Cost Effectiveness Analysis: Relevant Outcomes

Which Outcomes are Relevant in CEA?

Introduction

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

Program	Outcome chosen	Rationale
Patient reminders	Fully vaccinated child	Link between vaccination and disease is not well established

Program	Outcome chosen	Rationale
Smoking cessation campaign	Number of quitters	Cases of lung cancer prevented are too far in future

Program	Outcome chosen	Rationale
Nurse home visitation	Number of families reached	Total child maltreatment cost 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

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

Question

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 "Alternative" Component

The "Chance Event" Component

The "Payoff" Component

Expected Value

Steps in Decision Analysis

Sensitivity Analysis

Advantages and Limitations of Decision Analysis

An Example: Decision Analysis

Test Your Understanding

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.
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?
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.
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.
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.
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.
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.

EV	=	(0.8 x 0.27)	+	(0.0 x 0.73)
	=	0.22

EV	=	(0.93 x 0.35)	+	(0.0 x 0.65)
	=	0.33