A short primer on cost-effectiveness analysis

INTRODUCTION — Health care advances such as new drugs, devices, or screening and diagnostic tests must demonstrate safety and efficacy to be approved for clinical use. However, because of rising health care costs and limited budgets, questions may remain about their value. Cost-effectiveness analysis is one approach to determining value and refers to a method for assessing the costs and health benefits of an intervention. Assuming that health budgets cannot meet all of the possible demand, cost-effectiveness evaluation can assist decision-makers in allocating resources to maximize the net public health benefit when choosing among options in the care of patients.

Cost-effectiveness analysis has become a fundamental method in medicine and healthcare policy. However, it can be misunderstood because of its methodologic complexity [1]. The term "cost-effective" itself is frequently misused as an adjective (eg, an intervention is "cost-effective") without providing a point of reference.

This topic will review the basic principles of cost-effectiveness analysis while highlighting some of the controversies. Detailed discussions on this topic have been presented in a series of consensus statements issued by the Panel on Cost-Effectiveness in Health and Medicine through the United States Public Health Service [2-4].

DEFINITIONS — Four types of economic analysis have been applied to health care [5].

●Cost-effectiveness analysis and cost-utility analysis (a type of cost-effectiveness analysis) are most commonly used for performing economic analyses in health care. In these analyses, monetary and health outcomes are measured separately, and the relative value of an intervention is measured as the additional cost to achieve an incremental health benefit such as dollars to prevent a case of cancer. In cost-utility analysis, the effectiveness metric becomes life expectancy adjusted for the morbidity or quality of life associated with the alternative strategies.

Four outcomes are possible when making comparisons using cost-effectiveness analysis (eg, treatment A versus treatment B):

•Treatment A is more effective than treatment B and is less costly

•Treatment A is no more effective than treatment B but is less costly

•Treatment A more effective than treatment B but is more costly

•Treatment A is no more effective than treatment B and is more costly

If treatment A costs less and leads to better health outcomes, it is cost saving and is preferred over treatment B. The situation is more complex if treatment A is more effective but at higher cost. In this scenario, cost-effectiveness analysis can determine the additional cost relative to the incremental benefit gained [6]. Cost-effectiveness does not imply that an intervention is cost saving. Similarly, an intervention cannot be considered cost-effective merely because it is more effective.

●Cost-identification or cost-minimization analysis simply examines costs of care, implicitly assuming equal health benefits for all alternative options.

●Cost-benefit analysis incorporates both costs and health outcomes, placing a monetary value on health outcomes so that the alternatives can be evaluated in terms of a single (monetary) outcome measure. However, because assigning a monetary value to a health outcome (or life) raises ethical objections, cost-benefit analysis has generally not been accepted in health care.

PERSPECTIVE — The point of view of the analysis determines which costs and health effects it considers. As an example, patients, clinicians, health payers, and society may view antibiotic costs differently: Patients may consider only out-of-pocket or copayment costs, health payers may consider the antibiotic cost and hence whether it is generic or non-generic, and society may also consider the costs of emerging drug resistance from antibiotic overuse. Clinicians may consider the health benefit for an individual patient but weigh it against the public health implications of antibiotic overuse.

For health policy decisions, cost-effectiveness analyses ideally apply a societal perspective and hence include costs, benefits, and harms that may extend beyond the individual patient, clinician, and payer directly involved in the decision [7]. The societal perspective represents the overall public interest by including social opportunity costs where the use of limited resources (such as personnel, hospital beds, donor organs, or budgets) results in the loss of opportunity to use those funds (or resources) for other purposes. The societal perspective allows cost-effectiveness results to be compared directly with other interventions from a public health vantage point when using reference case methods, as described below [8]. (See 'Reference case methods' below.)

COSTS — Costs refer to the total expenditures related to an intervention, including the costs of treatment, adverse treatment effects, and future possible savings from the prevention of disease or morbidity [9]. Costs are distinct from charges (which include a profit margin). They can be categorized as [2,7]:

●Direct medical care (eg, clinician time, test, or drug)

●Direct nonmedical care (eg, food, transportation, lodging, clothing, home health aides, or care by family members due to illness)

●Time or indirect morbidity and mortality (eg, reduced work productivity or loss of life) and intangible (eg, pain and suffering)

Fixed costs are those unrelated to short-term changes in volume (eg, cost of an endoscopy suit), while variable costs are those directly related to changes in volume (eg, cost of medications used in sedation).

Estimation of costs can be done from a top-down or a bottom-up approach and can be retrospective or prospective. In a top-down analysis, an appropriate clinical cohort is identified and their aggregated economic or resource costs are obtained from patient-specific medical billing data, usually as charges (eg, hospital or clinician bills), which are then adjusted with cost-to-charge ratios. A bottom-up approach obtains estimates in a two-step process. First, the frequency of utilization of individual resources is obtained (eg, drugs, tests, procedures, and hospital days). Subsequently, the frequencies are multiplied by each unit's cost and then summed to yield a total cost. A complete assessment of costs may also involve "micro-costing," in which additional costs such as the contribution of nursing care, supplies, or ancillary services to specific costs (such as a hospital day) are detailed. Not surprisingly, the method used to determine costs can result in substantially different estimates.

Practice patterns and costs may vary considerably across different providers or regions. This difficulty can, in part, be addressed by estimating average costs and examining uncertainty by performing sensitivity analysis. (See 'Sensitivity analysis' below.)

EFFECTIVENESS — Effectiveness is typically measured in units that are relevant to the condition under study and are meaningful for the decision-maker. Examples include cancers prevented, lives saved, or life years gained. A standard outcome scale helps policymakers compare the net health benefits of alternative funding decisions. Thus, cost-utility analysis frequently uses quality-adjusted life years (QALYs) gained to reflect not only prolongation of life but also the quality of life (QOL) associated with those years (eg, surviving without prostate cancer but with erectile dysfunction from its treatment).

Unlike functional measures of QOL (eg, SF36 or EQ5D), determining QOL for the purposes of cost utility analysis involves utility assessment, which quantifies preferences for health outcomes. Although methods to determine health effects and to incorporate QOL have not been standardized, the following approaches have most commonly been used to address these issues:

●The "time trade-off" and "standard gamble" methods [10]:

With the time trade-off method, individuals choose between living a shortened amount of time with perfect health and living longer with impaired health. The length of time is varied until the individual is close to indifferent between the alternatives. If someone were indifferent to "living six months of life in perfect health versus living for one year with hepatocellular carcinoma," then living a year with hepatocellular carcinoma has the same value as living six quality-adjusted life months.

With the standard gamble method, individuals choose between a guaranteed intermediate health outcome and the possibility of having either the worst outcome (most often death) or the best outcome. The likelihood of dying is varied until individuals are indifferent between these two options.

●Scales that tabulate premeasured preferences for health states or outcomes are defined in various dimensions (such as the Health Utilities Index, Quality of Well-Being Scale, or EuroQol) [11,12].

Besides variation in the methods to assess "utilities" or "preferences," the study population used to determine QOL affects the estimate. Different estimates may be reached depending upon whether the study population consists of clinicians, patients with the disease, or individuals from the general population who have not experienced the disease. In most cases, individuals experiencing a disease assign higher (better) QOL values than those who have not experienced the disease [13,14].

REFERENCE CASE METHODS — A cost-effectiveness analysis should ideally incorporate reference case analysis that uses a standard set of methods with specified assumptions for the measurement and reporting of costs and health effects. The reference case methodologies specify the following considerations [2]:

●Components belonging in the numerator and denominator of a cost-effectiveness ratio

●Methods for estimating and valuing the components in the numerator of a cost-effectiveness ratio (the costs)

●Methods for identifying, quantifying, and valuing the components in the denominator of a cost-effectiveness ratio (the health consequences)

●For outcomes that occur at different time points, methods for making them comparable (ie, discounting) (see 'Time horizon and discount rate' below)

●Methods for handling uncertainty in cost-effectiveness analysis (ie, probabilistic sensitivity analysis) (see 'Sensitivity analysis' below)

The reference case facilitates comparisons across cost-effectiveness analyses, thereby permitting health policymakers to choose the most efficient use of public health resources in their funding decisions.

Although use of standardized reference case methods, including probabilistic sensitivity analysis, has increased since the early 2000s, their use is not universal [15]. Unfortunately, many cost-effectiveness analyses continue to be published that do not contain a reference case.

TIME HORIZON AND DISCOUNT RATE — The time horizon of an analysis reflects the length of time over which health benefits and costs should be considered and included in the analysis. Because of annual budgets and competing market forces, health payers usually consider short-term, one-year time horizons, but the societal perspective recommended in the reference case applies a long-term or lifetime time horizon. In such cases, time preferences for expenditures become important and are captured using discounting.

Money available or spent now is more valuable than money available or spent in the future because of opportunity costs. As an example, one would prefer to receive money now as opposed to receiving the same amount a year from now because money available now can be put to immediate use. The discount rate quantifies this time preference and places all economic costs in terms of present value. For example, applying a 3 percent annual discount rate, spending $100 now equals spending $97 one year from now and $74 ten years from now. Because costs are discounted, the benefits of health interventions must also be discounted.

Note that the discount rate is not an adjustment for inflation, which is a separate consideration. Even in the absence of inflation, most individuals would prefer to have an equivalent health benefit or money now as opposed to in the future. The discount rate captures this time preference. When data regarding costs are derived from different years, older costs should be inflated to a common year so that there can be a consistent economic basis. If future medical inflation costs rise uniformly, then future purchasing power for health care remains the same and there is no need to adjust for medical inflation.

SENSITIVITY ANALYSIS — As underscored in the previous discussions, considerable uncertainty may remain regarding the parameters used to measure costs and health effects, even in the most carefully conducted cost-effectiveness studies. To help identify the most influential or important parameters and to assess the degree to which uncertainty in the parameter could affect the overall results, cost-effectiveness analyses should perform multiple evaluations in which one or more of the parameters are varied across reasonable ranges. The ranges reflect intrinsic variability or regional variation. As an example, the cost of colonoscopy may be cheaper in some institutions or health care delivery settings compared with others; thus, to determine the cost-effectiveness of screening colonoscopy, the cost of a colonoscopy is varied over a range to determine the maximum cost at which it remains cost-effective. This process (termed "sensitivity analysis") allows for a reasonable appraisal about the parameters that are most important in the analysis and the stability of the reference case results.

Cost-effectiveness analyses that include a decision analysis routinely perform sensitivity analysis. Decision analysis involves the mathematical modeling of health outcomes, utilities (preference-based estimates of the quality of life with various health states), and costs. The degree to which sensitivity analysis is performed (and thereby the rigor with which assumptions are tested) varies across decision analyses. Additional details regarding decision analysis are provided separately. (See "Decision analysis".)

Deterministic sensitivity analyses assess the impact of varying single or multiple parameters related to cost-effectiveness; however, this method can only assess variation in a few parameters (one to three) at a time. Monte Carlo simulation can assess the impact of varying all parameters simultaneously. These sophisticated analyses use probability distributions to yield a cost-effectiveness acceptability curve that describes how likely it is that the cost-effectiveness ratio will be more favorable than the value benchmark (or "threshold") corresponding to a societal "willingness to pay" for health benefits. (See 'Interpretation' below.)

By describing the range and relative likelihood of cost-effectiveness ratio projections consistent with the model's plausible assumptions, uncertainty analysis conveys whether the model's projections are relatively precise or if they are so uncertain that it might make sense to gather more information before making health policy decisions.

COST-EFFECTIVENESS RATIO

Average versus incremental cost-effectiveness ratio — The average cost-effectiveness ratio divides each intervention's costs by its effectiveness. This can result in misleading conclusions about an intervention's cost-effectiveness [16].

A preferable way to express cost-effectiveness is the incremental cost-effectiveness ratio, which refers to the additional cost and the additional benefit of one intervention compared with another. The units are typically in dollars (or other units of currency) per unit of effectiveness gained. The incremental cost-effectiveness ratio helps decision-makers determine whether a new intervention should be used. Lower ratios imply better cost-effectiveness.

As an example, consider the cost effectiveness of two strategies for annual colon cancer screening, one using three annual stool guaiac tests and the other using four annual stool guaiac tests [17]. Performing three annual tests represents the standard of care against which performing four tests is being compared. When applied to 10,000 people, performing three annual tests has a net cost of $130,999 and detects 71.9003 cases of colon cancer, whereas four annual tests has a cost of $148,116 and detects 71.9385 cases. The cost-effectiveness can be expressed as the average cost-effectiveness ratio or the incremental cost-effectiveness ratio:

●Average cost-effectiveness ratio – The average cost-effectiveness ratio of performing three annual tests $1,822 per cancer detected and the average cost-effectiveness ratio of performing four annual tests is $2,059 per cancer detected; either appears to be reasonable.

●Incremental cost-effectiveness ratio – The incremental cost-effectiveness ratio conveys how much additional benefit and at what additional cost does performing four instead of three guaiac tests provide. The incremental cost of four versus three tests ($17,917) is divided by the incremental benefit of four versus three tests (0.0382 additional cancers detected), yielding an incremental cost-effectiveness ratio of $469,534 per additional cancer detected.

The absolute costs of different interventions and the context of decision-making also need to be incorporated into decision-making because the consistent selection of strategies based only upon relative costs may lead to a minimalist approach to providing services. Consider, for example, a disease that is invariably fatal within one week if left untreated [1]. Two treatment options are available. The first option costs $100 and produces a life expectancy of one year. The second option costs 10 times as much ($1000) but yields a life expectancy of five years. A practice based only upon cost-minimization would select the first option, yet the incremental cost-effectiveness of the second option is only $225 per year of life gained ([$1000 - $100] ÷ [5 – 1]). Although the first option has the lowest cost, it would be unacceptable when considering the severity of the illness, degree of benefit, and relatively low absolute cost of the second option.

Standard measure of cost-effectiveness — The standard measure of cost-effectiveness used in most cost-utility analyses is the cost to increase life expectancy by one quality-adjusted life year (QALY; adjusted to one year of perfect health and discounted to its present value). The rationale for using this measure is that it facilitates comparison of value across analyses of interventions addressing different health conditions. Without a common measure, there would be no straight-forward way to compare cost-effectiveness ratios from different studies. As an example, having to decide between an intervention to detect colon cancer and another to prevent a myocardial infarction would leave a policy analyst in a quandary as to which health outcome was more valuable.

Despite the efforts to standardize analyses using the reference case, direct comparison of different cost-effectiveness studies may not be straightforward, because studies were performed at different times using different methodologies, assumptions, and measures of effectiveness. Often, different studies ask slightly different questions (eg, What is the most efficient treatment strategy? Should a drug be reimbursed? What is a value-based price for an innovative treatment based on its benefit relative to the current standard of care?). Furthermore, treatment options may differ depending on the context for the decision (eg, for those without the disease, the focus might be on prevention/vaccination, whereas for those with the disease, the focus is on treatment).

Alternative measures — Because of the challenges in measuring QALYs and ethical concerns that QALY-based cost-effectiveness analyses may be prone to biases against disabled populations, there is growing interest in using alternative measures. These include:

●Disability-adjusted life years (DALY), a measure that is used by the World Health Organization.

●Equal value of life years gained (evLYG), developed by the Institute for Clinical and Economic Review (ICER) [18]. This measure omits the impact of quality of life in attempt to alleviate bias against disabled populations [19].

●Generalized risk-adjusted QALY (GRA-QALY) incorporates risk aversion so that value benchmarks rise with illness severity [20].

Interpretation — Having determined the incremental cost-effectiveness ratio, how should those ratios be interpreted? The examples presented above bring into focus two general methods for evaluating cost-effectiveness ratios.

●The first method is based upon the notion of "willingness to pay." A decision-maker (such as a governmental health policymaker) may decide that it is only willing to pay a certain amount per unit of gain (such as QALYs) across all of the services that it covers. Thus, the selection among options with different cost-effectiveness ratios would be based upon staying below a value benchmark such as $50,000, $100,000, and $150,000 per QALY gained, sometimes referred to as "thresholds" in the literature.

●The second method involves comparing the cost-effectiveness ratio of an intervention with other well-accepted medical practices by examining a league table. A league table is a compilation of cost-effectiveness ratios for various treatments and diseases complying with the reference case (table 1). As a general rule, interventions that yield a cost-effectiveness ratio of less than $50,000 to $150,000 per QALY gained have been considered to be acceptable in the United States and several other countries. This cutoff is also consistent with prior World Health Organization recommendations, which suggested that interventions with cost-effectiveness ratios less than three times the gross domestic product (GDP) per capita are "cost-effective" and those less than the GDP per capita (approximately $75,000 for the United States in 2022) are "very cost-effective." The historical standard used for setting this threshold has been hemodialysis for chronic kidney failure, which has an incremental cost-effectiveness ratio of $60,000 to $128,000 per QALY gained.

However, because of moral imperatives related to social justice (including that patients with rare or life-threatening diseases should still have access to effective therapies despite their expense), some medical interventions with high incremental cost-effectiveness ratios are still widely performed (eg, cardiac transplantation or some cancer treatments). On the other hand, these interventions with higher incremental cost-effectiveness ratios can drive health care costs up, potentially depriving others of access to basic health care or driving up taxes or insurance premiums.

EVALUATING A COST-EFFECTIVENESS STUDY — The discussion presented above emphasizes that cost-effectiveness analysis is complex and that studies making claims regarding cost-effectiveness should receive the same level of scrutiny as other types of studies. The following questions can provide guidance when evaluating a cost-effectiveness analysis, although many additional features reflecting the conduct of the study and its quality can be considered in specific settings [21-29].

●Did the study compare well-defined strategies that are consistent with medical practice?

●Were the included patients representative of the types of patients that the analysis is intended to apply to?

●Were costs defined reasonably?

●Were all the relevant costs considered?

●Did the estimates of cost reflect those in the community in which the results are intended to apply?

●Were ranges of costs considered for key services?

●Was effectiveness expressed in relevant units such as quality-adjusted life years (QALYs) gained? Was it reasonable to ignore quality of life if it was not considered?

●Was the time frame examined long enough for the expected benefits to have been observed?

●Were all the relevant outcomes considered?

●Was sensitivity analysis performed?

●Was the perspective defined clearly?

●Was a reference case presented?

●Were the findings discussed in context of other options available to treat the particular condition?

SUMMARY

●What is cost-effectiveness analysis? – Cost-effectiveness analysis is a widely accepted method to evaluate the value or efficiency of new technologies and drugs. In these analyses, monetary and health outcomes are measured separately, and the relative value of an intervention is measured as the additional cost to achieve an incremental health benefit (eg, incremental cost per quality-adjusted life year [QALY] gained). (See 'Definitions' above.)

●Components of cost-effectiveness analysis – A cost-effectiveness analysis should ideally incorporate reference case analysis that uses a standard set of methods with specified assumptions for the measurement and reporting of costs and health effects. (See 'Reference case methods' above.)

•Costs – Costs refer to the total net expenditures related to an intervention, including the costs of treatment, adverse treatment effects, and future possible savings from the prevention of disease or morbidity. They can be categorized as (see 'Costs' above):

-Direct medical care (eg, clinician time, test, or drug)

-Direct nonmedical care (eg, food, transportation, lodging, clothing, home aides, or care by family members due to illness)

-Indirect morbidity and mortality (eg, lost productivity) and intangible (eg, pain and suffering)

•Effectiveness – Effectiveness is typically measured in units that are relevant to the condition under study and are meaningful for the decision-maker. In most cost-utility analyses, the standard measure of effectiveness is QALYs gained, which reflects not only prolongation of life but also the quality of life associated with those years. This standard outcome allows policymakers to compare the value across analyses of interventions addressing different health conditions. (See 'Effectiveness' above and 'Standard measure of cost-effectiveness' above.)

Because of the challenges in measuring QALYs and ethical concerns that QALY-based cost-effectiveness analyses may be prone to biases against disabled populations, there is growing interest in using alternative measures (eg, disability-adjusted life years [DALY], equal value of life years gained [evLYG], and generalized risk-adjusted QALY [GRA-QALY]). (See 'Alternative measures' above.)

•Incremental cost-effectiveness ratio – The incremental cost-effectiveness ratio refers to the additional cost and the additional benefit of one intervention compared with another. The units are typically in dollars (or other units of currency) per unit of effectiveness gained. The incremental cost-effectiveness ratio helps decision-makers determine whether a new intervention should be used. Lower ratios imply better cost-effectiveness. (See 'Cost-effectiveness ratio' above.)

•Sensitivity analysis – To help identify the most influential or important parameters and to assess the degree to which uncertainty in the parameter could affect the overall results, cost-effectiveness analyses usually perform multiple evaluations in which one or more of the parameters are varied across reasonable ranges. (See 'Sensitivity analysis' above.)

●Interpretation – Interventions that yield a cost-effectiveness ratio of less than $50,000 to $150,000 per QALY gained have been considered to be acceptable in the United States and several other countries. The historical standard used for setting this threshold has been hemodialysis for chronic kidney failure, which has an incremental cost-effectiveness ratio of $60,000 to $128,000 per QALY gained. (See 'Interpretation' above.)