The Role Of Economic Evaluation

Economic evaluation has been defined as "a comparative analysis of two or more alternatives in terms of their costs and consequences.''64 From this definition it can be seen that evaluation involves a comparison between alternatives, which may include "do nothing,'' while the evaluation includes both the direct costs (see above under Direct costs of pain management) and indirect costs (see above under Productivity and indirect costs associated with pain) incurred - depending upon the perspective employed - and the benefits derived from each of the alternatives. The process and techniques of economic evaluation are well documented and it is suggested that interested readers consult some of these

The nature and categorization of costs and benefits have already been highlighted, but in deciding which costs and benefits to include in the evaluation, it is the perspective employed in the evaluation that will determine this - a narrow health service perspective will not include patients' costs, productivity costs, and intangibles, whereas a societal perspective will include all costs, and wherever possible measured and valued. In reality, this would not be possible, but the decision-maker needs to be informed how the analysis has dealt with costs and benefits not specifically included in the calculations in determining cost effectiveness or cost benefit.

The valuation of costs and benefits also needs to reflect when costs are incurred and when benefits are realized. Individuals and societies are not indifferent to timing -preferring to delay costs as long as possible and to receive benefits as soon as possible. Therefore, costs and benefits which occur today are valued more highly than those which occur in the future, and the current value of any cost or benefit is lower the further in the future that it arises. In order to allow for this, future costs and benefits are subjected to discounting. The approach is quite simple using the formula:

where PV is the present value, K is the nominal value of the cost or benefit, r is the discount rate, and n is the number of years in the future the cost or benefit arises. If we expect to receive a benefit of £10,000 in five years' time, the present value, based on a discount rate of 5 percent, is equivalent to £7835.

In addition, when a new treatment or service is being considered it is unlikely that it will replace all existing and established therapies and services. Instead, some patients are switched, while others will remain on existing treatments and services. The issue therefore is what additional benefits are gained from the additional costs of the new therapy? This approach is termed "incremental analysis,'' where the difference in costs between the alternatives is divided by the difference in benefits. This provides a much more focused assessment of the impact of the new technology in context, rather than providing data relating to the total costs and benefits or the average cost and benefit generated by the new technology. The incremental cost-effectiveness ratio (ICER) (difference in costs divided by the difference in benefits) is used to address this issue.

efficiency, in that it enables judgments to be made about the relative value of pursuing one objective (e.g. full restoration of a person to employment) as opposed to another (e.g. ability to pursue some aspects of normal functioning). Cost-effectiveness analysis, on the other hand, can only provide an indication of technical efficiency, since it provides an assessment of different ways of fulfilling the same objective (for example, securing pain relief). However, cost-benefit analysis is reliant on being able to place monetary values on the identified costs and benefits. This is possible where, for example, people are willing to pay for a reduction in pain. Methods of arriving at indicators of willingness-to-pay can be arrived at by asking people directly through, for example, questionnaires. One such method is the contingent valuation approach, which asks people the maximum amount they would be prepared to pay for the benefit. An alternative to the questionnaire approach is to employ proxy values; for example, the price people would be prepared to pay for surgery in a private hospital would be an indicator of how much they were willing to pay to avoid having to join a waiting list. However, there are many issues relating to the translation of health outcomes into a monetary measure and thus cost-benefit analysis is not widely used when undertaking health economic evaluations.

Techniques of economic evaluation


Under the umbrella of economic evaluation there are five techniques available, depending on how the consequences of healthcare interventions and programmes are measured and valued and, as already stated, interested readers are invited to consult the array of available sources.


Cost-effectiveness analysis is used when outcomes are one-dimensional and measured in terms of health effect, such as reduction in pain score. When survival is the key measure of outcome, cost-effectiveness would assess the cost per life year gained from each of the alternatives with the lowest cost-effectiveness ratio indicating the best course of action. When the outcomes generated by the alternatives are equal, it is possible to use cost-minimization analysis, where the choice of the best alternative is made purely on the basis of cost. However, in order for cost-minimization analysis to be used, the equivalence of all outcomes from the alternatives must be unequivocal, which is rarely seen in practice.


Cost-benefit analysis enables the notion of efficiency to be viewed from a higher level, that of allocative

An alternative measure of value to that of a monetary approach is one of utility, where quality of life adjustments are made to a given state of outcomes, whilst simultaneously providing a common denominator for comparison of costs and outcomes in different healthcare programs. The common denominator, usually expressed as quality adjusted life years (QALYs) is arrived at by adjusting the duration of the outcome (e.g. life expectancy) by the utility value of the resulting health status. The basis of using utility effects is based on the notion that outcomes from treatments and other health-influencing activities have two basic components, quantity and quality of life. Life expectancy is a traditional measure with few problems of comparison. However, attempts to measure and value quality of life have a more recent history, with a number of approaches and instruments being utilized. Particular effort has gone into researching ways in which an overall health index might be constructed which would locate a specific health state on a continuum between 0 (worst possible health state) and 1 (perfect health). The QALY therefore takes one year of perfect-health life expectancy to be worth 1, but regards one year of less than perfect-health life expectancy as less than 1. QALYs are discussed and described elsewhere,20, 64, 65, 66 but the comparison between healthcare programs and interventions in terms of QALYs gained is depicted in Figure 6.1.

Additional years of life Figure 6.1 Quality adjusted life years gained.

Additional years of life Figure 6.1 Quality adjusted life years gained.


When outcomes are measured in terms of QALYs, the technique used is that of cost-utility analysis. The beauty of cost-utility analysis is that it enables comparisons to be made across different areas of health care - so that the cost per QALY of a pain management program can be compared with those designed to treat people in advanced stages of cancer. While they provide an indication of the benefits gained from a variety of medical procedures, in terms of quality of life and survival for patients, they are far from perfect as a measure of outcome. However, their use means that decisions are made explicitly and not based on political pressures and power or the quest for technological advancement. To restrict decision-making to doctors, or for that matter administrators, is to result in situations where most resources go to those who shout the loudest or to those who pluck the heartstrings the hardest. Widening the decision-making process is a move in the right direction and the utilization of QALYs (despite their limitations) is a means whereby the benefits generated by the healthcare system can be included in the process, thereby enabling better decisions to be made.


When the outcomes are multidimensional - for example, changes in pain scores, return to normal functioning, etc. - the technique employed is that of cost-consequences analysis, where the outcomes are quantified and related to the costs for each of the alternative courses of action. It is this approach which is beginning to find increasing support among health economists, as it does not restrict the outcomes generated from healthcare interventions and programs to a single measure, such as QALY. It is easier to understand and enables decision-makers (on behalf of society) to impute their own specific, local values to these costs and consequences, and incorporate other aspects in the portfolio of information with which to inform the decision-making process.67


It should always be borne in mind that economic evaluation is not an exact science and findings from such studies should be treated with caution. Uncertainty is a fact of life and no economic evaluation can do anything other than reach a conclusion on the basis of the best (most informed) assumptions possible. In undertaking economic evaluations there are four sources of potential uncertainty:

1. methodological 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.

It is important, therefore, to investigate how sensitive the findings of an evaluation are to changes in the assumptions used in the study and variations in the parameter estimates. Sensitivity analysis in such cases involves rerunning the analysis with the assumptions changed and asking "what if''-type questions. A number of approaches have been employed to estimate the effect of uncertainty, but it is not the intention to delve into these techniques here, and interested readers are invited to consult relevant

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