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A1. What is cost-effectiveness analysis?

Cost-effectiveness analysis is a tool used to aid decisions about which medical care should be offered. It is a method of comparing the cost and effectiveness of two or more alternatives. Such comparisons are useful when one of the alternatives being considered is standard care, as this allows the decision maker to consider whether an innovation is better than the status quo.

The goal of cost-effectiveness analysis to determine if the value of an intervention justifies its cost. Cost-effectiveness involves more than determining cost, it also involves assignment of a value to the outcome.

To facilitate the comparison of different interventions, a standard method of cost-effectiveness analysis was developed by a task force of experts organized by the U.S. Public Health Service (PHS) (Gold, Siegel, Russell, & Weinstein, 1996).

The PHS Task Force made the following recommendations:

  • Costs should be estimated from society's perspective. The effects of an intervention on all costs should be considered, not only the direct cost of the intervention, but its effect on healthcare expenditures, and costs incurred by patients.
  • Costs and benefits should be discounted at a 3% annual rate, to reflect the lower economic value of an expense that is delayed and the higher value of a benefit that is realized sooner.
  • When the effect of the intervention on costs and benefits is not fully realized during the study period, modeling should be used to estimate the costs and benefits over the patient's lifetime.
  • The task force also described methods of estimating the statistical significance of cost-effectiveness findings. Note that when cost-effectiveness is a primary study hypothesis, variance in costs and outcomes, and their covariance will affect the sample size.

Cost-effectiveness analysis is not uniformly applied in the healthcare system. Decision makers often adopt new treatments without knowing if they are cost-effective. Even when cost-effectiveness has been studied, decision makers may not be able to interpret the data, or they may not agree with the results. Despite this limitation, cost-effectiveness is increasingly used to inform healthcare decision makers.

Cost-Effectiveness Studies of Two Interventions

When the choice is between an innovation and standard care, the analyst first applies the principle of strong dominance. Either the innovation or standard care may be preferred using this principal. Strong dominance favors a strategy that is both more effective and less costly. Strong dominance occurs only when the innovation is very good (it works better and saves cost) or very bad (its works worse and costs more).

When the more effective innovation is more costly, strong dominance provides no guidance. The decision maker must decide if the greater effectiveness justifies the cost of achieving it.

It is for this reason that the PHS Task Force recommended that cost-effectiveness studies use the Quality-Adjusted Life Year (QALY) as the outcome measure The QALY reflects both the quantity and the quality of life (Torrance & Feeny, 1989) . It is the most widespread method of measuring the value of providing a healthcare intervention.

Quality of life adjustments are based on patient or societal ratings of the quality of life associated with different health states. The ratings, also known as "preferences" or "utilities," are on a scale of zero (representing death) to one (representing perfect health). There are several methods for obtaining these ratings. The Time-Trade-Off method asks the individual doing the rating how much healthy life they are willing to give up to be cured of the condition. The Standard Gamble method asks them how much of a risk of death they are willing to incur in order to be cured of the condition. The Health Utilities Index (HUI) and EuroQoL are instruments used to gather information on quality of life. Methods for assessing economic quality of life are found in the HERC guidebook, Preference Measurement in Economic Analysis.

When the more effective innovation is also the more costly, the decision maker must decide if the greater effectiveness justifies the cost of achieving it. This is done by calculating an incremental cost-effectiveness ratio. This is difference in costs divided by the difference in outcomes. The ratio is the most useful when outcomes are expressed in Quality Adjusted Life Years (QALYs).

The cost-effectiveness ratio represents a measure of how efficiently the proposed intervention can produce an additional QALY. By using this standard method, the cost-effectiveness of alternative innovations may be compared, helping healthcare payers decide what changes they should adopt. The goal of the decision maker is to adopt all interventions that represent efficient ways of producing QALYs, and to disapprove of interventions with ratios that are too high.

The PHS Task Force did not recommend a standard of what constitutes a cost-effective intervention, that is, how low the cost-effectiveness ratio must be for an intervention to be adopted. When outcomes are measured in QALY's, the ratio may be compared to the ratios of other innovations (if standard methods have been employed). Knowledge of the incremental cost-effectiveness of interventions that have been approved can be helpful. It has been observed that the U.S. healthcare system adopts treatments that cost less than $50,000 per quality-adjusted life year (Owens, 1998). The criteria for judging cost-effectiveness are different in different healthcare systems and in different countries.

Comparison of Multiple Interventions

In some studies that compare multiple mutually exclusive interventions, an additional dominance principle is applied (Kamlet, 1992). As in the case when comparing two interventions, the analyst first applies the principle of strong dominance. Any of the competing interventions is ruled out if these is another intervention that is both more effective and less costly.

The analyst may then apply the principle of extended dominance (sometimes called "weak dominance"). The list of interventions, trimmed of strongly dominated alternatives, is ordered by effectiveness. Each intervention is compared to the next most effective alternative by calculating the incremental cost-effectiveness ratio. Extended dominance rules out any intervention that has an incremental cost-effectiveness ratio that is greater than that of a more effective intervention. The decision maker prefers the more effective intervention with a lower incremental cost-effectiveness ratio. By approving the more effective interventions, QALY's can be purchased more efficiently. This is made clear by the following example.

Example of Method for Multiple Interventions

Here is a hypothetical example of a comparison of multiple mutually exclusive interventions. The table gives cost in dollars and outcomes in QALY's for standard care and 5 innovations. In the first table, we can rule out intervention A. It is strongly dominated by intervention B, which costs less and yields better outcomes.

Intervention Cost Effectiveness
E $55,000 5
D $35,000 4
C $25,000 3
B $10,000 2
A $12,000 1.5
Standard Care $5,000 1

Next we apply the principle of extended-dominance. Interventions are listed in the order of effectiveness. The incremental cost-effectiveness ratio of each intervention is found by comparing it to the next most effective intervention.

Intervention Cost Effectiveness Incremental Cost-Effectiveness Ratio
E $55,000 5 20,000
D $35,000 4 10,000
C $25,000 3 15,000
B $10,000 2 5,000
Standard Care $10,000 1 _

We can use extended dominance to rule out intervention C. It has an incremental cost-effectiveness ratio of $15,000 per QALY. In order to adopt C, the decision maker must have decided to adopt interventions with a cost-effectiveness ratio of $15,000 per QALY. If this is the case, then the decision maker would prefer intervention D. A greater number of QALY's may be obtained at a lower cost per QALY.

The final table indicates the interventions and their cost-effectiveness ratios after the dominance principles have been applied. It is now up to the decision maker to choose among the interventions by deciding how much a QALY is worth. If a QALY is not worth even $5,000 to the decision maker, then none of the innovations generate sufficient value to be adopted; if a QALY is worth more than $20,000 to the decision maker, then intervention E would be adopted.

Intervention Cost Effectiveness Incremental Cost-Effectiveness
E $55,000 5 20,000
D $35,000 4 12,500
B $10,000 2 5,000
Standard Care $5,000 1 _

Dominance principles can be also applied by ranking interventions in the order of their cost. The same finding will result. Dominance principles can be applied when outcomes are measured in units other than QALY's. This requires the assumption that measures reflect the most important effect of the treatment on health. For example, if a drug prevents death, and the side effects are known to be minor, outcomes could be measures in terms of life years of survival.

QALY's are the preferred measure of the outcomes, because they have the potential to allow the analysis to trade off mortality with quality of life, including treatment benefits and the side effects.


Kamlet MS. A framework for cost-utility analysis of government healthcare programs: Office of Disease Prevention and Health Promotion, Public Health Service, U.S. Department of Health and Human Services; 1992.

Gold MR, Siegel JE, Russell LB, Weinstein MC. Cost-effectiveness in health and medicine. New York: Oxford University Press; 1996. see p. 285 et. seq.

Owens, D. K. (1998). Interpretation of cost-effectiveness analyses [Editorial]. J Gen Intern Med, 13, 716-717.

Torrance, G. W., & Feeny, D. (1989). Utilities and quality-adjusted life years. Int J Technol Assess healthcare, 5(4), 559-75.

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Guidebook, Health Economics Resource Center (March 2007) | Download »
  • This guide includes an overview of the concepts of preference measurement and quality-adjusted life years, a description of the most common techniques used for measuring preferences in economic evaluation, a summary of experience measuring preferences in the VA Cooperative Studies Program (CSP) (Spitzer, Dobson et al. 1981) clinical trials, and recommended criteria by which to select both the methods and measures to use in cost-effectiveness analysis (CEA). In Appendix 1 we have included sample questions from each of the multi-attribute health status classification systems included in the discussion of indirect methods. In Appendices 2 and 3, we have included links and references to various resources highlighted in the document