The document discusses quality-adjusted life years (QALYs) as a method for measuring health outcomes by combining survival periods and health status valuations. It explores various economic evaluation techniques, including cost-minimisation analysis, cost-effectiveness analysis, and cost-utility analysis, to compare healthcare interventions based on their costs and benefits. Additionally, it emphasizes the importance of incremental cost-effectiveness ratios (ICERs) in decision-making when evaluating the trade-offs between different treatment options.

1. • 4-Quality-adjusted life years
• The utility measures are used to generate quality adjusted life-years (QALY). A
QALY combines survival periods (quantity of life) with health status valuations
(quality of life) to provide a standard unit for measuring health gain. One QALY
is 1 year in perfect health. One QALY could also be 2 years at 'half perfect health.
• A treatment that moves a patient from 0.5 to 0.75 produces the equivalents of 0.25
QALY if it is maintained for 1 year. If applied to 4 individuals, and duration of the
treatment effect is 1 year, the effect of the treatment would be equivalent to 1
completely well-year life. If you value health states using QALYs, you can
compare different treatments. This method would let you compare the health
gain from hip replacements with those due to antidepressant treatment, even
though the clinical indicators for these conditions are very different.

2. Whose utility values should be used?
Utility values can be obtained from healthcare professionals, patients and
the general public.
There are advantages and disadvantages associated with each group.
• Healthcare professionals are more informed about the health states
and interventions but may provide a biased value owing to their
continued exposure to that illness or intervention. Healthcare
professionals have been shown to assign lower ratings than patients or
the general public.
Patients are informed about the health states and interventions they have
experienced. They will not be informed about interventions they have not
experienced

3. • 5- Expressing benefits as monetary values
Another method of measuring outcome is to convert these benefits to
a monetary value. The 'willingness to pay' (WTP) method, elicits
monetary values for items not typically traded in private markets, such
as health.

4. Pharmacoeconomic
Methodologies

5. Introduction
There is often more than one way of doing something in healthcare.
For example, there may be two different drugs that can be used to treat
depression, or two surgical techniques for the management of dysmenorrhoea.
Note that interventions may be compared against each other (for example
antibiotic A against antibiotic B) or against a 'do nothing' scenario.
There are different ways in which we can choose one of these options. We may
decide to pick the more effective surgical technique, or we may decide to
select the less costly antidepressant. Economic evaluation is a generic term for
techniques that are used to identify, measure and value both the costs and the
outcomes of healthcare interventions. An economic evaluation is concerned
with identifying the differences in costs and outcomes between options. It can
be defined as a study that compares the costs and benefits of two or more
alternative interventions; so, the main components are costs and benefits

6. Types of economic evaluation
There are four main types of economic evaluation:
Cost- minimisation analysis (CMA)
Cost-effectiveness analysis (CEA)
Cost-utility analysis (CUA)
Cost-benefit analysis (CBA).
Although they employ similar methods to define and evaluate costs,
they differ in the methods used to estimate the benefits from a
program or intervention.

7. The components of economic evaluation.
It is clear that economic evaluations can be understood in terms of
the inputs (costs) and outputs (benefits or outcomes) of a healthcare
intervention.

10. Cost-minimisation analysis (CMA)
In CMA, the outcome of the treatments being compared is the same. Having ensured that
the outcomes between the comparators are equivalent, then the approach used is to
consider the costs of each option. The preferred option is the cheapest.
For example, suppose two antibiotics, G and C, are equally effective in the treatment of
Pseudomonas pneumonia, according to the current evidence. Therefore, we should use
the least costly alternative. The following assumptions have been made:
The two interventions are equally effective.
We have included all the costs.
A recent economic evaluation of Atenolol versus Captopril in hypertensive patients with
type 2 diabetes reported that there was no statistically significant difference in life
expectancy between groups (Gray et al., 2001). However, the mean cost per patient over
the trial period was £6,485 in the Captopril group and £5,550 in the Atenolol group. The
reduction was statistically significant and was due partly to differences in drug acquisition
prices, and partly due to fewer and shorter hospitalizations in the Atenolol group. The
results from this CMA would suggest that Atenolol should be used in preference to
Captopril in this group of patients.

11. Another common example of CMA is comparing medications that are the
same chemical entity, the same dose, and have the same pharmaceutical
properties (i.e. they are bioequivalent) such as brand versus generic or
generic made by one company compared with generic made by another
company. In these cases only the cost of the medication itself needs to be
compared because outcome should be the same.
Another example of CMA includes measuring the cost of receiving the same
medications in different setting. For example researchers could measure the
costs of receiving I.V. antibiotics in a hospital and compare this with receiving
the same antibiotics (at same doses) at home via a home health care service.
CMA is the simplest of the four types of pharmacoeconomics analysis
because the focus is on measuring the left-hand side of the
pharmacoeconomic equation (the cost) and the right –hand side of the
equation (outcomes) is assumed to be the same.
This method is limited in use because it can only compare alternatives with
the same outcomes

12. Cost-effectiveness analysis
Cost-effectiveness analysis is a technique designed to assist a decision-
maker in identifying a preferred choice among possible alternatives.
Generally, cost-effectiveness is defined as a series of analytical and
mathematical procedures that aid in the selection of a course of
action from various alternative approaches. Cost-effectiveness
analysis has been applied to health matters where the program's inputs
can be readily measured in dollars, but the program's outputs are more
appropriately stated in terms of health improvement created (e.g., life-
years extended, clinical cures)

13. Outcome measures in cost-effectiveness analysis
In CEA, outcomes are reported in a single unit of measurement, and are given in
natural units, for example mmHg for blood pressure reduction, or life years
gained by transplantation. The outcome measure is common to both
alternatives, but may be achieved to different degrees (i.e. there is a difference
in effectiveness).
An economic evaluation could examine the use of coronary artery bypass graft
(CABG) surgery for ischemic heart disease compared with medical (drug therapy
only) management.
The effectiveness of both treatment methods can be measured using mortality at
10 years.
Evidence suggests that it is likely that mortality will be lower if CABG is used.
Therefore, cost-effectiveness analysis is the appropriate method to use because
the outcome is common to the two alternatives, but there is a difference in
effectiveness

14. Cost-Effectiveness Ratios
Results from a CEA are typically expressed as a cost-effectiveness (C/E)
ratio;. Two forms of the C/E ratio exist:
(1) average, or simple.
(2) incremental (ICER).
The average/simple C/E ratio is a straightforward approach, defined as
follows:

15. • Although average C/E ratios provide useful information for analysts,
incremental analyses are considered a hallmark of CEA.
• In cost-effectiveness analysis (and cost-utility analysis) you will come
across the regular use of incremental economic analysis. This is a sys-
tematic method for identifying the difference (increment) in costs and
outcomes between two healthcare interventions. The following ques-
tions are always asked:
• What is the difference in cost between the interventions?
• What is the difference in outcome between the interventions?

16. The answers to these questions allow the derivation of the incremental
cost-effectiveness ratio (ICER). Incremental cost/outcome ratios may be
calculated using the following equation

17. Outcome1 is the number of patients successfully treated with intervention 1.
Outcome 2 is the number of patients successfully treated with intervention 2.
Cost 1 is the cost of treating patients with intervention 1.
Cost 2 is the cost of treating patients with intervention 2.
The ICER expresses the cost required to achieve each extra unit of
outcome. When one alternative is more effective but requires more
resources, the ICER must be calculated. In the situation when one alter-
native is more effective and less costly, this alternative is the dominant
therapy. When there is dominance, ICERs do not need to be generated
(see Worked example 5.1)

18. WORKED EXAMPLE 5.1 incremental economic analysis.
An economic evaluation could examine the first-line management of community-acquired
pneumonia using antibiotics A or C. The effectiveness for both treatment methods can be
measured using 'infections successfully treated first line'.
The incremental economic analysis is carried out in the following way:
What are the costs associated with treatment with
Antibiotic A [CostA]
Antibiotic C [Costc]
What are the outcomes associated with
a) Antibiotic A [Outcome A]
b) Antibiotic C [Outcome C]
What is the difference in cost between using antibiotic A and antibiotic C?
[Cost A – Cost C]
What is the difference in outcome between using antibiotic A and antibiotic C?
[Outcome A – Outcome C]
ICER for treating community-acquired pneumonia with antibiotic A instead of antibiotic C

20. Using an incremental cost-effectiveness ratio to make a decision.
After reading Worked example 5.1, you may now ask yourself: which antibiotic
do you think should be chosen by the healthcare decision maker? This example
illustrates that carrying out incremental cost-effectiveness analysis does not
necessarily provide an obvious option: this will only happen when dominance
occurs, where it is clear that the more effective, less costly option should be
selected. However, the decision-maker usually has to select between the more
costly, more effective option and the less costly, less effective option.
The generation of the ICER allows us to see how much extra cost is incurred
for the extra benefit. It is then left to the decision-maker to make a value
judgement as to whether they think that the extra benefit is worth the extra
cost. In the example above, the decision-maker must decide whether they
think that the extra case of pneumonia successfully treated with antibiotic C is
worth £200. This is a disadvantage of cost-effectiveness analysis.

21. Cost-Effectiveness Grid Cost of Alternative A Relative to Alternative B
LOWER EQUAL HIGHER
Effectiveness of Alternative A Relative
to Alternative B
HIGHER A(+) (Dominant) B (+) C (+/-)(TRADE-OFF)
EQUAL D(+) E Arbitrary F(—)
LOWER G (+/-) (Trade-off) H (—) I (Dominated)
Figure 5.1. Cost-effectiveness grid

22. A cost-effectiveness grid can be used to illustrate the definition of "cost-effectiveness" (Figure 5.1). To
determine if a therapy or service is cost effective, both the costs and effectiveness must be considered.
Think of comparing a new drug with the current standard treatment. If the new treatment is:
1) Both more effective and less costly (cell A),
2) More effective at the same price (cell B), or
3) Has the same effectiveness at a lower price (cell D),
The new therapy is considered cost effective.
On the other hand, if the new drug is :
1) Less effective and more costly (cell I),
2) Has the same effectiveness but costs more (cell F), or
3) Has lower effectiveness for the same costs (cell H).
Then the new product is not cost effective.
For the middle cell E, other factors may be considered to determine which medication might be best.
For the other two cells (C and G), an ICER is calculated to determine the extra cost for each extra unit
of outcome.
Dominant strategies are defined as offering both lower cost and higher effectiveness compared with
an alternative, while a dominated strategy is one that costs more than the comparator and is less
effective. Options requiring a trade-off include technologies that present a higher cost with higher
effectiveness or lower cost with lower effectiveness relative to comparators