Health Care Manag Sci (2012) 15:103–107 DOI 10.1007/s10729-011-9186-3
Presenting Germany’s drug pricing rule as a cost-per-QALY rule Afschin Gandjour
Received: 26 June 2011 / Accepted: 2 November 2011 / Published online: 21 December 2011 # Springer Science+Business Media, LLC 2011
Abstract In Germany, the Institute for Quality and Efficiency in Health Care (IQWiG) makes recommendations for ceiling prices of drugs based on an evaluation of the relationship between costs and effectiveness. To set ceiling prices, IQWiG uses the following decision rule: the incremental cost-effectiveness ratio of a new drug compared with the next effective intervention should not be higher than that of the next effective intervention compared to its comparator. The purpose of this paper is to show that IQWiG’s decision rule can be presented as a cost-perQALY rule by using equity-weighted QALYs. This transformation shows where both rules share commonalities. Furthermore, it makes the underlying ethical implications of IQWiG’s decision rule transparent and open to debate. Keywords Drug pricing . Germany . QALYs . Equity
In Germany, the Institute for Quality and Efficiency in Health Care (Institut für Qualität und Wirtschaftlichkeit im Gesundheitswesen, IQWiG) makes recommendations for ceiling prices of drugs based on an evaluation of the relationship between costs and effectiveness [5, 15]. In particular (but not exclusively), IQWiG evaluates prescription drugs that were recently approved for use in the German health care system. If the price of a drug is above the ceiling price, patients need to pay the difference out-ofpocket. Note that IQWiG’s task of setting ceiling prices is different from that of other health technology assessment (HTA) agencies around the world which decide whether or A. Gandjour (*) Frankfurt School of Finance & Management, Frankfurt, Germany e-mail:
[email protected]
not to fund a drug (in case of no-funding patients pay the price completely out-of-pocket). The decision to fund a drug has been made already when IQWiG starts the evaluation. Comparators of the new drug do not need to be drugs, but can be any health intervention. To recommend ceiling prices, IQWiG uses a decision rule1 (henceforth called ‘proportional’ rule) which comes in 3 variants. In the base case, the incremental cost-effectiveness ratio (ICER) of a new drug compared with the next effective intervention should not be higher than that of the next effective intervention compared to its next effective intervention ([15], p. viii). That is, incremental costs (compared to the comparator’s comparator) should increase at most proportionally to incremental effects. Thus, if we place the various alternatives on a cost-effectiveness plane (Fig. 1), draw an ‘efficiency frontier’ along non-dominated alternatives (A and B in the figure), the threshold ICER and thus the ceiling price C″ is determined by an extension of the last segment of the efficiency frontier (from A to B). Stricter variations of the base-case rule (leading to lower ceiling prices) exist and derive threshold cost-effectiveness either from i) the ICER of the currently most effective intervention (B) compared to no intervention (henceforth called ‘no intervention’ rule and leading to C′) ([15], p. ix), or ii) the average ICER of all non-dominated alternatives ([15], p. ix). As IQWiG’s rule does not start from a fixed budget, each therapeutic area is assessed separately; this means that no direct comparisons between therapeutic areas are performed. IQWiG’s decision rule has received a lot of attention and criticism [16]. One major point of critique has been the
1 The term ‘decision rule’ is used in its usual sense, i.e., it does not preclude that other criteria may lead to a change in recommendation.
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A. Gandjour Incremental cost
a Incremental effect
C’
C
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B New drug
B Existing interventions Efficiency frontier
New drug
Existing interventions X
X
A
A
Incremental cost
No intervention
C’’ C’
B
New drug
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A
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Fig. 2 Absolute decision rule for setting ceiling prices. A, B, and X are cost and effect pairs of existing interventions and C is the cost and effect pair of the new drug. The slope of C vs B corresponds to the absolute cost-effectiveness threshold and is independent of the costeffectiveness of B vs no intervention or B vs A
b
Incremental cost
No intervention
Efficiency frontier
Incremental effect
Fig. 1 Decision rules for setting ceiling prices by the Institute for Quality and Efficiency in Health Care (IQWiG). A, B, and X are cost and effect pairs of existing interventions and C′ and C″ are cost and effect pairs of the new drug. a presents costs on the x- axis and effects on the y-axis as proposed by IQWiG [15]. b presents effects on the xaxis and costs on the y-axis in line with most international convention
absence of direct comparisons between therapeutic areas and IQWiG’s reluctance to use quality-adjusted life years (QALYs) for that purpose. While IQWiG does not exclude the use of QALYs ([15], p. 4), it is critical of their use particularly based on ethical grounds ([15], p. 4). As an alternative to IQWiG’s rule, some critics proposed an absolute cost-effectiveness threshold [16], henceforth called ‘absolute’ rule. According to this rule, incremental costs per unit increase in health need to be equal or less than a threshold such as €30,000 per QALY gained (Fig. 2). In the current debate IQWiG’s decision rule is often perceived to be fundamentally different from a cost-perQALY rule. This, however, may not be the case. For example, Brouwer and Rutten [4] argued that IQWiG’s approach and a cost-per-QALY rule have some common-
alities. Similar to IQWiG’s rule, a cost-per-QALY rule may set a different threshold ICER in each therapeutic area and similar to a cost-per-QALY rule, IQWiG’s rule may allow calculating costs per QALY gained in different therapeutic areas. The purpose of this paper is to build on this idea and formalize it. We show that IQWiG’s proportional rule can be presented as an absolute rule by use of equity-weighted QALYs. This transformation shows where both rules share commonalities. Furthermore, it makes the underlying ethical implications of IQWiG’s decision rule transparent and open to debate. Finally, this transformation offers the opportunity for IQWiG to use a cost-per-QALY rule without compromising its ethical values. This would support international attempts to harmonize economic evaluation methodologies [7, 14] and make them more comparable across jurisdictions.
1 Methodology As stated, IQWiG’s decision rule is a’proportional’ rule, i.e., the increase in incremental costs is proportional to the increase in incremental effects/health. For example, if incremental health increases by 5%, incremental costs should also increase by no more than 5%. Based on the ‘no intervention’ rule this means that the same absolute increase in health leads to a smaller relative increase when the next effective intervention is fairly effective already (compared to no intervention). Hence, IQWiG’s rule accounts for disease severity: an improvement in health for a less severe condition is valued less than a same size improvement for a severe health condition [12].
Presenting Germany’s drug pricing rule as a cost-per-QALY rule
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In addition, IQWiG’s rule implicitly accounts for past resource consumption in the numerator of the ICER [12]. As past resource consumption can be regarded as a measure of disease severity, disease severity is considered twice, both in the numerator and denominator of the ICER [12]. While disease severity is considered in relative terms in the denominator (in the ‘no intervention’ rule relative to the level of disease severity without intervention), it is considered in absolute terms in the numerator (approximated by past resource consumption by the new drug’s comparator B). The absolute level of disease severity can be considered as a scaling factor of the relative level and allows a comparison across diseases. To formalize a consideration of relative disease severity in IQWiG’s value function we use the concept of diminishing marginal utility of health. Based on a pretreatment level of health H=1, 2, 3,…, h the marginal value of an equivalent increase in health (by one unit) is thus 1/H. If we measure total gain in value from increasing health from level 1 to h we obtain, based on the proportional rule: ðh V ðhÞ ¼ 1
1 dH ¼ ln h H
ð1Þ
V(h) represents a value function which is concave and describes diminishing marginal value of health. In fact, the value function is logarithmic with respect to health. As V″(h)< 0, the value function incorporates risk aversion. Based on the Arrow-Pratt measures of risk aversion, relative risk aversion is constant, i.e., absolute risk aversion is decreasing in health. As stated, Eq. 1 accounts for disease severity only in relative terms. A consideration of the absolute level of disease severity requires relating the level of health of comparator B to a single reference point for all diseases (thus enabling a comparison across diseases). This is formalized in Eq. 2 with optimal health (hmax) as a reference point: ðh V ðhÞ ¼ ðhmax H Þ 1
1 dH ¼ hmax ln h h þ 1 H
ð2Þ
Furthermore, assuming that the health gain of a new drug (ΔH) is independent of the pre-treatment level of health, the increase in value associated with the new drug is determined as follows: ðh V ðh; $HÞ ¼ $H ðhmax H Þ 1
1 dH H
¼ $H ðhmax ln h h þ 1Þ
ð3Þ
That is, the health gain of the new drug serves as a constant scale parameter which does not influence the
shape of the value function. While Eqs. 1 and 2 refer to the marginal value of an increase in health by one unit, Eq. 3 considers the actual increase in health (ΔH). Note that the value of the health gain ΔH is not simply added to the value of the pre-treatment level of health because IQWiG’s decision rule is proportional and thus considers the relative health gain, i.e., the health gain is set in relation to the pretreatment level of health. Simply adding the value of the health gain to the value of the pre-treatment level of health would correspond to the ‘absolute’ rule mentioned in the introduction. The value of the new drug compared to its comparator B at a given pre-treatment level of health h is determined by taking the first derivative of the value function (Eq. 3): dV ðh; $HÞ ðhmax hÞ ¼ $H dh h
ð4Þ
The pre-treatment level of health h can be defined as a function of the difference in absolute risk of disease (AR) between no intervention and comparator B, i.e., h ¼ f ðARnointervention ARB Þ. Optimal health (hmax) is given when ARB =0. The health gain by the new drug ΔH is calculated as a function of the difference in AR between the new drug and comparator B, i.e., $H ¼ f ARB ARnewdrug . Substituting in Eq. 4 yields: dV ðh; $HÞ ARB 0 ¼w dh ARnointervention ARB ARB ARnewdrug
ð5Þ
where w is a weight translating disease-specific AR into health. This weight is introduced because AR itself is disease-specific and thus does not allow a comparison across therapeutic areas (in contrast to h). Equation 5 shows that there are three weights by which health effects (ARB−ARnewdrug) are weighted. The first weight, w, transforms risk or health effects into value as QALYs would do. The second weight, ARB, is a simple measure of absolute disease severity which weighs QALYs or an alternative measure of health outcome that transforms health into value. It is not captured by QALYs and reflects a societal preference for treatment of the severely sick. The third weight, 1=ðARnointervention ARB Þ, is a measure of past health improvement or relative disease severity: the larger the past health improvement, the smaller the relative disease severity. It determines the slope of the value function (or efficiency frontier, in IQWiG’s terminology): the smaller the weight, the smaller the relative disease severity and the smaller the change in value for a given increase in drug effects. That is, a smaller weight leads to a smaller increase in price. Alternatively, if we consider V(h) in Eq. 5 as a measure of willingness to pay, then willingness to pay is linearly
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related to QALYs (or an alternative measure of health outcome), absolute disease severity, and the inverse of past health improvement. Thus, absolute disease severity and the inverse of past health improvement become weighting factors of the baseline willingness to pay across all therapeutic areas. Therefore, application of the equity-weighted-QALY rule requires defining Germany’s baseline willingness to pay for a QALY across all therapeutic areas. To this end, one would either need to obtain an empirical estimate of the average costeffectiveness ratio of health innovations in the past or survey a representative sample of the population. Next, an equity weight would need to be defined for each therapeutic area. As an example, consider clopidogrel to prevent re-infarctions in patients with a history of myocardial infarction (the first costbenefit assessment commissioned by IQWiG). Comparators of clopidogrel are aspirin (B) and no intervention. Based on ARB =6.6% [17] and ARnointervention = 9.1% (based on the Antithrombotic Trialists’ Collaboration [1]) we obtain an equity weight of 2.6. That is, in the example of clopidogrel considering that past health improvement has been relatively small yields a relatively large equity weight. The equityadjusted willingness to pay thus also becomes large.
2 Discussion This paper shows how IQWiG’s rule can be presented as an absolute rule by use of equity-weighted health outcomes such as QALYs. This transformation makes the underlying ethical implications of IQWiG’s rule transparent and also shows differences and commonalities between IQWiG and international HTA agencies using the cost-per-QALY rule. It also offers an opportunity for IQWiG to use a cost-per-QALY rule based on equity-weighted QALYs, without compromising its ethical values. The transformation would not affect the recently suggested shortcut for determining drug prices by IQWiG [13]. An important finding of this paper is that IQWiG’s rule uses two severity weights in order to weigh QALYs or an alternative measure of health outcome that transforms health into value. The first is an absolute measure of disease severity (ARB) and the second is a relative measure of disease severity (1=ðARnointervention ARB Þ). This does not lead to double counting of disease severity, however. Whereas the absolute measure of disease severity serves as a scale parameter of the value function, the relative measure serves as a shape parameter. In the following we would like to discuss the validity of the two weights. A severity weight such as ARB in IQWiG’s value function has been proposed before [18, 19]. Yet, it is not clear whether the implied linear relationship between absolute disease severity and value also holds empirically. What is unique to IQWiG’s rule is, in fact, the third weight, which rules in a concern for past health improvement. It
A. Gandjour
means that new drugs in therapeutic areas with little available treatment opportunities and perhaps limited previous research activities have more value. Interestingly, but unintended by IQWiG, this is the type of incentive perhaps desirable for developing orphan drugs. The transformation of IQWiG’s rule in an absolute rule is based on the assumption that past resource consumption is a measure of disease severity. This is not an uncommon assumption in the health economic literature [3, 10]. One could counterargue that consideration of past resource consumption is ethically justified on its own; however, in line with Dworkin [11], access to resources should not depend on past resource consumption and be equal for everyone. An alternative interpretation of past resource consumption is that of lost opportunities open to an individual. That is, use of health care services could be considered as a measure of the impediment to pursuing one’s life plan and the ability to achieve. The value of a new drug would then be assumed proportional to the degree of impediment. IQWiG’s rule would thus be in line with ethical theories such as Norman Daniels’s theory of justice for health [8, 9] and Amartya Sen’s capability approach [20]. On the other hand, luck egalitarians such as Gerald Cohen [6] and Richard Arneson [2] would argue that only the resources over which individuals have had no control would need to be considered for drug pricing. For example, if individuals’ choices were responsible for 10% of past resource consumption in a certain therapeutic area, then the price of a new drug in that area would need to be lowered by 10%. In conclusion, IQWiG’s rule leaves some room for interpretation of its ethical constraints. Thus, IQWiG needs to state its ethical constraints more explicitly. If we interpret past resource consumption as a measure of disease severity, IQWiG’s proportional rule can be represented by an equityweighted-QALY rule. The distinct feature of IQWiG’s decision rule is then the inclusion of a parameter representing past health improvement. The transformation of IQWiG’s rule into a cost-per-QALY rule as shown in this paper offers an opportunity for IQWiG to actually use a cost-per-QALY rule without compromising its ethical values. The remaining question is then how to estimate baseline willingness to pay across all therapeutic areas, the two options being i) an estimate of the average costeffectiveness ratio of health innovations in the past and ii) a survey of a representative sample of the population.
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