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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:
  1. provide a new facility to assist in the development and procurement of vaccines, or
  2. 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.
Test Your Understanding
Please enter your answer to each question before you click on "Our Answer".
  1. CEA is used widely in public health to evaluate alternative programs or policies to gain the maximal health outcome for a given level of resources.
    True   False
    Our Answer
    True.
  2. A CEA measures health outcomes in physical units (e.g., quality-adjusted life years).
    True   False
    Our Answer
    True. Specifically, CUA, a special variant of CEA, examines the quality component of health outcomes.
  3. A CEA would be useful for an organization to determine the return on investment from a health program.
    True   False
    Our Answer
    False. A CBA measures health outcomes in dollars and should be used to determine the return on investment for a particular health program.
  4. For a CEA to be useful in comparing two different programs, common health outcomes must be employed.
    True   False
    Our Answer
    True.
  5. If a CEA for a program expansion proves not to be cost effective, decisionmakers should remove the program from their list of possible investment choices.
    True   False
    Our Answer
    False. Programs with implicit political or social value can be implemented, whether or not they are cost effective.
  6. The results of a CEA evaluating a vaccination program designed to reduce infant mortality in a developing country could be used by a program manager in the United States for evidence of the program's cost effectiveness.
    True   False
    Our Answer
    False. The risk factors and exposures of vaccine-preventable diseases among children in the developing world are different than those experienced by children in developed nations, which would result in dissimilar outcomes that should not be compared.
Framing CEA
General concepts on framing have been presented in the FramingOpen this in a new window tutorial. This tutorial will focus on how framing pertains to CEA.
Defining the Problem
In a CEA, health-related outcomes are relevant in the problem specification section. Since CEA is a comparative analysis, knowing costs and outcomes for both the existing and the proposed or alternative available programs is relevant.
Specific questions that could guide the problem identification section include:
  • Which intervention, a telephone help line or group treatment, is more cost effective for increasing the rate of smoking cessation among middle-aged adults?
  • Which intervention is more cost effective in treating persons who are intermediate or heavy smokers:
    • a transdermal nicotine patch in addition to physician counseling, or
    • counseling alone?
When defining the study problem for a CEA, asking these four questions is often helpful:
  • What is the problem to be analyzed?
  • Why is this problem important?
  • What aspects of the problem need to be explained?
  • What questions need to be answered?
Once the study problem has been identified, a research strategy must be adopted to further direct the framing process. This requires deciding how to structure the CEA.
An Example: Defining the Problem
This example is abstracted from a CEA conducted in 2000 to assess the cost effectiveness of two interventions (i.e., lifestyle and structured) designed to increase physical activity among sedentary adults in Dallas, Texas.
Texas' Project ACTIVE:
Lifestyle versus Structured Interventions
What is the problem to be analyzed? Sedentary lifestyles are prevalent among adults in the United States.
Why is this problem important? An association exists between inactivity and morbidity and mortality, especially with regard to chronic diseases, such as diabetes and cardiovascular disease.
What aspects of the problem need to be explained? In an effort to reduce overall health-care costs and utilization by promoting prevention activities, information on costs and effectiveness was needed to evaluate the program.
What questions need to be answered?
  • What was the cost of the first two years of running the program?
  • Did the program effectively increase physical activity among its participants?
Adopting a Research Strategy
Once the study problem has been identified and defined, a research strategy must be adopted that can direct an evaluator through the remainder of the framing process.
This requires deciding how to structure the CEA.
Following is a list of questions to ensure that all aspects of the research strategy are considered.
What Intervention(s) Will Be Analyzed?
The first task is to define with precision the programs or interventions to be evaluated. For each intervention or program included in the study, identify the following elements:
  • Nature of the intervention — e.g., a screening and vaccination program for varicella zoster virus (VZV) or "chickenpox" infection.
  • Target population — e.g., employees of a health-care institution.
  • Delivery site — e.g., hospital.
  • Personnel delivering the service — e.g., hospital nurses.
  • Technology to be used — e.g., an enzyme-linked fluorescent immunoassay test to determine serologic status.
  • Timing of the intervention — e.g., screening performed at program onset with subsequent vaccination for those patients with no immunity immediately following.
Identifying the elements stated above precisely is important because programs that appear similar might have very different costs and outcomes.
For example, in the example above, program costs would be different if only high-risk workers were screened rather than all hospital personnel.
Who Is the Audience?
The CEA study must address the needs of all persons, clinicians, legislators, and public health officials involved. A well-written problem identification section typically specifies the audience.
Whose Perspective?
Typically, the societal perspective is used in CEA studies dealing with public health issues.
What is the Time Frame?
The study must also specify the time during which the intervention is in effect. In other words, the time frame for a CEA of a varicella vaccination program should span the entire vaccination delivery schedule, not just the screening process.
What is the Analytic Horizon?
The researcher must make sure to include all costs and outcomes attributable to the intervention over the entire period that these costs and outcomes are observable or measurable.
In a CEA study for the varicella vaccination program described above, the analytic horizon would include the time frame (screening and delivery) plus the time during which the vaccine provides protective effects against acquiring the disease.
What is the Study Format?
The study format for a CEA may be:
  • a prospective study,
  • a retrospective study, or
  • a model.
What Outcome Measures Are We Interested In?
CEA outcomes are measured in natural or physical units and can be intermediate outcomes or final outcomes.
What Are the Available Alternatives?
After the study has been carefully framed, all appropriate interventions for comparison must be selected. For a CEA to be useful, the program under evaluation must be compared with all relevant alternatives.
The baseline comparator generally refers to the existing program and must be included as an option in the analysis. Alternatively, the baseline can be "no program." Including the baseline measure meets the needs of policy makers, who typically are interested in a new program's incremental costs (i.e., the costs beyond current expenditures) as well as in its effectiveness.
As a general rule, all programs that effectively achieve the same outcome among a given population and are deemed socially and politically acceptable should be considered as alternatives.
Which Costs Are Included in the CEA?
A CEA typically includes all tangible costs and excludes intangible costs.
Cost is referred to as the net cost, which is program costs minus 1) the cost of disease averted and 2) the cost of productivity losses averted. In a CEA, the costs of the disease averted and the cost of productivity losses averted are assessed by using the cost of illness (COI) method.
Net cost = Program cost Cost of disease averted Cost of productivity losses averted
Net cost is a summary measure that subtracts overall savings from gross program costs. Cost of disease averted and cost of productivity losses averted are subtracted because they are savings, and excluding them from the net cost equation will result in overestimating costs.
If the analysis is conducted from a societal perspective, averted productivity losses should be included in the net cost calculation. From a health-care system perspective, productivity losses might not be relevant.
Cost of Productivity Losses Averted
In a CEA, the human capital (HC) approach, a COI method, can be used to assess productivity losses.
The HC approach uses as its assessment measure forgone income attributable to morbidity and premature mortality as the result of some injury or illness. The HC methods are generally used to value productivity changes attributable to health problems.
An Example
Adopting a Research Strategy: Lifestyle versus structured interventions
Problem Sedentary lifestyles are:
  • thought to be associated with cardiovascular disease and diabetes, and
  • prevalent among adults in the United States.
Target audience
  • health-care providers who wish to improve the health of their patients, and
  • third-party payers who must consider health, costs, and service utilization of their enrollees.
CEA perspective The provider perspective was used, because costs individual to the patient are not included.
Time frame Twenty-four months for both interventions, the first 6 months being more intensive than the last 18 months.
Analytic horizon In this study, the analytic horizon is identical to the time frame, e.g., 24 months, because only intermediate outcome measures were assessed.
Study format Prospective.
Outcome measure under investigation The study used intermediate outcomes in the form of average units of improvement, including such measures as:
  • "change in energy expenditure,"
  • self-reported activity levels,
  • weight, and
  • blood pressure.
Costs included in the CEA Program costs included direct nonmedical costs, such as:
  • personnel (e.g., health educator and nutritionist),
  • capital equipment (e.g., computerized tracking system),
  • curriculum materials,
  • supplies (e.g., postage and printing),
  • facilities, and
  • health club memberships.
Costs borne by the patient (e.g., travel expenses) were not included in the cost inventory.
Test Your Understanding
  1. Is it appropriate to define the research problem clearly before adopting a strategy?
    Our Answer
    Generally, yes, because once projects are under way, their objectives and characteristics need to be defined so that appropriate research is conducted and succinct results are reported.
  2. Who is the audience for a study?
    Our Answer
    The users or consumers of the final results.
  3. What is the perspective of a study?
    Our Answer
    The perspective of a study is the viewpoint from which it is conducted. A study's perspective defines both the costs and benefits that are measured.
  4. Which costs are included in a study conducted from a societal perspective?
    Our Answer
    A study conducted from a societal perspective includes all relevant costs, regardless of who incurs them.
  5. Would patient travel costs be included in a study conducted from a health-care system perspective?
    Our Answer
    No. Travel cost borne by the patient would not be relevant to a health-care system; however, a study conducted from a patient or societal perspective would include such costs.
  6. What is the difference between a study time frame and analytic horizon?
    Our Answer
    • The time frame is the period over which program/intervention costs are tracked.
    • The analytic horizon is the period over which the costs and outcomes associated with the impact of the program/intervention are tracked.
  7. Is it possible to conduct a prospective study to assess the cost of a program that was recently terminated?
    Our Answer
    No. In a prospective study, information about costs is collected as the costs are incurred. No information can be collected prospectively if no program activity exists.
  8. List two intermediate outcomes that could be used to assess the effectiveness of a nursing home vaccination program.
    Our Answer
    • Number of vaccine doses administered
    • Number of persons receiving vaccine
  9. Give an example of a final outcome for this same program.
    Our Answer
    Number of life years gained from use of vaccine.
  10. List two alternative programs for a community wide education campaign for increasing child safety seat use.
    Our Answer
    • Incentive programs
    • Child safety seat laws
    • A combined distribution and education program
  11. What are the components of the net cost equation?
    Our Answer
    The three components are:
    1. program cost,
    2. cost of disease averted, and
    3. cost of productivity losses averted.
  12. Why are cost of disease averted and cost of productivity losses averted deducted from the program cost in the net cost equation?
    Our Answer
    Cost of disease averted and the cost of productivity losses averted are deducted from the program cost because they are savings.
    Ignoring costs averted understates the benefits and consequently overstates the cost of the program.
  13. In which of these studies should the cost of productivity losses averted be included in the net cost equation?
    A study conducted from a societal perspective
    A study conducted from the patient's perspective
    A study conducted from the health-care system perspective
    Our Answer
    The cost of productivity losses averted should be included in the net cost equation if the study is conducted from either:
    • a societal perspective, or
    • the patient's perspective.
  14. The cost of an intervention was estimated at $740,000 for 50 participants. The program averted 60% of disease conditions, and the average cost of the disease per person was estimated at $20,000. The total cost of productivity losses averted was estimated at $300,000.
    1. Calculate the cost of disease averted.
      Our Answer
      Using:
      Cost of disease per person = $20,000
      Number of persons with averted disease conditions = 0.6 x 50
        = 30
      Then:
      Total cost of disease averted = $20,000 x 30
        = $600,000
    2. Calculate the net cost from the societal perspective.
      Our Answer
      Using:
      Program cost = $740,000
      Cost of disease averted = $600,000
      Cost of productivity losses averted = $300,000
      Then:
      Net cost = Program cost Cost of disease averted Cost of productivity losses averted
      Net cost = $740,000 $600,000 $300,000
        = –$160,000
    3. Calculate the net cost from the health-care system perspective.
      Our Answer
      Using:
      Net cost = Program cost Cost of disease averted
      Then:
      Net cost = $740,000 $600,000
        = $140,000
  15. Given your answer to question 14B above, should the program be implemented?
    Our Answer
    Negative net costs imply savings, and such programs typically are implemented.
Which Outcomes are Relevant in CEA?
Introduction
Health outcomes set a CEA apart from other forms of economic evaluation (i.e., CA, CBA, and CUA).
The table below lists possible health outcomes. Each outcome should be considered in terms of "cost per health outcome" (e.g., cost per additional vaccination and cost per life-year saved).
Health Outcomes
Additional person vaccinated Additional person screened
Fatal injury prevented Increase in child safety seat use
Pregnancy prevented Case of lung cancer prevented
Child educated Work days lost
Reduction in blood pressure Increase in physical activity
Case of depression averted Length of hospital stay
Quality-adjusted life-year saved Life-year saved
Decisionmakers typically prefer to assess program costs against final outcomes, but when final outcomes are unavailable, CEAs must depend on intermediate outcomes. Therefore, intermediate outcomes should be used only in the following situations:
  • Intermediate outcomes are more closely associated with the intervention being examined:
    Program Outcome chosen Rationale
    Patient reminders Fully vaccinated child Link between vaccination and disease is not well established
  • Intermediate outcomes are directly measurable within the time frame of the study:
    Program Outcome chosen Rationale
    Smoking cessation campaign Number of quitters Cases of lung cancer prevented are too far in future
  • Cost data for a final outcome measure are insufficient:
    Program Outcome chosen Rationale
    Nurse home visitation Number of families reached Total child maltreatment cost is unknown
  • The relationship between the intermediate and final outcome is unknown:
    Program Outcome chosen Rationale
    HIV risk reduction Number of persons counseled Lack of evidence to link patients who have undergone counseling to cases of HIV prevented
Outcome Implications in CEA
  • Costs. One implication of the outcome chosen for a CEA deals with its related costs. To a large extent, the outcome defines which costs will be included in the analysis.
  • Value. The value of health outcomes used in a CEA is important not only for defining costs but also for assessing the program's overall health benefit.
Outcomes include the tangible benefits of an intervention, which are subsequently weighed against the intervention's associated costs. However, the ultimate decision of whether to implement a program often depends more on the implicit value of the outcome.
The example below illustrates the decision-making process for choosing an appropriate outcome.
Outcomes: A Hypothetical Example
Nearly 40,000 people die in the United States annually as a result of motor-vehicle crashes. Approximately 40% of these crashes are alcohol-related.
Substantial research has been devoted to preventing the number of injuries and deaths suffered as a result of motor-vehicle crashes.
The Problem
A state policy maker is provided a list of interventions that have been proven to reduce the number of injuries and deaths attributable to motor-vehicle crashes. The interventions are in these three primary areas:
  • child safety seat use,
  • safety belt use, and
  • alcohol-impaired driving.
"Which interventions should receive funding and support?"
The Data
If we assume that total costs of the interventions are similar, the information below is useful for solving this problem.
Promote Child Safety Seat Use
Interventions Outcomes
Community wide information and enhanced enforcement campaigns promote the use of child safety seats required by law in all 50 states. An example of this intervention would be a public display of proper safety seat use or mass mailings containing safety seat use information.
  • 12.3% increase in correct child safety seat use
Distribution and education programs provide child safety seats to parents of low socioeconomic status at no cost or at a low cost. In addition, educational materials explaining the importance of child safety seat use are included.
  • 6.4% decrease in fatal and nonfatal injuries
  • 7% increase in correct child safety seat use
Incentive and education programs provide educational information to parents regarding the appropriate use and importance of child safety seats as well as incentive rewards (e.g., movie tickets or food coupons) for subsequent correct use.
  • 9.9% increase in safety seat use
Promote Seat Belt Use
Interventions Outcomes
Primary enforcement laws empower law enforcement officers to stop and issue citations to drivers for not wearing safety belts. (Without these laws, officers may not stop drivers solely for safety belt violations.)
  • 9% decrease in fatal injuries
  • 17% increase in observed safety belt use
Enhanced enforcement includes boosting current efforts to enforce existing safety belt laws (e.g., increasing the number of officers on duty to issue citations or providing more safety belt checkpoints).
  • 11% decrease in fatal and nonfatal injuries
  • 24% increase in observed safety belt use
Reduce Alcohol-Impaired Driving
Interventions Outcomes
.08 Blood alcohol content (BAC) laws lower the BAC limit for drivers.
  • 7% decrease in fatalities
  • 5% decrease in alcohol-related crashes
Minimum legal drinking age (MLDA) laws set an age floor (e.g., age 21 years) for the purchase or consumption of alcoholic beverages.
  • 17% decrease in alcohol-related crashes (resulting from increasing the MLDA)
Sobriety checkpoints allow law enforcement officers to stop and administer selective breath testing to drivers suspected of being intoxicated.
  • 20% decrease in fatalities
  • 13% decrease in alcohol-related crashes
Recommendations
  • The outcomes indicate that the state policy maker should support community-wide information and enhanced enforcement campaigns because the intervention increases the correct use of child safety seats by 12.3%, compared with 7% and 9.9% increases for the other two interventions.
  • The outcomes indicate that the policy maker should fund enhanced enforcement campaigns that increase the use of safety belts by nearly 25%.
  • The outcomes indicate that minimum legal drinking age laws should be supported to reduce alcohol-impaired driving because of their effect on alcohol-related crashes compared with .08 BAC laws and sobriety checkpoints.
Question
The state legislature reduces the budget; as a result, the policy maker has funding sufficient to support only the single intervention that will have the greatest effect on final outcomes (e.g., fatalities prevented).
Which intervention should the policy maker choose?
Answer
Only five interventions — distribution and education programs, primary enforcement laws, enhanced enforcement, .08 BAC laws, and sobriety checkpoints — report final outcomes such as fatal injuries or fatalities prevented.
If one category (e.g., exceptionally low child safety seat use) is not a primary concern for that particular state, the policy maker should allocate the dollars to sobriety checkpoints.
Sobriety checkpoints result in a 20% reduction in fatalities whereas the other four interventions result in fatality reduction ranging from 6.4% to 11%.
Before the sobriety checkpoints intervention is implemented in the community, policy makers would generally assess the overall intervention cost.
If the intervention cost is predicted to be approximately $165,000, a CEA would be useful to evaluate the outcome (fatalities prevented) relative to the $165,000 cost.
Decision Analysis
Decision analysis is a modeling technique that provides a systematic framework for decision making.
  • The decision model is an applied tool that has been adapted to public health for patient- and population-based decision making.
  • Decision models are informative and visually appealing for breaking down complicated problems into their components, including the primary goal, alternatives, chance events, and payoffs (outcomes). This decision tree shows a goal with two alternative interventions:
This decision tree shows a goal with two alternative interventions.
In public health, decision analysis is particularly useful for solving problems for which different alternatives (e.g., lower BAC laws, MLDA laws, or sobriety checkpoints for reducing the number of fatalities associated with alcohol-related motor-vehicle crashes) might be selected.
Decision modeling is important in CEA because it takes into account the uncertainty in events and outcomes.
For example, in the case of a sobriety checkpoints intervention, if "prevented fatality" is the outcome chosen for the study, a thorough decision model will include the uncertainty associated with effectiveness of the intervention, probable risk, and measurement error.
Decision Tree Components
The decision tree above is only one form of decision models. Decision trees are made up of three types of nodes: decision, chance, and terminal nodes
The "Goal" Component
The goal component explains the problem or labels the objective for the decision at hand.
For example, a state experiencing high fatalities as a result of alcohol-related motor-vehicle crashes could decide whether or not to implement sobriety checkpoints in all counties. The goal of the related decision problem is to reduce the number of fatalities. This decision tree outlines two alternatives:
This decision tree shows two alternatives to reduce motor-vehicle crash fatalities.
The "Alternative" Component
  • The alternative component begins the pathway for each program or intervention competing for the same resources.
  • The number of branches included at this first decision node (blue square) of the tree should be commensurate with the number of alternatives being considered.
For example, the state policy maker is considering only sobriety checkpoints. Note that current practice could include previously mandated BAC and MLDA laws, as shown in this decision tree:
This decision tree shows alternatives: BAC laws, sobriety checkpoints, and MLDA laws.
The "Chance Event" Component
  • An alternative generally leads to a chance event. A numerical probability is assigned to each event to account for uncertainty.
  • Probabilities are typically provided by previous studies of randomized clinical trials or expert opinion. Because the probabilities for any chance node (green circle) must sum to 1.0, the list of events must be exhaustive.
For example, if a pneumococcal conjugate vaccine is administered to a child, multiple chance events (e.g., pneumococcal disease, meningitis, or ear infections) might occur.
A separate branch should represent each chance event or disease state, and all probabilities assigned to the branches must sum to 1.0.
Now assume that prior studies suggest the probability of an alcohol-related crash is 40% under current practice (with no program) and 13% lower with sobriety checkpoints. These values are incorporated into this decision tree:
This decision tree shows the probabilities of an alcohol-related crash for no intervention and with sobriety checkpoints.
Note that the sum of probabilities at each chance node is 1.0 (e.g., 0.27 + 0.73 = 1.0).
The "Payoff" Component
  • The desirability of each outcome determines its payoff.
  • The payoff for a particular outcome is relative to the payoffs for other outcomes included in the analysis.
In the example below, assume the outcome is deaths per 100,000 persons. Currently, one fatality for every 100,000 persons is attributable to alcohol-related motor-vehicle crashes whereas only 0.8 deaths per 100,000 persons occur with sobriety checkpoints (i.e., the intervention reduces the fatality rate by 20%).
In this decision tree, values of 0.0 are assigned to the crash-free outcomes that result in no fatalities:
This decision tree shows values of 0.0 assigned to the crash-free outcomes that result in no fatalities.
Expected Value
  • Expected values use the probabilities associated with each chance event and the payoff value assigned to each outcome to determine which alternative should be chosen.
  • Whether or not to choose the alternative with the lower or higher expected value depends on the outcome.
For instance, the earlier "Payoff" ComponentJump to another section on this page. Use the Back command to return. example uses deaths per 100,000 persons as the outcome; therefore, the lower expected value will determine the correct decision.
In contrast, if life-years saved were the outcome, the decision would be made based on the higher expected value.
Expected values are calculated simply by summing the probability-payoff products for each alternative. In the earlier example, the expected value (EV) for sobriety checkpoints is:
EV = (0.8 x 0.27) + (0.0 x 0.73)
= 0.22
The decision tree below shows the expected values at each chance node (green circle). Each value is shown in a green box to the right of the chance node.
This decision tree shows the expected values for the sobriety checkpoints intervention and for no intervention to be 0.22 and 0.40, respectively.
In the decision tree, the expected values for the sobriety checkpoints intervention and for no intervention are shown as 0.22 and 0.40, respectively.
The appropriate decision is to implement sobriety checkpoints because they reduce the number of fatalities attributable to alcohol-related motor-vehicle crashes compared with current practice.
In this example, the better choice (i.e., sobriety checkpoints) is straightforward.
Steps in Decision Analysis
  1. Define the problem and specify the goal or objective of the analysis.
  2. Develop a comprehensive model that takes into account all possible pathways and chance events over time.
  3. Estimate probabilities at chance nodes by using published sources and expert opinion. (Be sure the sum of all probabilities at each node is 1.0.)
  4. Assign payoff values to outcomes.
  5. Calculate expected values.
  6. Further evaluate uncertainty.
Sensitivity Analysis
  • Uncertainty can be further evaluated by sensitivity analysis. Essentially, sensitivity analysis involves providing a range for all probabilities and outcome values included in the decision model that are particularly important to the results.
  • The reason for conducting sensitivity analyses after the model has been run with initial estimates is to increase the validity of conclusions drawn from the model.
  • If the decision does not change after key inputs are tested, results will be more substantive.
For example, the chance of an alcohol-related crash occurring at current practice might be tested from 20% to 60%.
Likewise, the payoff value of 0.8 deaths per 100,000 persons attributable to alcohol-related crashes might be tested from 0.2 to 1.5 deaths per 100,000 persons.
Advantages and Limitations of Decision Analysis
  • Decision analysis is most useful for problems with near-term outcomes or final outcomes that occur in straightforward paths.
  • The more complicated the pathway, the more difficult it is for decision analysis to take into account all possible avenues of chance events and decisions.
  • Both a limitation and advantage of decision analysis is its dependence on estimated values and hypothetical events.
    The "guesswork" inherent in the model is a limitation but applies to any modeling technique.
  • The primary advantage of decision analysis is its ability to tackle difficult research problems that otherwise would not be assessed because of time or resource constraints.
An Example: Decision Analysis
Suppose that current practice for curbing alcohol-related driving includes MLDA laws only.
If alcohol-related motor-vehicle crash prevalence is high, a policy maker might consider imposing tighter restrictions and increasing law enforcement capabilities. Therefore, BAC laws and sobriety checkpoints should be included in the decision.
Assume that under MLDA laws only, 40% of crashes are related to alcohol and that BAC laws reduce that rate by 5%. In addition, assume that one death per 100,000 persons is attributable to MLDA laws whereas BAC laws reduce that number 7%.
This information as well as that for sobriety checkpoints provided in the decision tree for the earlier "Payoff" ComponentJump to another section on this page. Use the Back command to return. example can be used to add a third alternative branch to the decision tree.
This decision tree shows 3 alternatives: BAC laws, sobriety checkpoints, and MLDA laws.
Once the new branch is added, expected values are calculated to generate a new decision rule.
EV = (0.93 x 0.35) + (0.0 x 0.65)
= 0.33
This decision tree shows that the sobriety checkpoints intervention has a greater impact than either BAC or MLDA laws.
In this case, the decision rule is the same. The sobriety checkpoints intervention should be implemented because it has a greater impact on reducing the number of fatalities attributable to alcohol-related accidents compared with BAC and MLDA laws.
Test Your Understanding
  1. What distinguishes CEA from CBA?
    Our Answer
    CEA assesses health outcomes in natural or physical units (e.g., additional patient screened) whereas CBA converts outcomes to dollars.
  2. Why are value judgments inherent in CEA decision making?
    Our Answer
    Decisionmakers often exercise judgment when assessing the results of CEA studies. In effect, cost cutoff points are established above which no program will be funded.
    Decisionmakers must answer questions such as:
    • Is an additional life-year worth $100,000?
    • Is a case of depression prevented worth $50,000?
    • Is the money used more efficiently if allocated in a different manner?
  3. Why is "number of children educated" not a suitable health outcome for state policy makers wishing to distribute tobacco settlement monies appropriately?
    Our Answer
    State policy makers are responsible to their constituents for how funds are allocated to improve the public's health.
    Tobacco-control programs that are definitively linked to final outcomes (e.g., "cases of lung cancer prevented") would be more appropriate for state support.
  4. What is necessary for the comparison of two alternative health conditions with CEA?
    Our Answer
    For CEA to be useful in this case, a final outcome common to both interventions is necessary.
  5. Which one of these reasons does NOT justify using an intermediate outcome in CEA?
    Insufficient cost data
    Researcher interest in the intermediate effect
    No close association between final outcome and intervention
    Outcome measurement exceeds the study time frame
    No link between intermediate and final outcome
    Our Answer
    The second reason:
    Researcher interest in the intermediate effect
    is NOT reason enough to warrant its use in place of a final outcome measure.
  6. Suppose a lifetime UV exposure reduction program effectively prevents cases of melanoma. Assume that 20% of persons with high lifetime exposures develop melanoma.
    1. If 150 persons undergo the program, how many cases of melanoma are prevented?
      Our Answer
      20% of 150 is 30. So 30 cases of melanoma are prevented under these circumstances.
    2. Would medical costs associated with melanoma be included in the scenario?
      Our Answer
      Yes. If the link between persons in the program and prevented cases of melanoma is known, all costs associated with the final outcome should be included.
  7. Which step in decision analysis is missing from this list?
    • Define problem
    • Develop model
    • Estimate probabilities
    • Assign payoff values
    • Calculate expected values
    Our Answer
    The final step, "Further evaluate uncertainty," is not included in the list.
    The study is not complete after construction of the tree and assignment of numerical estimates to relative branches. Sensitivity analysis must be employed to test important parameters and substantiate the findings.
Interpreting CEA Results
Cost Effectiveness Ratios
Once a CEA has been conducted and cost effectiveness has been calculated, ratios combining the expected results are calculated and reported. The cost referred to in the CER is a net cost value discussed earlier in the section: "Which Costs Are Included in the CEA?"Open this in a new window
There are three types of cost effectiveness ratios (CERs):
  • Average cost-effectiveness ratio (ACER),
  • Marginal cost-effectiveness ratio (MCER), and
  • Incremental cost-effectiveness ratio (ICER).
ACER
An ACER
  • deals with a single intervention and evaluates that intervention against its baseline option (e.g., no program or current practice).
  • is calculated by dividing the net cost of the intervention by the total number of health outcomes prevented by the intervention.
An Example of an ACER
Intervention Net cost Total outcomes
(life-years saved)
ACER
cost per life-year saved
Home vaccination program $50,000 8 $6,250
MCER
The marginal cost-effectiveness ratio (MCER) assesses the specific changes in cost and effect when a program is expanded or contracted.
Because the majority of programs that are cost effective are considered good investments only at a certain level, the MCER and ACER are often considered simultaneously.
This figure shows the ACER and MCER for the vaccination program example:
ACER and MCER for the vaccination program example.
At low vaccination coverage rates (approximately 70%), the ACER is negative, indicating a savings in cost. As that percentage grows, however, so does the cost per case prevented because the marginal cost per each additional person vaccinated is much higher than the average cost.
In general, the MCER is used in conjunction with the ACER as a tool to determine the most efficient level of program implementation.
Once this level is determined, the ACERs of that and other independent programs that result in the same outcome can be compared.
ICER
An ICER
  • compares the differences between the costs and health outcomes of two alternative interventions that compete for the same resources, and
  • is generally described as the additional cost per additional health outcome.
When comparing two competing programs incrementally, one program should be compared with the next-less-effective alternative.
The ICER numerator includes the differences in program costs, averted disease costs, and averted productivity losses if applicable. Similarly, the ICER denominator is the difference in health outcomes.
An Example: Decision Analysis CERs
The values and estimates used in this analysis were modified from various studies for the purposes of this example and should not be considered literally.
Consider a policymaker that is trying to decide whether or not to implement a sobriety checkpoints program if BAC and MLDA laws (baseline) are already in place. The probabilities and payoffs (costs and outcomes) for each branch pathway are shown in this decision tree:
Decision tree for the sobriety checkpoints intervention when BAC and MLDA laws (baseline) are already in place.
  • The outcome of interest is deaths per 100,000 persons.
  • Total costs for the baseline option include trial and sanctioning and law enforcement costs.
  • Total costs for the sobriety checkpoint program include officer wages, equipment, publicity, travel delay, and sanctioning costs.
  • Both total cost estimates also include the costs (medical and productivity losses) associated with a fatality resulting from an alcohol-related crash.
The expected total cost estimates (i.e., values that take probabilities into account) are shown in the decision tree below. Each value is shown in a green box to the right of the chance node (green circle).
This decision tree shows the expected total cost estimates of $12,360 for the sobriety checkpoints intervention and $9,200 for no checkpoints.
The additional cost of sobriety checkpoints is:
$12,360 $9,200 = $3,160
The expected total outcome values indicate that sobriety checkpoints are more effective (i.e., result in fewer deaths per 100,000 persons) than the baseline option. This analysis is presented in this decision tree:
This decision tree shows that the expected total outcome values indicate that sobriety checkpoints are more effective (i.e., result in fewer deaths per 100,000 persons) than the baseline option.
The cost and outcome results considered separately warrant the use of CEA. Sobriety checkpoints are both costlier and more effective than what is currently being done. This decision tree shows both results.
This decision tree shows the cost and outcome results with and without sobriety checkpoints.
From the numbers in this decision tree, the ICER comparing sobriety checkpoints to the baseline option is:
ICER = ( Total costB Total costA ) / ( Total outcomesA Total outcomesB )
ICER = ( $12,360 $9,200 ) / ( 0.37 0.22 )
ICER = $21,066.67 per death prevented
If program costs and health outcomes are different but averted disease costs (i.e., alcohol-related crash costs) are the same, then the ICER should be computed as:
ICER = ( Add'l program cost Add'l cost of disease averted ) / Add'l health outcomes
ICER = ( $3,160 $0 ) / 0.15
ICER = $21,066.67 per death prevented
This analysis suggests that each death prevented by sobriety checkpoints will cost $21,066.67.
Exclusion Criteria
  • The programs are arrayed in order from least to most effective in terms of outcomes prevented.
  • This is done first so that the ICERs may be calculated and resources allocated appropriately.
This table shows data and calculations for Program A, an expanded Program A, and Programs B and C:
Programs Prevented outcomes Total costs ACER MCER ICER
Independent programs  
Program A 10 $150 $15    
Expanded program A 12 $200   $25  
Mutually exclusive programs  
Program A 10 $150      
Program B 20 $300     $15
Program C 25 $250     –$10
Notes for Table Columns
ACER
ACERs can be calculated with an alternative formula similar to that for ICERs above if the baseline is "no program":
ACER = ( $150 $0 ) / ( 10 0 )
ACER = $15 per additional outcome prevented
MCER
MCER = ( $200 $150 ) / ( 12 10 )
MCER = $25 per additional outcome prevented
ICER
ICERB to A = ( $300 $150 ) / ( 20 10 )
ICERB to A = $15 per additional outcome prevented
and
ICERC to B = ( $250 $300 ) / ( 25 20 )
ICERC to B = –$10 per additional outcome prevented
If program A is expanded, the MCER is $25. Because $25 is higher than $15, a decisionmaker needs to decide whether or not expansion is worth the additional cost.
If two competing programs are compared, such as programs A and B, the ICER is $15. The comparison between programs C and B shows a cost saving of $10 for program C over program B.
The negative ICER for program C indicates that program B is "strongly dominated." In other words, program B is more costly and less effective than program C.
Strongly dominated programs should be excluded from the set of alternatives so they do not consume limited resources. In addition, the ICERs should be recalculated so that the magnitude of the negative ICER is not misleading, as shown in this table:
Mutually exclusive programs Prevented outcomes Total costs ICER
No program 0 0
Program A 10 $150 $15
Program B 20 $300 $15
Program C 25 $250 $6.67
ICER Calculation for Program C
ICER = ( $250 $150 ) / ( 25 10 )
ICER = $6.67 per additional outcome prevented
If a program's ICER is higher than the next most effective program, the program is "weakly dominated." In effect, weakly dominated programs produce effectiveness at a higher marginal cost, which means that some combination of at least two other alternative programs is more cost effective.
In this table, Program D is compared with Program C because they are ranked in order of increasing effectiveness:
Mutually exclusive programs Prevented outcomes Total costs ICER
Program A 10 $150
Program B 20 $300 $15
Program C 25 $250 $6.67
Program D 40 $325 $5
In this case, some combination of programs A and D is more cost effective than program C. Therefore, program C should be removed from the list of alternatives and the results recalculated accordingly (i.e., program D compared with program A). This table shows the final results:
Mutually exclusive programs Prevented outcomes Total costs ICER
Program A 10 $150
Program B 20 $300 $15
Program C 25 $250 $6.67
Program D 40 $325 $5.83
Decision Guidelines
Decision making is a complex process that takes into account much more than numbers and calculations.
Value judgments are often implicit in the choice made by a decisionmaker.
Even so, calculations that allow comparisons to be made between independent and competing programs are important and generally valued by decisionmakers.
Users of CEA can allocate limited resources and make decisions more efficiently if certain decision rules or guidelines are followed.
When Assessing Independent Programs
  1. Order the programs from least to most effective.
  2. Eliminate the strongly dominated programs.
  3. Calculate ACERs.
  4. Implement programs in order of increasing ACER until either resources are exhausted or the ACER is equal in value to one unit of effectiveness.
When Assessing a Mix of Independent and Mutually Exclusive Programs
  1. Form groups of mutually exclusive programs.
  2. Order programs within each group from least to most effective.
Within Each Group
  1. Calculate the ICER.
  2. Eliminate both strongly and weakly dominated programs.
  3. Calculate the ACER of each independent program.
  4. Rank all programs in order of increasing ratio.
  5. Implement programs in order of increasing ACER until either resources are exhausted or the ratio is equal in value to one unit of effectiveness.
Presentation of Results
Presenting CEA results in a comprehensive and concise manner is imperative to CEA's overall usefulness among decisionmakers. The information included in a CEA is practical and advantageous to the decision making process.
Thus, the presentation of a CEA should include these eight major elements:
Eight Elements of a CEA
  1. A clear study perspective, time frame, and analytic horizon
  2. An explicitly defined study question
  3. Relevant assumptions underlying the study
  4. Detailed descriptions of the interventions
  5. Existing evidence of the interventions' effectiveness
  6. Proper identification of all relevant costs:
    • decide whether to include or exclude productivity losses
    • apply appropriate discount rate
    • confirm that included costs are relevant to perspective
  7. An appropriate choice of outcome:
    • calculate a suitable CER
    • report ICER results (unless the only comparator is baseline)
    • conduct sensitivity analyses
  8. A comprehensive discussion of the results:
    • deal with issues of concern
    • address implications of underlying assumptions
Test Your Understanding
  1. Should a highly effective intervention always be supported? Why or why not?
    Our Answer
    A highly effective intervention should not necessarily be supported regardless of cost.
    Both cost and outcome should be taken into account when deciding whether or not to allocate funding to a particular program.
  2. Why is the net cost — rather than total program costs — relevant for CERs?
    Our Answer
    The net cost takes into account the benefits that are attributable to the intervention and therefore provides a "true" estimate of cost.
    Without subtracting future savings, the cost would be overestimated, resulting in a large CER.
  3. Provide a criticism of using the human capital (HC) approach to measure productivity losses.
    Our Answer
    By using forgone wages to calculate productivity losses, the HC approach systematically undervalues persons who receive lower wages (e.g., women and certain blue-collar workers).
  4. Calculate the ACER for a program with these costs and outcome:
    • Program cost = $10,000
    • Disease cost averted = $2,000
    • Productivity losses averted = $3,000
    • Life-years saved relative to no program = 5
    Our Answer
    ACER = ( Program costs Averted disease costs Averted productivity losses ) / Health outcomes prevented
    ACER = ( $10,000 $2,000 $3,000 ) / 5
    ACER = $1,000 per life-year saved
  5. Calculate the MCER for expanding the program:
    • Total costA = $15,000
    • Total costAx = $20,000
    • Total outcomesA = 5
    • Total outcomesAx = 7
    where subscripts:
    • "A" refers to the original program and
    • "Ax" refers to the expanded program.
    Our Answer
    The MCER is the ratio of the differences in total costs and total outcomes between the initial program level and expansion level.
    MCER = ( Total costAx Total costA ) / ( Total outcomesAx Total outcomesA )
    MCER = ( $20,000 $15,000 ) / ( 7 5 )
    MCER = $5,000 / 2
    MCER = $2,500 per outcome
    Comparing the MCER for expanding program A to its ACER in the answer to question 4 suggests maintaining the program at its current production level rather than funding expansion.
  6. Calculate the ICER for two alternative programs, "A" and "B," competing for resources, given:
    • Total costA = $15,000
    • Total costB = $ 30,000
    • Total outcomesA = 8
    • Total outcomesB = 5
    where a program outcome is the count of disease cases attributable to the program.
    Our Answer
    The ICER is the ratio of the differences in total costs and total outcomes between the two programs.
    ICER = ( Total costB Total costA ) / ( Total outcomesA Total outcomesB )
    ICER = ( $30,000 $15,000 ) / ( 8 5 )
    ICER = $15,000 / 3
    ICER = $5,000 per disease case prevented
  7. Explain the difference between strongly and weakly dominated programs.
    Our Answer
    A strongly dominated program is one for which an alternative exists that is both more effective and less expensive. Weakly dominated programs generate effectiveness at a higher marginal cost than an alternative program.
    Any program that is dominated by another should be removed from the list of competing alternatives so that the most efficient allocation of resources can be achieved.
Glossary — CEA
Analytic horizon
The period over which costs and outcomes associated with the intervention accrue. Costs and outcomes are measured during the intervention and after it ends.

Audience
The consumers or users of the results of a cost effectiveness analysis.

Average cost-effectiveness ratio (ACER)
Ratio that deals with a single intervention and evaluates that intervention against its baseline option (e.g., no program or current practice).
The ACER is calculated by dividing the net cost of the intervention by the total number of health outcomes prevented by the intervention.

Cost effectiveness analysis (CEA)
An economic evaluation method in which all costs are related to a single common outcome or natural unit (e.g., life years saved).

Cost of illness (COI)
A method generally used to determine the economic burden of a disease by assessing the direct medical and nonmedical costs of disease averted as well as productivity losses averted.

Cost-effectiveness ratio (CER)
An end result that summarizes the intervention's net cost and effectiveness. The three types of CERs are:
  • Average cost-effectiveness ratio (ACER),
  • Marginal cost-effectiveness ratio (MCER), and
  • Incremental cost-effectiveness ratio (ICER).

Decision analysis
A modeling technique that systematically aids in decision making by considering the uncertainty associated with alternative solutions to a particular problem

Disease costs averted
All expected costs that are related to a disease or condition and that are not incurred by society (or some other entity) as a result of implementing a program or intervention.

Economic burden
The total cost incurred by society for a particular disease or condition.

Economic evaluation
The use of applied analytic techniques to identify, measure, value, and compare the net costs and outcomes of alternative interventions.

Effective
The improved health outcome that a prevention strategy can achieve under typical community-based settings.

Efficacious
The improved health outcome that a prevention strategy can achieve under ideal settings.

Final outcome
The ultimate outcome of interest, such as years of life gained or deaths prevented.

Human capital approach
As a method of COI, the human capital approach assesses productivity losses by using forgone income attributable to morbidity and premature mortality of a disease or condition.

Incremental cost-effectiveness ratio (ICER)
The additional cost of one unit of outcome when we change to a more effective, mutually exclusive intervention.

Intermediate outcome
Near-term effects of an intervention, such as persons screened, rate of condom use, or number of vaccine doses administered.

Marginal cost-effectiveness ratio (MCER)
The additional cost of one unit expansion of a single intervention.

Model
A simplified yet accurate representation of a program or intervention based on a set of assumptions.

Outcome measure
A measurement unit used to assess the effectiveness of a program or intervention.

Output
The product or service produced (e.g., patients seen, patient days).

Payer
An individual or organization that provides money to pay for health-care services.

Perspective
The viewpoint of the bearers of the costs and benefits of an intervention (e.g., society, government, health-care providers, businesses, or patients).

Productivity losses
Refer to the value of time (usually in terms of wages) that is forgone as a result of the morbidity or premature mortality associated with a disease or condition.

Program costs
Include all fixed and variable costs that are incurred as a result of program implementation and maintenance.

Prospective study
A study in which the events of interest (costs and outcomes) have not yet taken place when the study begins.

Retrospective study
A study in which the events of interest (costs and outcomes) have already occurred when the study begins.

Sensitivity analysis
Method for testing the validity of decision analysis findings by providing a range for all probabilities and outcome values included in the decision model that are particularly important to the results.

Societal perspective
The broadest possible perspective for an economic evaluation. It includes all program costs, no matter who incurs them, and all program consequences, no matter who experiences them.

Target population
The population(s) for whom the program is intended.

Time frame
The period over which program or intervention costs are tracked.

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