We argue that this large literature is limited in that it is focused largely on consumption smoothing rather than smoothing of health itself. However, a problem with insuring health itself is that human capital cannot be traded; a person diagnosed with an incurable cancer cannot be made whole through reallocation of someone else's health. This lack of tradability in human capital implies that pooling of health risks, through private or public insurance, is infeasible except in rare instances such as transplantations.
We argue that medical innovation can be interpreted as an insurance mechanism for a population's health. By enabling treatment of a harmful disease, it completes the previously incomplete market for risk-sharing in health by pooling the health care spending risk. Given the potentially large value of smoothing health itself rather than consumption, we argue that more explicit analysis is needed on the relative value of public programs stimulating medical innovation versus health care reforms largely aimed at enabling consumption-smoothing.
Philipsona, George Zanjanib. Development of the American Economy. Economic Fluctuations and Growth. International Finance and Macroeconomics. International Trade and Investment. However, given the broad scope of much public health guidance, it will not be possible to conduct original analyses for every intervention or question. The selection of interventions or questions for further economic analysis including modelling should be a joint decision between the health economist, the CPHE project team and the PHACs.
Selection should be based on systematic consideration of the potential value of carrying out an economic analysis across all interventions. Note that an economic analysis will be more useful if it is likely to influence a recommendation, and if the recommendation will have a significant health and financial impact. So the decision about whether or not to carry out an economic analysis depends on:. Because local government will after March be largely responsible for implementing public health programmes, NICE has broadened its approach to the appraisal of public health interventions.
Local government is responsible not only for the health of individuals and communities, but also for their overall welfare. It is also less centralised than the NHS. The tools of economic evaluation must reflect both of these aspects wider remit than health and greater local element. The main change to the approach to economic evaluation is to place more emphasis on cost—consequences analysis CCA and cost—benefit analysis CBA than has been the case in previous methods manuals.
Cost-effectiveness analysis and cost—utility analysis CUA will still be required routinely, for several reasons:. CUA provides a single yardstick or 'currency' for measuring the impact of interventions on health. This form of analysis should be maintained wherever health is the sole or predominant benefit or influence. CUA allows interventions in healthcare to be compared so that resources may be allocated more efficiently. It should continue to be possible to compare estimates of cost effectiveness in the new institutional environment mainly local government with previous estimates of similar interventions made for use in the NHS.
All NICE programmes should include the use of a common method of cost-effectiveness analysis that allows comparisons between programmes. In some circumstances, almost all benefits are health benefits. Nevertheless, CUA has its disadvantages. The main disadvantage is its narrowness. It measures only health benefits, and even then, does not include the benefits associated with working: a healthier person will often work longer and return-to-work sooner as a result of being healthier.
It is therefore most suitable when the main or only benefit is a health benefit. It is also narrow in that it accounts only for efficiency, and not equity. If there are not enough data to estimate QALYs gained, an alternative measure of cost effectiveness may be considered such as life years gained, cases averted or a more disease-specific outcome.
Costs of lost production and any costs borne by patients and carers that are not reimbursed by the public sector should be included if a sufficiently wide perspective is also adopted. A cost-effectiveness analysis could be modelled on a single well-conducted randomised controlled trial RCT , or it could use decision-analytic techniques to analyse probability, cost and health-outcome data from a variety of published sources.
There is often a trade-off between the range of new analyses that can be conducted for the development of a given piece of guidance and the complexity of each piece of analysis. Simple methods may be used if these provide the PHACs with sufficient information on which to base a decision.
For example, if an intervention is associated with better health outcomes and fewer adverse effects than its comparator and has a similar cost, then a simple decision tree may provide a sufficiently reliable estimate of cost effectiveness. In other situations a more complex approach, such as Markov modelling or discrete-event simulation, may be warranted. Costs and health outcomes are discounted at 1. Health-related quality of life is valued using choice-based elicitation methods, a representative sample of the general population and validated, generic health-state instruments.
There is unlikely to be time to collect original quality-of-life valuations, so data collected by alternative methods may be used, but this should be suitably justified. In some circumstances, cost utility and cost effectiveness will not be an appropriate measure. This will normally be decided before work is commissioned, and an alternative form of analysis such as CCA, CBA or cost minimisation will be specified.
Additionally, public health has aspects that are wider than health alone, and these are more readily recognised in a local government environment. This necessitates both making the method of analysis more inclusive, and a corresponding change in perspective. The 2 elements that have always been discussed by decision-making committees are efficiency usually measured in terms of cost per QALY and equity.
The committees, as appropriate, also discuss adverse events, people's satisfaction with the intervention, its delivery, its ease of access and other aspects that have not been covered by efficiency and equity. It can take many other items into account that local authorities are likely to find important, including the trade-off between long-term goals and a paucity of short-run funding, and spillover effects into other areas of local government responsibility.
The extent to which these effects are material for any particular analysis will depend on circumstances. Where none of them is material, then there need be no change from the previous practice of conducting only a CUA or cost—effectiveness analysis together with a CCA to include equity considerations. In many cases, however, this will not be sufficient, and a wider and more formal form of CCA should be used.
In addition, the perspective used in CCA will often be wider than that of a healthcare provider. This aspect will be covered in more detail in section 6. The outcomes are usually more difficult to interpret and to aggregate than the single CUA outcome. Different bodies will impose different rankings on the allocation of resources to the same set of projects evaluated in this way.
The method takes more time and resources to measure the range of outcomes than does CUA for its single outcome. If cost-benefit studies occur in economic evaluation literature included in the evidence, NICE has used these studies.
CBA is a common form of analysis in transport studies, capturing a wide range of health and non-health impacts such as congestion, time saving and CO 2 emissions. CBA converts all benefits and costs that can be readily quantified into monetary terms. It sums the costs and benefits separately to arrive at either a net monetary benefit or a ratio of benefits to costs and consequently it usually operates with a societal perspective 'perspective' is covered in more detail below.
There are advantages of using CBA, such as:. If it is society's interests we are interested in, then all costs and all benefits should be included. Omitting some costs or some benefits in a decision to recommend an intervention will not usually be the best decision for society, unless the omitted items are not material to the decision. CBA includes benefits to individuals, such as those of a person being employed compared with not being employed as the result of an intervention. Expressing costs and benefits in money terms avoids the difficulties of aggregating data that occur with cost—consequences analysis.
Some outcomes cannot readily be quantified. For example, equity and social cohesion cannot be quantified in a CBA. The inclusion of either of these concepts requires a CCA to be used. If decisions are being made about what a government department or local government should pay for, then only the costs and benefits of interest to that sector might be required.
For example, if the ratio of aggregate individual WTP to government WTP were 3 for a given intervention, then a benefit:cost ratio of at least 3, based on aggregate individual WTP, would be required before the government might be expected to fund it.
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Little work has been done on what value the ratio of aggregate individual WTP to government WTP should be in any particular intervention, or for an 'average' intervention, but decision-makers should be aware that it is likely to exceed unity. WTP, especially the aggregation of individual WTP, as distinct from the WTP of a government department or local government , is a measure of demand rather than of need, whereas in the NHS, healthcare is allocated according to need.
This may occasionally cause contradictions with NICE's equity objectives. CBA may sometimes have large data requirements over and above what would be required for a CCA, such as a survey to estimate WTP and appropriate estimates of all relevant costs. Traditionally, there have been measurement issues concerning how health and non-health impacts can be valued in terms of money. Despite this, a CBA is sometimes the most appropriate method of analysis for public health guidance. The standard perspective for the economic analysis of public health interventions is typically that of the public sector.
This allows the costs and benefits of more than 1 central government department or body, and local government, to be taken into account. In addition to the public sector perspective, the perspective of the department that administers the interventions should be used. For example, if local government is involved almost exclusively, or is the body administering the intervention, then a local government perspective should be used as well as the public sector perspective.
If the NHS is involved almost exclusively, or is the body administering the intervention, then an NHS perspective should be used as well as the public sector perspective. When appropriate, and in agreement with the CPHE project team, results may also be presented from other perspectives. For example, an employer's perspective would be taken to demonstrate the business case for a public health intervention on, say, workplace smoking. The transfer of many public health functions to local government means that a local government perspective is likely to be the most common for public health programmes.
The broadening of the perspective set for public health guidance reflects the wider remit of public health and the changes in the way that it will be delivered after March Table 6. All health effects on individuals. For local government guidance, non-health benefits may also be included.
Where appropriate, to be decided on a case-by-case basis in conjunction with the CPHE technical team. An annual rate of 1. An additional QALY has the same weight, regardless of the characteristics of the individuals who gain the health benefit. No standard method has been devised of apportioning costs and who should bear them when more than 1 government department or local government is involved in the delivery of an intervention.
The problem is greatest when 1 government department or local government reaps the benefits of an intervention but another department is required to implement it: for example, a school being asked to find time in its timetable to deliver a health intervention. No method is suggested in this guide for dealing with such problems.
There is currently some debate about the most appropriate rate of discounting future costs and benefits. Since public health interventions usually act over the long term, it has been decided to use a discount rate of 1. In practical terms, for many interventions in public health where the intervention occurs over a relatively short period earlier in people's lives but the benefits accrue mostly at the end of their lives, the use of this set of discount rates will give approximately the same result as a 3. In sensitivity analysis, an annual discount rate of 3.
The general approach to modelling to be taken must be agreed with the CPHE project team prior to implementation. Where available, consideration should be given to linking the model structure to the logic model used to develop the research questions. The logic model illustrates the causal pathways between human behaviour, the social, environmental and biological determinants of health and potential interventions and outcomes see chapter 2 and appendix A for details.
Sensitivity analysis should be used to explore the impact that potential sources of bias and uncertainty could have on model results. Deterministic sensitivity analysis should be used to explore key structural assumptions: testing whether and how the model results change under alternative, plausible scenarios. It should also be used to test any bias resulting from the data sources selected for key model parameters. Probabilistic sensitivity analysis should be used to explore the uncertainty arising from imprecision in model parameters.
Any uncertainty associated with all parameters can be simultaneously reflected in the results.
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In non-linear decision models, probabilistic methods also provide the best estimates of mean costs and outcomes. However, models incorporating probabilistic methods are more time-consuming to construct and may not always be a priority for health economists working on public health guidance.
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In such cases, deterministic sensitivity analysis should be used, and the decision not to use probabilistic methods should be justified in the guidance. The Guide to the methods of technology appraisal includes other useful advice for health economists developing economic models for use in public health guidance. Regardless of the modelling approach adopted, economic analysis should be based on the following principles:. The question being asked for the economic analysis should be clearly specified and appropriate and include comparison of all relevant alternatives for specified population groups.
There should be the highest level of transparency in the reporting of methods and results. Conventions on reporting economic studies should be followed see Drummond and Jefferson Potential sources of bias and uncertainty should be fully explored and reported using an appropriate sensitivity analysis and discussed with the PHACs. Where the average effect size at individual level is small, particular attention should be given to potential biases, especially publication bias. The limitations of the approach and methods used should be discussed with the PHACs and presented in the report.
Whenever a probabilistic sensitivity is carried out, a value of information VOI analysis should be undertaken to indicate whether further research is necessary, either before recommending an intervention or in conjunction with its recommendation. The review team and the CPHE project team should discuss whether or not any additional searches are needed.
Additional searches may be necessary if the effectiveness searches do not provide the information needed for economic modelling. For example, information on:. It is not necessary to conduct formal, systematic literature searches for all the types of information required for economic modelling although effectiveness data used in the modelling should be taken from the effectiveness reviews.
In addition, it might be better to obtain some information about epidemiology or public services from national statistics or databases, rather than from literature studies. Ideally, systematic literature reviews should be conducted for other model inputs, for instance to model the relative risk of coronary heart disease in relation to physical activity levels. However, this is time-consuming and the health economist should look at other options first. Possibilities include: searching the public health effectiveness evidence that was used to structure the key questions and perhaps other relevant questions in the scope; or liaising with the review team, the PHACs and other experts.
If an additional literature search is necessary, the review team should discuss and agree this with the information scientist and the CPHE project team. If longer-term follow-up data are required, a literature search to identify cohort studies may be appropriate. The report by Philips et al. Where appropriate, economic model s should be run to estimate the cost effectiveness of an intervention in different population subgroups. The subgroups of relevance will be agreed with CPHE project team. For an economic study or analysis to be useful, it must inform the public health guidance recommendations.