomes cannot be readily measured in monetary terms but a major outcome, measureable in another metric, is common to the interventions being compared. A notable example in the health care literature pertains to interventions that avoid preventable premature deaths (or preventable illness or disability). Historically, the principal outcome in published studies was measured in terms of life-years saved. Now, most commonly, outcomes are measured as quality-adjusted life years (QALYs). Analysts typically employ CEA when they think that the desired outcome does not lend itself readily to monetization. Thus, breast or prostate cancer screening and treatment avoid premature deaths, but as they do so primarily for people beyond their working years, many analysts are uncomfortable attributing a dollar value to the beneficiaries’ extra years. It is possible to do so, using a measure of willingness-to-pay (Gafni, 1997). Since the desired outcomes and the undesired outcomes (costs) are measured in different metrics in CEA (life years and dollars, respectively), the bottom line of a CEA is a ratio,