Report on Guidelines for Health economic analyses of medicinal products

Transcription

1 Anita Alban Hans Keiding Jes Søgaard March 1998 Report on Guidelines for Health economic analyses of medicinal products In 1997, the Danish Ministry of Health set up a working group consisting of: Research Director Anita Alban Professor Hans Keiding Professor Jes Søgaard that were to propose a set of guidelines for health economic analyses of medicinal products. The working group has met to establish consistent points of view and it has also met with an expert monitoring group set up for the purpose and consisting of representatives from Danish ministries and the Danish pharmaceutical industry. The working group hereby presents the result in the form of suggested guidelines (appendix 1 to this report). Below is a brief account of general considerations on which the concrete formulated guidelines are based. 1. Introduction As the name indicates, a health economic analysis of a medicinal product aims to analyse the benefits for society as a whole from the use of the medicinal product concerned. The methodological base for such analyses is extensively described in economic literature both generally and with a particular focus on the pharmaceutical area. The most prevalent Danish work within this field is Alban, Pedersen, Gyldmark and Søgaard (1995) and internationally the most recent extensive work is a report by Gold, Russell, Siegel and Weinstein (1996). As the literature indicates, the area is currently undergoing a certain methodological development, which means that the base is not always clarified completely. In connection with the preparation of suggestions for guidelines, it means that the requirements for the outline and execution of analyses should have a theoretical explanation to the greatest extent possible. On the other hand, it is of course the purpose of guidelines to limit the methodological scope, so that results of different analyses can be compared to as great an extent as possible, and at the same time it should not be possible to affect the result of an analysis by selecting one method instead of others. Thereby, there is a certain conflict of the aims for setting up guidelines. It should be added to this that it is probably inappropriate to set up a homogeneous set of requirements for health economic or socioeconomic analyses, as medicinal products are very different, and so are their prices and economic consequences. The findings of the analyses are primarily supposed to be used in connection with decisions about reimbursement, and therefore the analyses have a concrete aim. However, it is probably not desirable to put too little emphasis on the purely socioeconomic aim (to the extent that there is a conflict between the aim of lower medicine expenses and better welfare in society, which is possible at least theoretically). In a number of cases, and perhaps even predominantly, it is natural that a health economic analysis is configured as a cost-effectiveness analysis, in which a single relevant outcome target is compared to the costs, usually in the form of differences from the best alternative medicinal product. However, it would be wrong to exclude in advance that the analysis may be configured as a cost-benefit analysis, in which

2 the outcome is included in monetary units, as this kind of analysis has a consistent theoretical base, whereas other analysis methods largely should be seen as acceptable adaptations of desired theory to what can actually be carried out. In keeping with the tradition within the area, the following is divided into three main sections dealing with costs, outcome, and design and analysis. This is followed by recommendations for future guidelines with the same division. 2. Costs Types of costs: In health economic literature, a distinction is made between direct costs what is used for the treatment or saved by changing the treatment indirect costs, which are the productivity gains or losses related to illness, and finally intangible costs, i.e. an expression of loss of wellbeing in connection with disease. Frequently, the part of the analysis that deals with costs, and especially indirect costs, centres on reduction of costs compared to other kinds of treatment. Direct costs: It is relatively uncomplicated to include these costs. When calculating both quantities and prices, it should be ensured that relevant information is used, both when it comes to the material cost consequences and the price basis. Hence, it is not possible to use foreign cost data, as it is difficult to compare the price basis and the actual resources used. Indirect costs: In general, it is desirable if the analyses shed light on the consequences related to indirect costs, but it should be indicated separately. Here, the interesting topics are loss of time and productivity loss due to illness. There is a significant disagreement in this area as regards method of calculation. The two most prevalent methods are the human capital method, which bases the calculation on actual earnings, and the friction cost method, which is based on what it would cost society to replace lost performance. This debate can hardly be regarded as completely settled. So far, it is recommended that the human capital method is used instead of the friction cost method, not least because there will hardly be satisfactory data available for the latter any time soon. In addition, the friction cost method does not yet have a theoretical base similar to that of the human capital method. Intangible costs: Great restraint is recommended regarding inclusion of such costs, as the valuation is frequently of a dubious nature. On the other hand, in some cases a reduction of such costs (e.g. periods of anxiety) is significant, and therefore it is reasonable to describe them. Thus, it is very problematic (e.g. in screening programmes) to ignore intangible costs as anxiety about the result of a test, and especially if there is a relatively large number of false-positive results (such as in a mammography screening). Discounting: The use of discounting in analyses is linked with development over time. A reduction of future costs and effects with a given determined discount factor signifies the inclusion of a weighing between future and current benefits and drawbacks. For example, if the market rate is used for the discounting, it corresponds to the weighing between two periods being made consistent with how future income is weighed on the capital market. Other discount factors reflect the same type of weighing, for instance in individuals or with society s decision-makers, and these decisions need not be consistent. It is probably not a good idea to establish a specific rate of discount in the guidelines, as it would quickly become outdated and thereby discredit the entire method. If required, a concrete determination of a discount rate should take place continuously at the Danish Ministry of Health. It is recommended that adequate sensitivity analyses are carried out in cases whose profile in terms of time makes it interesting.

3 The significance of discounting and the choice of a discount rate varies from project to project. It most likely has the greatest impact on prevention projects, but a number of medicinal products seem to be made for reducing the occurrence of deaths and handicaps (e.g blood clots in the brain or brain haemorrhages) in the long term. 3. Outcome targets Outcome of an intervention within health services is to be understood as a change of health status of the person or persons who have undergone the intervention (prevention, diagnosis, treatment, nursing care). Outcome may be measured in survival rate, increased life expectancy, improvement of health status, etc. Intermediate outcome targets are a change of a health status related variable which can be related to an intervention. For example, this can be surrogate end-points that do not directly reflect a dimension of health status but relate to it: blood pressure, cholesterol level; events/avoided events: heart attack, headache; survival indicators reflecting the probability or frequency of survival in a specified time interval; years of life referring to the number of years alive within a given time interval or until death; target for Quality of Life (QoL), variables or indexes quantifying a set of dimensions of health status. QoL profiles provide the values for a set of dimensions of health status. QoL provides a simple aggregated value. One of the arguments against the use of surrogate end-points is that they make limited if any sense. Rather, it may sometimes make sense to use changes of the incidence of events, e.g. attacks, as this is more consistent with clinical targets and may be assumed to be a significant parameter for the individual s utility function, and the utility will be greater if a given event is avoided. The problem of using events is that it can be difficult to estimate how many events that have been avoided within a limited time horizon, and in the course of a lifetime such events may only be postponed. The same argument can be used for survival, as this can only be a case of postponement (so it is a case of prolonging life expectancy rather than saving lives). Years of life entail fewer interpretation problems, and the same thing applies to expected years of life, defined as the change of the sum of cumulative survival probabilities from a given point of time to death. Many interventions within modern healthcare do not affect survival, but the way we survive. The QoL index or QoL profiles attempt to reflect this (e.g. SF36, the Nottingham Health Profile, the Sickness Impact Profile). However, the QoL does not have any economic basis. The reason for this is that these indexes or profiles typically contain several dimensions of health and that they are reduced to one score by means of an arbitrary weighting procedure, which is not based on utility theory and does not reflect the population s health state preferences. Moreover, neither disease specific or general QoL targets can be used in isolation as a meaningful expression for effect without a time dimension. The QoL can be used for monitoring effect on health status and for observing how different treatments affect different aspects of health status. Utility-based/preference-based outcome targets: Preference-based outcome targets are scores achieved by asking individuals about their health state preferences. QALY is used most frequently, but HYE is also used in a number of instances. QALY may involve medical experts, so that their preferences determine how the value of different states of health is to be weighted. However, it has been proven that large differences may exist between experts and patients health state preferences. QALY most often involves the patient group, the target group for the intervention or a segment of society, depending on the purpose of the study. Three methods can be used for estimating the value of health state preferences, i.e. a sensitivity scale (visual analogue scale), time preference and the standard-gamble method. The sensitivity scale is easy to use in practice and is easily understandable for the interviewee, but it has no theoretical foundation. The standard-gamble method is based on expected utility theory, but it is difficult to adapt it so that the

4 respondents can understand it. The time preference method is derived from the standard-gamble method, which is easy to transfer and understand for respondents and it provides reliable estimates. The QALY target can only be considered a valid cardinal utility target if the assumptions about additive utilities (the utility of one health status is independent of other possible health states either before or after) holds good. The alternative utility target HYE does not have this requirement, as it is based on health profiles, and the overall expression for health status for a given diseased is weighted to 1. HYE is defined as number of years in good health, which is estimated to be the same as a health profile over a lifetime. Thus, the time preference method can be used for deriving HYEs. However, HYE is only a valid expression of a cardinal utility target, as used in economic analyses, if the assumptions about risk neutrality over years of life in good health holds good. The argument in favour of this is that the less restrictive assumptions about HYE are not compensated for by practical difficulties in connection with use of the method. As with the other conditions discussed, it is important that the choices made are documented and that the analysis can be replicated by the user with other choices. Concretely, this means that the material on which the analysis is based must be available with distributions over time, so that the user can discount differently. Monetary outcome targets are based on a number of methods measuring the willingness to pay of a segment of the population. The willingness to pay is measured in Danish kroner and corresponds to the value the persons asked believe the offered outcome to have the direct method is known as CV (contingency valuation). Contrary to the non-monetary outcome target directed at cost effectiveness and cost utility, the willingness to pay is a benefit target in a cost-benefit analysis. The advantage of using willingness to pay as a preference target is that, in principle, the preferences measured go beyond state of health, e.g. emotional or ethical aspects. 4. Design, analysis and data The design of a study is the way in which data for costs and outcome targets has emerged. Analysis is all algebraic analyses of data and assumptions, including statistical analyses, multi-variable analyses, decision analyses, scenario analyses, simulations, inclusion of different kinds of insecurity and sensitivity analyses. The following criteria are generally used concerning design and analysis: internal validity, external validity and transparency. Internal validity covers two aspects. The first aspect is whether the concepts and variables chosen in the concrete analysis are properly defined for the purpose and precisely quantified and potentially valued, where precision comprises reliability in the form of reproducibility. The second aspect concerns durability of the results relative to purpose and problem. External validity comprises generalisation and potentially extrapolation of results from the framework of a given study (population, indications, dosage, time horizon, etc.) to everyday practice. Transparency deals with reporting of the results and it is a practical criteria, but an important one nonetheless. It is most important for complicated model analyses, in which model structure and connections are to be reported in a manner that allows others (i.e. authorities and independent experts) to understand what is going on. One single study can rarely allow for both high internal validity and high external validity. Often there is some sort of contradiction between the two. A health economic analysis may be considered as a number of partial analyses that are linked together: (1) Studies based on primary data and where causality between intervention and changes of costs and benefits/outcome is established with a high internal validity, but not necessarily with a high external validity. Controlled prospective studies are usually required to document safety and effect (Phase III),

5 and therefore it seems natural to make an equivalent requirement for documentation of economic consequences on the short term and possibly in a narrower sense. (2) Model analyses in which data and findings from one or more of the above kinds of study is linked with epidemiological data (from ad hoc analyses or registers), clinical observation data and information on unit costs for conversion of use of resources for monetary costs and assumptions, where actual data is not available, typically for the long-term effects. Sensitivity analyses constitute an important element in this type of analysis. Many different model types exist and it is hardly possible to make a set of rules on which type to use. Results from such model analyses can rarely be transferred from other countries to Denmark. However, if such results were to be transferred, it would be necessary to demand documentation for consistency with epidemiological assumptions, clinical practice (for example in the case of adverse events) and unit cost in the analysis and in Denmark, which can probably only be done satisfactory in very few cases. Literature Alban, A., M. Gyldmark, A.V. Pedersen and J. Søgaard (1995), Sundhedsøkonomiske analyser af lægemidler (Health economic analyses of medicinal products), the Danish National Board of Health, the department for medicinal products. Gold, M.R., L.B. Russell, J.E. Siegel and M.C. Weinstein (1996), Cost-Effectiveness in Health and Medicine, Oxford University Press, Oxford.

6 Appendix 1 Guidelines for drawing up economic evaluations of medicinal products. 1. Purpose 1.1. The present guidelines provide directions for the design of economic evaluations of medicinal products (pharmaco-economic evaluations) submitted to the Danish Medicines Agency when applying for reimbursement Deviation from the guidelines is accepted if a well-founded reason exists. 2. General framework 2.1. The analysis should include all relevant costs and benefits from a socio-economic perspective The time horizon of the analysis should ensure that all relevant costs and benefits are identified For new medicinal products, the target patient population should be described and specified The results are to be reported at a disaggregated level that enables reproduction of the evaluation with alternative assumptions. 3. Design and data 3.1. Economic data originating from primary, preferably randomised, blinded clinical trials should be reported separately. Such data may be interpreted as direct documentation of resource consequences and clinical effects of a new therapy Additional studies of long-term consequences (defined relative to the time horizon of the study) can be based on different data sources. Examples of such data sources are analyses based on decision tree models and sensitivity analyses. Clinical and epidemiological data may be supplemented by ad hoc data on use of resources, which may be retrospective, although prospective designs are recommended Data should be included which indicates the impact on health care expenditure of introducing new therapies. 4. Costs 4.1. The evaluation must include all relevant costs, regardless whether they are direct, indirect or intangible. Use of resources must be reported separately from the valuation of costs. Indirect and intangible costs must be reported separately and they should only be valued to the extent it is deemed necessary. 5. Outcome measures 5.1. No single outcome measure exists which applies to all health economic evaluations. The outcome measure(s) selected should be consistent with the type and specific context or aim of the evaluation.

7 5.2. Acceptable outcome measures include gained life years or quality adjusted life years, but also response rate, number of successful treatments, measure of time without symptoms, pains etc. As yet, willingness to pay should only be used as an additional measure When the health outcome measure is Quality Adjusted Life Years (QALY), preference information is gathered by use of the time trade-off or the standard-gamble method. Utility estimates of health outcomes are based on societal preferences, i.e. a representative sample of the population rather than the target patient population of a given intervention 6. Discounting 6.1. Discounting should be carried out in evaluations where costs and benefits are distributed over a number of years. Discount rates must be determined in the individual evaluation, possibly supported by sensitivity analyses. 7. Sensitivity analysis 7.1. A sensitivity analysis should be carried out to evaluate the robustness of the conclusions to changes of assumptions, valuation, costs, outcome and discounting. 8. Conclusion 8.1. The evaluation should contain a summary, a conclusion and a discussion of the results, including limits for extrapolating the results to the future target population.