First of all, I would like to thank Almighty God, for giving me the capability to complete the internship successfully on time. I express my deepest thanks to my university supervisor Nahid Akhter Jahan, Professor & Md. Mahfuzur Rahman, Lecturer for taking part in useful decisions & giving necessary advice and guidance and also thank to Dr. Md Saidur Rahman, team leader Model Urban primary health care clinics project of UNICEF, arranging all facilities to make internship easier. I would also like to express my appreciation to my colleagues and the staff at Aalo Clinic, Ershadnagar for their warm welcome and assistance during my internship. Throughout the internship, Mst Salima Khatun, Clinic in Charge provided me with valuable insights and guidance that helped me to navigate my tasks and responsibilities.

1. Cost Effectiveness Analysis
Syed Abdul Hamid, PhD
Professor
Institute of Health Economics
University of Dhaka

2. Outline
• What is CEA?
• Incremental versus marginal cost
• Incremental analysis of costs and consequences
• Ranking in CEA
• The critical value of cost effectiveness ratio
2

3. What is CEA?
Cost B
Choice
Cost A Program A
Program B Consequence B
Consequence A
• Single
• Common
• Not equal
Different
effectiveness
Calculate
C/E
1. (C/E) of A
2. (C/E) of B
• If (C/E )of A < C/E of B then
select the Program A
• If (C/E )of B < C/E of A then select
the Program B

4. What is CEA?
• Analyses, in which costs are related to a
✓single
✓common effect
✓But that may differ in magnitude
between the alternative programmes, are usually referred to as cost-
effectiveness analyses (CEAs).
• CEA is used to assess the cost per unit of a common outcome
• The outcomes here are measured in natural units such as total fertility,
contraceptive prevalence, maternal mortality, etc.
• E.g. Sculpher and Buxton (1993) compared treatments for asthma in terms
of the cost per episode-free day.
https://www.ncbi.nlm.nih.gov/pubmed/10146873

5. Cost-effectiveness analysis (CEA)
In CEA the incremental cost of a program is compared to the
incremental health effects of the program and health outcomes are
measured in natural units such as:
• average blood pressure improved in mm Hg
• cases found (screening procedure)
• cases of disease averted
• lives saved
• life years gain
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6. When should we conduct CEA?
• Single outcome
• Similar outcome
• Some CEAs are conducted in jurisdictions where QALYs are not
recommended as the measure of benefit in economic studies.
✓An example is the study by Dorenkamp et al. (2013) on the cost-effectiveness
of paclitaxel-coated balloon angioplasty in patients with drug-eluting stent
restenosis, conducted from the perspective of the German Statutory
Insurance. This used ‘life-years gained’ as the denominator in the incremental
cost-effectiveness ratio.

7. When should we conduct CEA?
• CEA is of most use in situations where a decision-maker, operating with a
given budget, is considering a limited range of options within a given field.
✓For example, a person with the responsibility for managing a hypertension treatment
programme may consider blood pressure reduction to be a relevant outcome; a
person managing a cancer-screening programme may be interested in cases
detected.
• Limitation: because of the specific measures of effect used in evaluating a
given treatment or programme, it is difficult to assess the opportunity cost
(i.e. benefits forgone) in other programmes covered by the same budget.
✓This requires the use of a generic measure of benefit that is relevant to all the
interventions for which the decision-maker is responsible.

8. Average vs. Incremental Cost-
Outcome Ratios
• Average cost-outcome ratio summarizes the impact of the program
relative to its cost.
• The incremental cost-outcome ratio allows you to evaluate the effect
of choosing one alternative vs. another.
• The key question in deciding whether an intervention is cost-effective
or not is to identify: compared to what?
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9. Incremental CE Analysis
9
=
–
Inputs
Outputs
Outcomes
Inputs
Outputs
Outcomes
Inputs
Outputs
Outcomes
– =
Alternative Comparison Incremental

10. Which alternative is most cost-effective?
Alternative Cost
(000s)
Effective-ness
(000s)
Avg. CE
Ratio
A 100 10 10.00
B 198 14 14.14
C 310 16 19.37
D 423 19 22.26
E 535 20 26.75
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Note: Alternatives shown in order of increasing cost

11. Comparing Alternatives:
Incremental Analysis
Alternative
Cost
(000s)
Eff
(000s) Cost/Eff
A 100 10 10.00
B 98 4 24.50
C 112 2 56.00
D 113 3 37.66
E 115 1 115.00
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12. The Concept of Extended Dominance
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The notion of extended dominance appears
when the incremental cost-effectiveness ratio
for a given treatment alternative is higher than
that of the next. In this situation the former one
should be excluded from consideration as it is
dominated (Alternative C in the example).

13. Assumptions
• The treatments are perfectly divisible
• There are constant returns to scale
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14. Allocating a Fixed Budget
• In order to maximize outcomes for a given
budget,
• Order alternatives in terms of increasing
incremental cost-outcome ratios including do
nothing or status quo, if relevant.
• Implement alternative with the lowest
incremental ratio and then either a) add
independent options or b) replace mutually
exclusive options until budget is exhausted.
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15. Example
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• Suppose we need to compare three treatment programmes of three
different groups of 1000 patients each. The three programs are for life
threatening conditions: different types of cancer, end stage renal
disease, and myocardial infraction. The cost and life years saved for
the alternative treatment strategies under each program is presented
in the following tables. How should we decide on an efficient
allocation of resources among the three programs?

16. Treatment strategy I
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Alternative
programs
Cost per
patient
(‘000), C
Life years
gained per
patient, E
Cost-
effectiveness
ratio (C/E)
Incremental
cost
effectiveness
ratio ((∆C/∆E)
A 100 10 10 10
B 200 14 14 25
C 300 16 19 50
D 400 19 21 33
E 500 20 25 100

17. Treatment strategy II
17
Alternative
programs
Cost per
patient (‘000),
C
Life years
gained per
patient, E
Cost-
effectiveness
ratio (C/E)
Incremental
cost
effectiveness
ratio ((∆C/∆E)
F 200 12 17 17
G 400 16 25 50
H 550 18 31 75

18. Treatment strategy III
18
Alternative
programs
Cost per
patient (‘000),
C
Life years gained
per patient, E
Cost-
effectiveness
ratio (C/E)
Incremental cost
effectiveness
ratio ((∆C/∆E)
K 100 5 20 20
L 200 8 25 33
M 300 12 25 25

19. Extended dominance
• There are two cases of extended dominance – C and L
• If 1000 patients were given alternative C – this would cost 30,000 and 16,000 life
years would be gained
• If 500 patients were given alternative B and 500 patients alternative D – this
would also cost 300,000 and 16,500 life years would be gained
• C and L should be excluded from consideration as it is dominated
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20. Efficient allocation of resources
• Ranking: A, F, K, B, M, D, G, H, E
• Each budgetary limit defines a shadow price of life years gained.
• For example, budget allows us to implement up to treatment strategy G, the
implied shadow price would 50 per life year gained (not willing to pay more than
50 for a unit of effectiveness).
• Alternative approach is to decide what we are willing to pay for a unit of
effectiveness and then to see the budget it implies.
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21. Critical value of cost effectiveness ratio (λ)
• The ceiling ratio (λ), or decision rule, is an important component of CEA,
representing a decision maker's valuation of a unit of health gain.
• CE threshold is defined as the maximum value of money per health
outcome that a jurisdiction decides to pay for adopting a technology or
an intervention.
• The value of λ that is appropriate may be heavily contingent upon
epidemiological, medical, political, ethical, cultural, budgetary and other
factors, and therefore is likely to vary across time and space.
• In addition, λ is not a strict decision-making criterion, and trade-offs
between cost-effectiveness and other important decision-making
factors are usually relevant.
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22. Different approaches of defining λ
• In several analyses, $US150 per disability-adjusted life year (DALY) has been used
as a rough benchmark for λ.
• Recent studies have used some multiple of per capita gross national income
(GNI), stimulated by the approach of the Commission on Macroeconomics and
Health (CMH), or some multiple of gross domestic product (GDP), as applied by
WHO.
• However, it can be argued that people value life in dimensions that extend
beyond income.
• Willingness to pay (WTP) for health gain, and willingness to accept (WTA)
increased risk of death, are more holistic approaches to valuing health
improvements.
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23. League Table Approach
• The $US150 per DALY estimate derives from work by the World Bank in 1993 to
recommend a minimum care package (MCP) of services that should be provided
by LMICs, and this threshold was reiterated in 1996 in an effort to define research
priorities.
• These committees specified $US150 per DALY as ‘attractive’ cost-effectiveness
and $US25 per DALY as ‘highly attractive’ cost-effectiveness for low-income
countries
• $US500 and $US100 per DALY, respectively, was specified for middle-income
countries.
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24. Twice Per Capita Gross National Income Approach
• Garber and Phelps derive twice per capita GNI for λ, using a standard von Neumann-
Morgenstern utility framework to model returns to investment in the health sector
relative to those in other sectors. We argue that by defining a person's life according to
the monetary value they produce or receive for their contribution to society, a human
capital approach is implied.
• Drawbacks to using multiples of per capita GNI include equity, affordability and neglect
of the multidimensional nature of welfare. In terms of equity, using an estimate based on
GNI values life differently in real economic terms across countries with different
economic environments, and using a state-dependent ceiling ratio may reinforce wide
global inequities in health and wealth.
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25. Twice Per Capita Gross National Income Approach
(contd.)
• Defining λ according to economic activity of individuals is gaining recognition in
economic evaluations of LMIC healthcare.
• The Commission for Macroeconomics and Health applied per capita income
• WHO-CHOICE initiative applied GDP as their thresholds for ‘very cost-effective’,
and three times this level for ‘cost-effective’.
• A human capital approach was also applied in the communicable disease analysis
of the 2004 Copenhagen Consensus (GNI), and the priority-setting initiative
recently undertaken by the Mexican health system (GDP).
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26. Preference-Elicitation Approach
• “To value life as the individual herself would value it”
• Eliciting preferences can take two perspectives – WTP for incremental improvements in
health, or the amount of money people are WTA as compensation to agree to take life-
threatening risks.
• The WTA approach has been found empirically to produce estimates for λ that are much
higher.
• From a policymaker's perspective, bias in WTP is likely to be upwards in decisions about
whether to fund an intervention, and downwards if deciding how much to charge.
• Attention should be paid to ensuring that preference-elicitation estimates are derived from
the context in which prioritization decisions will be made (e.g. regional, national or sub-
national).
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27. Results of a recent systematic review (Nimdet et al.
2015)
• The systematic review summarized the relationship between WTP per QALY and
cost-effectiveness (CE) threshold based on World Health Organization (WHO)
recommendation.
• The ratio between WTP per QALY and GDP per capita varied widely from 0.05 to
5.40, depending on scenario outcomes (e.g., whether it extended/saved life or
improved quality of life), severity of hypothetical scenarios, duration of scenario,
and source of funding.
• The average ratio of WTP per QALY and GDP per capita for extending life or saving
life (2.03) was significantly higher than the average for improving quality of life
(0.59)
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28. Thank you
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