COST EFFECTIVENESS ANALYSIS
How to do a cost evaluation: general steps The main steps are: 1. Defining the economic question and the perspective of the study 2. Determining the treatments to be evaluated 3. Choosing the study design 4. Identifying, measuring and valuing the costs of the alternative treatments 5. Identifying, measuring and valuing the benefits of the alternative treatments 6. Adjusting costs and benefits for differential timing 7. Measuring the incremental costs and benefits 8. Putting the costs and benefits together and analyzing the results 9. Testing the sensitivity of the results
Outputs and outcomes in health care services: • An output has been defined as ‘a measurable product attributable to an input or combination of inputs’, where as • an outcome has been defined as ‘an end state which may or may not be the intended effect of specified inputs, outputs or processes
Identify relevant health consequences and flow on effects
• Health consequences • All patient-relevant consequences, including both positive and negative outcomes, must be considered.
• Clinical or surrogate outcomes such as reduced cholesterol or reduced blood pressure can be used
Types of Outputs and Outcomes Disease specific/ clinical effects
Specific outputs and outcomes resulting from health care interventions and services, e.g.↓ cholesterol levels, ↓pain levels, return to normal successfully treatment , ↑ identified risk patients
Mortality and survival
Changes in life expectancy result from interventions and service provision expressed as life-years saved and lives saved.
Utility effects
Instruments that generate ‘common currencies’ to enable the health status of patients to be compared across all health care interventions, eg healthy days and quality-adjusted life years (QALYs)
Economic effects
Resources released for other purposes as a result of interventions and services, translation of health benefits into monetary perspective
Types of outcome The outcomes that are used to measure the health effects of interventions can be classified into three types: 1-Patient-relevant outcome: Final outcomes are related directly to the length and quality of life. Examples include deaths prevented, life-years gained, and QALYs gained Outcomes that matter to the patient and their care givers 2-Important clinical outcomes : Outcomes defined on the basis of the disease being studied (eg survival in cancer). valid outcomes of importance to the health of the patient. They include disease-specific events such as stroke and myocardial infarction. 3-A surrogate outcome : “a laboratory measurement or a physical sign used as a substitute for a clinically meaningful endpoint that measures directly how a patient feels, functions, or survives.
Intermediate Vs Final Outcome Measures Final
= change in health (status) resulting the programme.
from
Intermediate = change in clinical indicator resulting from the programme. Need to establish causal link between intermediate and final outcome measure
Measuring outputs and outcomes • Disease-specific/clinical effects • Mortality and survival • Utility effects/health-related quality of life
Benefit Categories Intervention
Direct Benefits
Reduced health services resource use
Improved patient health status / utility
Indirect Benefits
Savings in productivity
Family and friends quality of life
Making decisions is difficult! • What do we need in order to be able to choose the correct option?
A decision making exercise Exercise A: • The Government says that it will earmark a sum for the prevention of two diseases (Disease A and Disease B) that are prevalent in PHC . • These diseases are sometimes fatal, but can be prevented by suitable procedures. • You are asked to advise on how to spend the money to maximise the number of premature deaths averted.
Exercise B: • The Government hints that the sum will be $1 million. You ask public health experts, who tell you that the number of premature deaths averted by spending $1 million would be: 49 for disease A
or
101 for disease B
What would you advise?
• The Government now tells you that, at the insistence of the funds, the sum will actually be $500,000. • Again you ask public health experts, who tell you that the number of premature deaths averted by spending $500,000 would be 39 for disease A
or
81 for disease B
• Government documents on this decision, including your advice, are leaked before a crucial by-election in your region. • The Government announces publicly that they will, after all, make $1 million available. • What would you now advise?
Deaths averted
Average Cost
A
B
Total
A
B
$1 m
49
101
101
$20,408
$9,901
$0.5 m
39
81
81
$12,821
$6,173
$1m
39
81
120
$12,821
$6,173
Disease A
Disease B
Deaths averted
Cost per death averted
Deaths averted
Cost per death averted
100 000
10
10 000
26
3 846
200 000
19
10 526
43
4 651
300 000
27
11 111
58
5 172
400 000
34
11 765
70
5 714
500 000
39
12 821
81
6 173
600 000
43
13 953
87
6 897
700 000
46
15 217
92
7 609
800 000
48
16 667
96
8 333
900 000
49
18 367
99
9 091
1 000 000
49
20 408
101
9 901
Total cost (ÂŁ)
Disease A
Disease B
Deaths averted
Marginal cost per death averted
Deaths averted
Marginal cost per death averted
100 000
10
10 000
26
3 846
200 000
19
11 111
43
5 882
300 000
27
12 500
58
6 667
400 000
34
14 286
70
8 333
500 000
39
20 000
81
9 091
600 000
43
25 000
87
16 667
700 000
46
33 333
92
20 000
800 000
48
50 000
96
25 000
900 000
49
100 000
99
33 333
1 000 000
49
ď‚Ľ
101
50 000
Total cost (ÂŁ)
Types of Models • Descriptive – describes
• Prescriptive – suggests
• Deterministic – certainty
• Stochastic – probability
Example deterministic, prescriptive model (suggest, probability) Become ill See a doctor
Do not see a doctor
Obtain a prescription Take medication Recover rapidly
Slow recovery
Example stochastic, prescriptive model (decision-tree) Rapid recovery (p)
Leaves
See doctor Decision node
1-(p) Slow recovery
Become ill
Rapid recovery (q) Branches
Do not see doctor Chance node
1-(q) Slow recovery
Analysis of decision-tree • Decision tree is averaged out to get the expected value (EV) for each strategy (from decision node) • EV is the sum of products of the estimates of probability of events and their outcomes (payoff) Heads
£100
P=0.5 EV = 0.5x100 + 0.5x0 = £50
P=0.5 Tails
£0
Markov Modelling • Used when disease progresses over time • Patients grouped into a finite number of (Markov) states
• Time progresses in equal increments (Markov cycles) • All events or progression are represented as transitions from one state to another with a certain probability – Transitions (probability of improvement or deterioration) calculated from epidemiological and/or clinical data
• Spending one cycle in a given state is associated with a certain cost and a defined outcome
Example of Markov model States (levels of disability) A
B
C
D
E
1
2
3
4
Cycles (years)
Important points about models • Structure – Type of model (eg Decision-tree or Markov) – Elements of model (eg nodes, branches, states)
• Sources of data – Probability – Values (cost and outcomes)
• Conduct of sensitivity analysis to assess impact of these on the final result
• So, Any modelling should be explicit , clear, and assumptions used in the construction of models and inputs to them should be tested in a sensitivity analysis
A Basic Economic Model • Health as a consumer durable good: Utility = U (X, Health) • X represents “other goods and services” • H is a stock -- every action will affect health • On its own or combined with other goods and services, the stock of H generates a flow of services that yield satisfaction=utility
The Total Utility Curve for Health Utility Total U3 U2
Utility
U1 U0
H0 H1
H2 H3
Health
A Basic Economic Model (cont.)
•Production of health:
H = g (Medical care, other stuff)
Health
Marginal Increase in Health
Total Product
Medical Care
Medical Care
A Basic Economic Model (cont.) • Medical care is not homogeneous and differs in: – Structural quality (e.g. facilities and labor) – Process quality (e.g. waiting time, case management) – Outcome quality (e.g. patient satisfaction, mortality)
• Therefore medical services are often difficult to quantify
A Basic Economic Model (cont.) Health=H(Profile, Medical Care, Lifestyle, Socioeconomic Status, Environment) • If an individual has a heart attack, then overall health decreases, regardless of the amount of medical care consumed – The total product curve for medical care shifts down
• As a person ages, both health and the marginal product of medical care are likely to fall – The total product curve shifts down and flattens out
A Shift in the Total Product Curve for medical Care Health
TP0
TP1
Medical Care
MEASURING HEALTH • Important for all health care managers today – Insurers and consumers are demanding costs AND quality
HEALTH OVER THE LIFE CYCLE HEALTH Appendicitis
Auto Crash Cancer (radiation therapy) Cancer complications
Hmin
TIME BIRTH
HEALTH OVER THE LIFE CYCLE • Individuals make choices about health (make tradeoffs) which maximize U over time • Relatively high value for the future • Low discount rate
• e.g. Low-fat diet and exercise to avoid heart disease
• Relatively low value for the future • High discount rate
• e.g. Smoking, excess drinking, drug abuse
Valuation • Resources should be valued according to their opportunity cost • In most markets price is a good reflection of opportunity cost but health care provision is rarely subject to market valuations • Use of prices predominates but should be justified, and alternative ‘shadow’ prices may need to be used
•
Economic assessments of value for money have two distinctive characteristics: Opportunity costs A focus on marginal analysis
•
Focussing on changes in costs (and benefits) at the margin gives important insights that can be obscured by average or total costs (and benefits)
In any economic evaluation the following eight actions must be considered: • A description of the decision context and the perspective from which the analysis will take place. • Specification of the question being addressed. • Description of the alternatives (the options) that will be considered. • Identification, measurement and valuation of the costs of each alternative. • Identification, measurement and valuation of the consequences of each alternative. • A technical step where costs and consequences are adjusted for differences in their timing (called discounting). • An extensive sensitivity analysis to assess the importance of uncertainties arising inter alia from missing information. • Interpretation of the results of the evaluation and proposal of recommendations
Forms of Economic Evaluation • There are five distinct forms that the economic evaluation can take. • These are: • Cost-minimization analysis(CMA) • Cost-effectiveness analysis(CEA) • Cost-consequence analysis • Cost-utility analysis (CUA) • Cost-benefit analysis (CBA)
The selection of the appropriate type of evaluation depends on the research question the condition of interest the availability of data on outcomes Analysts should justify the choice of outcome and type of evaluation chosen
1-Cost-minimisation analysis The cost-minimisation analysis is an economic study in which two or more therapeutic alternatives with the same effectiveness or efficacy are compared in terms of net costs in order to establish the cheapest alternative. The equivalence of the comparators in terms of efficacy must be presented transparently and comprehensibly
2- Cost-effectiveness analysis The effects of an intervention (and its comparators) are measured in identical units of outcome (e.g. mortality, myocardial infarctions, lung function, weight, bleeds, secondary infections, revisional surgeries). Alternative interventions are compared in terms of ‘cost per unit of effect’. The CEA is an economic study in which the costs are expressed in monetary units and the results in non-monetary units.
Non-monetary units may for example be: (1) years of life gained, (2) hospital days prevented, (3) clinical parameters (e.g. response or remission reduction in cholesterol, etc).
rates,
3- Cost-utility analysis When alternative interventions produce different levels of effect in terms of both quantity and quality of life (or different effects), the effects may be expressed in utilities. The cost-utility analysis follows the same principle as the costeffectiveness analysis.
Costs are assessed in monetary units and the benefit is measured as a non-monetary but utility-adjusted outcome, the quality adjusted life year (QALY). The concept combines life expectancy and quality of life. If quality of life is an important aspect of therapy, this form of analysis should be chosen.
4- Cost-benefit analysis The cost-benefit analysis assesses all effects, including health effects, in monetary units. The disadvantage of the cost-benefit analysis is that a monetary assessment of clinical results must be made even though methodologically this is difficult to perform. Because of these methodological difficulties, this method of analysis is not used. On the basis of these methods of analysis, supplementary questions can then be considered, such as the cost impact
5- Cost Consequence Analysis Given the numerous limitations of CUA and CBA, just present a table comparing the various outcomes & let the decision�maker weigh the options (Coast, BMJ, 2004)
Cost Consequence Analysis Pros • global perspective • Decision‐maker evaluates what is important • Avoids inadequate hypotheses • Cons • burden of analysis for hurried decision‐makers
How Can Health Be Measured? • Length of life – Mortality (numbers, rates, SMRs) – Life expectancy – Life years lost
• Quality of life – Numerous QoL measures (generic and specific) – SF-36, Nottingham Health Profile, Guttman Scale, Rotterdam Symptom Checklist, Hospital Anxiety and Depression scale etc….
Process of Benefit Assessment 1.
Identification:
•Mortality. •Quality of life.
2.
Measurement:
•Measure in natural physical units (eg. number of deaths averted).
3.
Valuation:
•Value benefits if appropriate ie. if performing CUA or CBA.
Issues in Assessing Benefits for CEA 1. Efficacy vs effectiveness vs efficiency 2. Intermediate versus final outcome 3. Sources of data for CEA
Efficacy Vs Effectiveness Vs Efficiency Efficacy
= measure of effect under ideal conditions.
Effectiveness= effect under ‘real life’ conditions. Efficacy does not imply effectiveness Efficiency
= relationship between costs & benefits. Effectiveness does not imply efficiency
The three-dimensional conceptual framework
The three-dimensional conceptual framework 1. Enables
the inter-sectoral reallocation of resources for health to
be:
• conceptualized • discussed 2. Possible applications: • a useful planning tool • a monitoring or auditing mechanism • prospective as well as retrospective 3. The local context may require: • adaptation • development 4. Preparing the ground for effective implementation 5. Application in an economy which is: • growing • declining
Health economics is not just about economic evaluation A. Meaning, measurement and valuation of health
B. Influences on health and the demand for health
C. Demand for healthcare F. Economic evaluation
E. Market equilibrium D. Supply of healthcare
G. Planning, budgeting, monitoring & regulation
H. Evaluation at the whole system level
Health economics is not just about economic evaluation
F. Economic evaluation
Generalization of Economic Evaluations • (2 x 2 table or the concept of the quadrant regarding cost &effectiveness) More cost less effective
More cost, more effective
Less cost, less effective
Less cost, more effective
1-Cost Minimization Analysis • What is the least costly way to get a given health outcome ? • Rare (because effectiveness, utility and safety of interventions must be identical)
Cost‐Minimization Analysis • A subset of cost analysis • Examples in TB diagnostics (mostly limited to laboratory settings): * Various microscopies – which instrument is the most cost minimizing one for large scale up in the National TB Programme? * Choosing between two types of Interferon Gamma Release Assays
Cost窶信inimization Analysis 窶｢ The cost-minimization analysis is an economic study in which two or more therapeutic alternatives with the same effectiveness or efficacy are compared in terms of net costs in order to establish the cheapest alternative. 窶｢ The equivalence of the comparators in terms of efficacy must be presented transparently and comprehensibly.
2- COST EFFECTIVENESS • Cost-effectiveness analysis (CEA) to evaluate the costs and health effects of specific interventions • is dominated by studies of prospective new interventions compared to current practice • Limitation : one indicator at a time in analysis
CEA: Use of effectiveness measures
USES OF COST-EFFECTIVENESS ANALYSIS
1- CEA of a wide range of interventions can be undertaken to inform a specific decisionmaker; This person faces a known set of resource constraints (hereafter called a budget), a set of options for use in the budget, and a series of other (ethical or political) constraints)
Steps of CEA 1. Define the programs
2. Apply decision rules
3. Compute net costs
4. Compute net
health Effect .
5. Perform CEA and ICEA
6. Perform sensitivity analysis
The cost effectiveness plane Difference in effect and cost of an option relative to its comparator IV
+ cost
Intervention less effective and more costly
I
- effect
+ effect Intervention more effective and less costly
III
- cost
II
Example of cost-effectiveness analysis (CEA) • Alternative dosage of lovastatin in secondary prevention of heart disease (Goldman et al 1991, JAMA 265: 1145-51) Ages 65-74 Daily dose
Cost ($bn)
Life years
20 mg.
3.615
348,272
Cost/Life year 10,400
40 mg.
7.051
477,204
14,800
Sources of Effectiveness Data
1. Clinical trials, eg RCT’s 2. Epidemiological studies, eg cohort studies 3. Synthesis methods, eg meta-analyses 4. Use of modelling
Cost-effective option for the guideline, taking into account: • the cost per unit of outcome (which should be consistent with the threshold cost per life-year saved of $30,000–$100,000) • the quality of the evidence of effectiveness of the health care option (if placed at the higher end of the range, evidence on costs and effectiveness needs to be ranked highly)
• other factors that increase the option’s attractiveness (important if the option is placed at the higher end of the range).
Example: Timeframe for analysis • Health care option: Screening for bowel cancer with annual faecal occult blood detection. • Timeframe for benefits: Improvement in 10-year survival. • Timeframe for costs: Should also be 10 years, including the costs of screening for 10 years: * the cost of confirming the cancer and *the costs of treating the cancer, including any relapse.
DETERMINING THE COST- EFFECTIVENESS OF OPTIONS Objective To decide on the preferred clinical practice, using both clinical effectiveness and economic evidence. Steps • Assess whether any options are dominant or dominated (X versus Y, B is dominate A) • Calculate incremental cost-effectiveness • Assess the quality of the evidence • Consider other factors • Make the decision
C. E. A. Intervention A (e.g. current practice)
Intervention B (e.g. new treatment)
Total costs A
Total effects A
Costs A Effects A
Total costs B
Total effects B
Costs B Effects B
Difference in costs: Costs B Costs A
ICER:
Difference in effects: Effects B - Effects A
Costs B - Costs A Effects B - Effects A
Example 1 Current practice Effects (average per patient)
25 lifeyears [Effect A]
New Difference medication [B-A] 25.5 lifeyears [Effect B]
+0.5
New medication more effective so implement new medication………….. but what about costs?
Example 2
Costs (average per patient)
Effects (average per patient)
Current practice
New medication
Difference [B-A]
£2000 [Cost A]
£4000 [Cost B]
+£2000
25 life-years 25.5 life-years [Effect B] [Effect A]
+0.5
ICER = £2,000/0.5= £4,000 per life-year
It costs an additional £4,000 to obtain 1 additional life year
Example 3
Costs (average per patient)
Effects (average per patient)
Current practice
New medication
£3000 [Cost A]
£2000 [Cost B]
25 life-years 25.5 life-years [Effect B] [Effect A]
New medication dominates
Differenc e [B-A] -£1000 +0.5
A dominated option Option
Cost $
Life-years resulting from the health care
A
10,000
5
B
40,000
4
C
120,000
8
Example : Identification of a dominant option • Problem: Diabetic nephropathy in type I diabetes. • Options: Captopril or blood pressure control without Captopril. • Results: The use of Captopril reduced the progression of nephropathy; the use of dialysis and the costs of treating the condition. • Conclusion: The use of Captopril dominates other blood pressure control in type I diabetes with overt nephropathy. • Source: Rodby et al (1996)
Marginal or Incremental or Average analysis? • An analysis of different doses of a cholesterol lowering drug shows that • 80mg per day gives a cost effectiveness of £25,000 per life year gained (LYG) • 40mg per day gives £15,000 per LYG • So it’s probably worth giving 80mg where possible as the extra LYG costs only £10,000?
Marginal cost effectiveness = what’s the extra cost to get the extra effectiveness?
i.e. Difference in costs Difference in effectiveness
Comparison of Interventions • Micro-analysis – comparison is no treatment or status quo treatment • Marginal analysis – comparisons are different intensities of the same intervention • Macro-analysis – Comprehensive “league table,” e.g. Disease Control Priorities Project – Vs as determined by rule of thumb, e.g. $100,000 rule – Vs as determined by economic analysis as function of wealth, distribution and preferences
Clinical practice guidelines among health service care options using the incremental cost-effectiveness ratio If the incremental cost-effectiveness ratio is expressed as cost per lifeyear gained, it is suggested that: • health care options that fall below the threshold of $30,000 per lifeyear gained are considered good value and are recommended • health care options that exceed a threshold of $100,000 per lifeyear are not recommended without strong justification • health care options that fall between $30,000 and $100,000 per lifeyear are given further consideration. What is the situation in developing countries????
It is important to recognise that there may be different conclusions for a health care option under different conditions. For example, the incremental effectiveness and/or cost may differ depending on *the group of individuals it is being applied to, *or according to varying institutional factors or settings. The groups of individuals may be split according to varying clinical indicators (such as age, sex, ethnicity, comorbidities). For example the use of warfarin might be more cost-effective in the over 65 age group than in the under 65 age group. The institutional factors or settings may be split according to urban/rural settings, size of the hospital or facility, or availability of technology or skilled workers. For each of these different groups it may be necessary to produce a separate statement about what the evidence points to in terms of whether the health care option is cost-effective.
Uncertainty When do we “observe� uncertainty in the Health Care Sector? Patients are uncertain about the type of illness. The only certainty is that they feel different from their norm.
Health Care providers may diverge in their prescribed care to the same individual, highlighting the possibility of uncertainty in the right care, both type and levels. There is also uncertainty about the effectiveness of new drugs/products, or type of care.
Uncertainty Sources of potential uncertainty: 1. Methodological changes arising from different approaches and methods employed 2. Potential variation in the estimates of the parameters used in the evaluation 3. Extrapolation from observed events over time or from intermediate to final health outcomes 4. Generalizability and transferability of results
Handling uncertainty • Sensitivity analysis – Systematically examining the influence of uncertainties in the variables and assumptions employed on the estimated results – E.g. change in a unit cost value of 10% lead to change in result of >10% (sensitive) or <10% (insensitive)?
• Further analysis might include – Alternative (sub)perspectives – Use of intermediate outcome measures – Subgroup analysis
Sensitivity analysis: Sensitivity analysis can play an important role in the judgment of the evidence on costs When sensitivity analysis is conducted on the study model or structure, the results can be labelled as either robust (insensitive to plausible changes in the assumptions/model) or not robust (sensitive to plausible changes in the assumptions/model). If multiple studies are available, the sensitivity analysis should include the important differences between them, where appropriate. If the results are robust to changing the model
-Process of sensitivity analysis 1. Identifying the (uncertain) variables – All variables in the analysis are potential candidates – Give reasons for exclusion rather than inclusion 2. Specifying the plausible range over which they should vary – Reviewing the literature – Consulting expert opinion – Using a specified confidence interval around the mean 3. Recalculating results based on combinations of the best guesses, most and least conservative, usually based on… – One-way analysis (each variable separately) – Multi-way analysis (number of variables together) – Extreme scenario analysis (all variables in extreme combinations) – Threshold analysis (amount of variance needed to achieve specified result)
4- Presentation and discussion of results • What do the decision makers want to know? – Is there a health gain? – Is there a cost difference? – What is the relationship between cost and outcome differences? – Is the cost justified by the benefit (CEA/CUA)? – Is there a net gain (CBA)? – Is this result robust or sensitive to parameters?
Results from a sensitivity analysis may be reported as the percentage change in costs consequences cost-effectiveness ratios compared to the base case
Importance of sensitivity analysis
Externalities â&#x20AC;˘ A good shows externalities when it generates third party effects outside the price system - positive: e.g. vaccination of my neighbors on my chances to get infected, etc. - negative: eg pollution, neighborâ&#x20AC;&#x2122;s loud music, etc. Competitive market only considers private costs and benefits, not social ones ! inefficiency: negative externalities ! overproduction; positive externalities ! underproduction
Decision-making • Use of tools in supporting decision-making • •
• • • •
• • • • • •
You can judge for yourself when economic tools can be helpful in your decision-making, although the production of economic information requires expert knowledge. The information is not an end in itself, and can be presented in more or less helpful ways. For example, in assessing economic evaluations the following ten-point check list would be useful. (i) Was a well defined question posed in answerable form? (ii) Was a comprehensive description of the competing alternatives given? (iii) Was effectiveness of the programme services established? (iv) Were all the important and relevant costs and consequences identified for each alternative? (v) Were costs and consequences measured accurately in appropriate physical units? (vi) Were costs and consequences valued credibly? (vii) Were costs and consequences adjusted for differential timing? (viii) Was an incremental analysis of costs and consequences of the alternatives performed? (ix) Was allowance made for uncertainty in the estimates of costs and consequences? (x) Did the presentation and discussion of study results include all issues of concern to users? Do not let the perfect become the enemy of the merely good.
CE Analysis Challenges â&#x20AC;˘ 1- Decision-makers have correctly noted that resource allocation decisions affecting the entire health sector â&#x20AC;˘ 2- Current CEA practice often fails to identify existing misallocation of resources by focusing on the evaluation of new technologies or strategies.
â&#x20AC;˘ 3- For all but the richest societies, the cost and time required to evaluate the large set of interventions needed to use CEA to identify opportunities to enhance allocative efficiency may be prohibitive.
Limitations Of CEA
CEA Is Not Implemented: Why?
CEA IS NOT IMPLEMENTED : • Limited ranges of programs. • Requirement of greater amount of data. • All factors for ranking not included. • Ethical issues. • Political factors. • Perspectives of study and decision making. • Equity not considered.
CE Analysis Challenges • 1- Decision-makers have correctly noted that resource allocation decisions affecting the entire health sector • 2- Current CEA practice often fails to identify existing misallocation of resources by focusing on the evaluation of new technologies or strategies. • 3- For all but the richest societies, the cost and time required to evaluate the large set of interventions needed to use CEA to identify opportunities to enhance allocative efficiency may be prohibitive. • 4- CEA does not consider societal benefits because the effects of interventions are valued in terms of health only.
To this end, CEA can be used • to inform decisions about incorporating new health interventions, health technologies, or treatments into existing health service delivery systems. • to support decisions to increase coverage of a service or to scale up projects from pilots to national programs. • CEA is often essential for advocacy and raising awareness prior to introducing a health intervention or technology that is new to a specific country setting. • CEA can provide useful information for increasing access to health care provision, and better targeting scarce resources to maximize the impact of health interventions.
Factors to be considered • quality of life as well as survival is improved • quality of life or functional status is a major factor • the condition is severe and preventable
• the condition leads to permanent effects in children and young people • the disease is rare and there are no other health care options • quality of life for family members is seriously affected
• the option prevents adverse flow-on effects into other sectors • there are equity implications
3- COST UTILITY ANALYSIS