Cost Effectiveness Analysis: Introduction | CDC Econ Eval Tutorials (E)

Cost Effectiveness Analysis

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Introduction

Cost Effectiveness Analysis (CEA) is a type of economic evaluation that examines both the costs and health outcomes of alternative intervention strategies.

CEA compares the cost of an intervention to its effectiveness as measured in natural health outcomes (e.g., "cases prevented" or "years of life saved").

CEA results are presented in a cost-effectiveness ratio, which expresses cost per health outcome (e.g., cost per case prevented and cost per life year gained).
CEA is generally used to either:
- compare alternative programs with a common health outcome, or
- assess the consequences of expanding an existing program.

CEA was created in the 1970s as a tool for healthcare decision making, primarily to avoid controversy regarding valuation of health-related outcomes in dollars.

CEA was initially applied in the clinical arena but has recently been used to evaluate health policies, programs, and interventions.

Why Is CEA Important?

Decisionmakers are often faced with the challenges of resource allocation.

Resources are scarce; therefore, they must be allocated judiciously. CEA is used to identify the most cost-effective strategies from a set of options that have similar results.

For example, the federal government might have to allocate scarce resources to:

provide a new facility to assist in the development and procurement of vaccines, or
enhance the current public health vaccine delivery.

These options have a common health outcome: the number of cases of a disease prevented by the vaccine. CEA can be used to identify the option that prevents the most cases at the least cost.

CEA differs from cost benefit analysis (CBA) and cost utility analysis (CUA) in that:

CEA expresses outcomes in natural units (e.g., "cases prevented" or "number of lives saved"), whereas
CBA assigns dollar values to the outcomes attributable to the program, and
CUA is a specialized form of CEA that includes a quality-of-life component associated with morbidity using common health indices such as quality-adjusted life years (QALYs) and disability-adjusted life years (DALYs).

Advantages of CEA over CBA and CUA

Compared with CBA and CUA, CEA is:

less time- and resource-intensive,
easier to understand, and
more readily suited to decision making.

Because CEA uses a particular outcome measure that must be common among the programs being considered, its value is limited when the programs have different outcomes.

To overcome this limitation, CEA uses more general summary measures (e.g., "number of lives saved").

For example, compare a smoking prevention program targeted at adolescents with a smoking cessation program targeted at committed smokers.

The prevention campaign results might be presented as "cost per student smoker averted" whereas the smoking cessation program might be measured by "cost per quitter."

To compare programs and better allocate resources, you could present results of both programs using a common outcome measure (e.g., "cost per life-year gained").

A CEA Example

This table lists factors that should be considered by a decisionmaker when choosing between alternative programs: expanding access for a breast cancer screening program to women with risk factors aged 40–69 years rather than 50–69 years.

National Breast and Cervical Cancer Early
Detection Program (NBCCEDP)

Factor	Value
Decisionmaker	NBCCCEDP
Resources	Congressional appropriations
Alternatives	Women aged 40–69 versus 50–69 years
Group affected	Low income women
Cost of including women aged 40–49 years	Resources that could be used to: screen more women for cervical cancer, increase the percentage of eligible women aged 50–69 years receiving breast cancer screening, and expand the program to cover treatment costs.
Benefits of including women aged 40–49 years	increase in early detection rates, and possible decreased mortality attributable to breast cancer that is left untreated for too long.

CEA could be used by the decisionmaker to provide empirical results that account for the costs and consequences associated with alternative programs.

The decisionmaker's role is to arrive at the choice that will maximize the health benefits to the population.

A host of factors goes into the decision-making process (e.g., timing and political consequences).

Beside these, individual or group value judgments also play a part in arriving at the final decision.

For instance, it might NOT be cost effective for a managed-care provider to cover mammographies for all beneficiaries aged 50–69 years, compared with covering just those who are at high risk (e.g., having a family history of breast cancer, white race, or late age at menopause).

Nevertheless, political and social pressures might force the provider to adhere to the recommendation of the NBCCEDP and cover all female beneficiaries aged 50–69 years.

When Can We Use CEA?

CEA is used most appropriately in situations having:

Interventions with Shared Goals

CEA is useful when the primary objective of the study is to identify the most cost-effective strategy from a group of alternatives that can effectively meet a common goal and are often competing for the same resources.

For example, to increase smoking cessation among adult smokers, a policy maker could compare a self-help treatment plan with a group-based intervention.

A Specific Population

CEA results might not be generalizable to all populations. Because each population has specific characteristics (e.g., prevalence of disease, or access to care), each might have different program costs, productivity losses, and medical expenses.

Inequalities in risk factors and exposure levels can also result in different outcomes.

For example, a mass media campaign might be the best intervention to increase smoking cessation among adolescents, whereas a prenatal health education program might be a better intervention to increase smoking cessation among pregnant women.

Sound Evidence

CEA can provide solid justification for a program. Empirical evidence might be needed to provide backing for the increased level of program funding or a switch from one to the other.

For example, a CEA will take into account the savings a managed-care organization will ultimately accrue by supporting prenatal smoking cessation education programs.

If the program is cost effective in raising the birth weights of infants, it will most likely encourage program managers to provide more financial support.

Possibly Inefficient Programs

CEA can be used when a need exists to identify and isolate programs that are wasting resources.

For example, follow-up calls conducted 6 months after a group-based smoking cessation program began might reveal that very few participants have indeed quit smoking.

If so, the decisionmaker might cut the group program entirely from the list of possible treatment regimens or form a team to research better methods of group program treatment.