Core Topics in General & Emergency Surgery: Companion to Specialist Surgical Practice (12 page)
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Authors: Simon Paterson-Brown MBBS MPhil MS FRCS
Whilst cost-effectiveness analysis and cost–utility analysis tell us whether a programme or intervention has better outcomes at additional costs or gains more QALYs, they cannot tell us whether the use of resources to achieve those outcomes is justified. Cost–benefit analysis is a type of evaluation that places a single value, usually in monetary terms, upon the benefits and outcomes from differing programmes of healthcare, i.e. it determines the absolute benefit of both quality and quantity, which is vital in resource allocation. In order to do this the health outcomes from treatment need to be measured in the same units as cost. This can be carried out as an extension to cost–utility analysis where the costs and benefits are converted to the same units. In the UK this is usually done with reference to the WTP threshold set by NICE. For example, if one were to consider a treatment that produces one additional QALY then at a WTP threshold of £20 000 this may be considered equivalent to a £20 000 benefit. If the cost of providing that treatment were £10 000 the treatment would result in a net benefit of £10 000. However, at a cost of £30 000 the net benefit would be − £10 000, implying that there would be a net loss from providing the treatment (as, for example, if it were to displace a more cost-effective use of the available resources). An alternative way of presenting such analysis is in terms of net health benefit rather than economic benefit, so that the result is presented in terms of QALY rather than monetary terms (0.5 or − 0.5 QALY in the above example).
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The appropriate method of economic evaluation depends upon which choices need to be made and the context within which those choices need to be reached (for example, refer to
Table 2.4
). If outcomes are expected to be the same then the choice is quite straightforward: cost-minimisation analysis may be used. The limitations of cost-effectiveness with disease-specific outcomes should be borne in mind. Cost–utility analysis has increased in popularity in an attempt to standardise and allow comparisons across different conditions and healthcare programmes. Cost–benefit analysis may offer decision-makers an alternative way of viewing such analysis but is dependent upon a predetermined WTP threshold.
Table 2.4
An example of how to choose a type of economic evaluation based on the question
Evaluations will always be subject to elements of uncertainty, be it in terms of resource use, costs or effectiveness. Sensitivity analysis is essential in such circumstances as it allows us to assess how sensitive the study results are to variations in key parameters or assumptions that have been used in the analysis. This allows us to assess whether changes in key parameters will result in savings or costs.
It is possible to undertake sensitivity analysis using as few or as many variables as desired. Commonly, variables such as production variables or discount rates will be used, or if statistical analysis of the variables has been undertaken one can carry out sensitivity analysis around known confidence intervals. Although sensitivity analysis is advocated for evaluations, a review by Briggs and Sculpher
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found that only 39% of articles reviewed had taken at least an adequate account of uncertainty, while only 14% were judged to have provided a good account of uncertainty. In addition, 24% had failed to consider uncertainty at all. There are differing methods of sensitivity analysis, which are discussed below.
Simple sensitivity analysis, in which one or more parameters contained within the evaluation are varied across a plausible range, is widely practised. With one-way analysis, each uncertain component of the evaluation is varied individually in order to assess the separate impact that each component will have upon the results of the analysis. Multi-way sensitivity analysis involves varying two or more of the components of the evaluation at the same time and assessing the impact upon the results. It should be noted that multi-way sensitivity analysis becomes more difficult to interpret as progressively more variables are varied in the analysis.
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Threshold analysis involves the identification of the critical value of a parameter above or below which the conclusion of a study will change from one conclusion to another.
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Threshold analysis is of greatest use when a particular parameter in the evaluation is indeterminate, for example a new drug with a price that has not yet been determined. A major limitation of threshold analysis is that it deals only with uncertainty in continuous variables, meaning that it is normally only useful for addressing uncertainty in analyses with data inputs.
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In analysis of extremes, a base-case analysis is undertaken that incorporates the best estimates of the inputs and then further analyses consider extreme estimates of the relevant variables. For example, if two alternative treatment strategies are being compared, then both the high and low costs can be considered for both therapies and costs can be assessed for each of the options based upon combinations of these. Analysis of extremes can be particularly effective in situations where a base-case value is known together with a plausible range, but the actual distribution between the outer limits is unknown. However, a problem with this approach is that it does not consider how likely it is that the various scenarios will arise.
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A final approach to dealing with uncertainty is through the use of probabilistic sensitivity analysis (PSA). This method allows ranges and distributions to be assigned to variables about which we are uncertain, thus allowing for combinations of items that are more likely to take place. For example, it is unlikely that all of the pessimistic factors regarding costs will occur in the evaluation. Techniques such as Monte Carlo simulations allow for the random simultaneous selection of items at designated values and undertake analysis based upon hypothetical patient cohorts. This approach allows the proportion of patients to be estimated for whom one of the options under evaluation is preferred; generally, proportions approaching 100% suggest that the intervention is nearly always preferable under a range of conditions. PSA is generally considered to be the most rigorous form of sensitivity analysis and is gaining widespread use.
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Value of information analysis is a recent development that is an extension of PSA. The method uses the results of PSA to consider the effect of reducing the uncertainty. Whilst PSA can provide a measure of the uncertainty around a prediction of cost-effectiveness, expected value of perfect information (EVPI) gives a measure that also incorporates the importance of such uncertainty.
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Further developments of this may help to guide priorities for future research
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or help to design studies and estimate required sample size.
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Any formal method for determining the costs and benefits of different treatments that may be used to allocate resources is likely to raise complex ethical issues. In particular, certain methods may create apparent discrimination against certain groups, such as the elderly or disabled, due to reduced capacity to gain from a particular treatment. Such methods may also fail to take into account other issues that are seen by society as being important in allocating resources, such as preferences relating to the process of care and issues such as equity.
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It is important that such economic methods should not be used without considering these wider implications of the decisions which stem from such analyses.
Most economic evaluations in healthcare use the above-mentioned methods looking at monetary value for new treatment options. There are, however, a number of complex issues in economic evaluation that remain controversial. These include whether to use patient or societal preferences, weighting of QALY to consider severity of disease, carer benefits and the incorporation of a value for innovation. Over the last decade, multi-criteria decision analysis (MCDA) has been suggested as a way to incorporate these complex and often conflicting values in economic evaluation. In MCDA, ‘criteria’ refers to the value taken into consideration. The process involves consideration of multiple criteria, each of which is given a weight in coming to an ‘objective’ decision.
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Currently, NICE health technology appraisals predominantly use ICER provided by cost–utility analysis. This is considered, using informal methods for incorporating other issues that are not thought to be incorporated in the costs or QALY measures, often by adjusting the WTP threshold that is considered acceptable.
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Another major change in NICE economic evaluations evolved in appraisals for interventions involving ‘end of life’. As mentioned in earlier sections, NICE considers interventions to be cost-effective if the cost per QALY gained is less than £20 000–30 000. However, in 2009, NICE issued guidance wherein some ‘end-of-life’ interventions or therapeutics that cost more than £30 000 per QALY gained may be given consideration if the treatment is indicated for conditions with a life expectancy of less than 24 months and if there is sufficient evidence that the new intervention improves life expectance by at least 3 months compared to the available NHS treatment and if the treatment if licensed for small population groups.
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Whether making individual or policy decisions regarding healthcare provision, it is becoming increasingly important for clinicians to take into account evidence about both the effectiveness and the cost-effectiveness of the treatment options. This requires that they examine the available evidence with particular attention to the appropriateness of the outcome measures used and of any techniques for economic analysis. In particular, there is a need for both clinicians and researchers to focus upon outcomes that are relevant to patients and truly represent their views about the relative values of the health states and events that they may encounter. Outcome research and economic evaluation are relatively new areas of healthcare research but they are progressing rapidly. An understanding of the methods used is a prerequisite for an adequate interpretation of the conclusions drawn from such work.
Key points
The choice of outcome measure is important in assessing the results of surgical treatment and needs to be carefully considered.
The measure used should be clinically relevant and preferably have been validated by previous research.
Possible measures relevant to surgery include mortality, condition-specific measures, standard pain questionnaires and generic measures of health-related quality of life.
Quality-adjusted life-years are a commonly used measure of outcome and there are several different ways to produce the weights (utilities) that are required to calculate these.
The estimation of the cost of treatments should include a detailed analysis of the resources used and their valuation, and may require consideration of the timing of incurring various costs.
There are several different methods of economic evaluation, including cost-minimisation, cost-effectiveness, cost–utility and cost–benefit analysis.
The use of cost-effectiveness analysis may allow comparison of health benefits to be gained by expenditure on different treatments but is not without both technical and ethical problems in its application.
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