Alternativa regulatoria

1 Pharmacoeconomic analysis

Pharmaceoeconomics is a sub-discipline of health economics, which is used by payers to determine the optimal price for a medicine.³ The use of so-called health metrics is one of the major tools used in pharmacoeconomic analysis, as they are a means to measure the health impact provided by a particular medical intervention.

(a) Health metrics

Health metrics are used to estimate the health impact of medical therapies. There are various types of health metrics,⁴ however, the Quality-Adjusted Life Year is the preferred metric used by most payers in developed countries with public-healthcare systems to determine drug pricing and reimbursement decisions.

(i) Quality-Adjusted Life Years

Quality-Adjusted Life Years (QALYs) are a measure of health-related quality of life.

They are calculated by adding the life expectancy gained as a result of a medical intervention, and multiplying a health ‘utility’ value that accounts for severity of disease, where zero is equivalent to death and 1 is perfect health.⁵ In order to account for the inherent uncertainty of future events, a discount rate,⁶ is applied to any future                                                                                                                

3 A Prescription for Pharmacoeconomic Analysis (Pharmaceutical Management Agency, 2012) at 9.

4 S Whitehead and S Ali “Health outcomes in economic evaluation: the QALY and utilities” (2010) 96 British Medical Bulletin 5 at 18-19. Alternative health metrics to Quality-Adjusted Life Years [QALYs] include the Disability-adjusted-life year (DALY), the Healthy-years equivalent (HYE) and Willingness-to-pay (WTP). A discussion of the advantages and disadvantages of these alternative health metrics is outside the scope of this thesis.

5 L Prieto and JA Sacristán “Problems and solutions in calculating quality-adjusted life years (QALYs)” (2003) 1(80) Health Qual Life Outcomes 1 at 2.

6 For example, between three to five per cent per annum.

estimate of QALYs.⁷ For example, if a medical intervention is estimated to add three years of life at a health utility value of 0.2, then, the total health impact provided by that intervention will be 0.6 QALYs, minus the discount rate applied to the second and third year.

While it is easy to measure the length of time a patient survives, an estimate of health utility is difficult because it requires a subjective assessment of disease severity or quality of life.⁸ A benefit of using QALYs is that collecting data is not cognitively challenging, only requiring a few minutes to complete a questionnaire.⁹ However QALYs can be criticised, primarily because the assumption they can be added together is an oversimplication, and that they may discriminate against older and sicker patients that may benefit less from an intervention.¹⁰ Despite this, QALYs are a useful ‘universal’ health metric that allow a meaningful comparison between therapeutic interventions in different disease classes.

Theoretically, it is possible for payers to use QALYs to enforce a threshold above which they will be unlikely to subsidise a medicine.¹¹ For example, this could be $50,000 per QALY gained. This ensures that expenditure on a less cost-effective intervention does not displace expenditure on a more cost-effective intervention.

7 E Nord, N Daniels and M Kamlet “QALYs: some challenges” (2009) 12 Value Health S10 at S13.

8 The basic QALY standard, EQ-5D-5L, asks a patient to rate the severity of their disease state within five health domains (mobility, self-care, usual activities, pain/discomfort, and anxiety/depression) by selecting one of five levels of severity ((1) no problem, (2) slight problems (3) moderate problems, (4) severe problems (5) extreme problems or unable). This generates a combination of 3127 possible health states (5⁵ = 3125 plus unconscious and dead) which is used to provide an estimate of health utility from zero to 1. Another measurement used to estimate health utility is referred to as the Visual Analogue Scale (VAS). The patient is asked to rank their health from zero to 100 with zero representing worst imaginable health and 100 representing the best imaginable health. QALYs are used globally by researchers and many of the largest pharmaceutical companies to monitor outcomes in clinical trials, with the most popular measurement standard, EQ-5D, having been translated into most languages. See R Rabin and F de Charro “EQ-5D: a measure of health status from the EuroQol Group” (2001) 33 Ann Med 337.

9 A standard 5Q-5D-5L questionnaire is available from <www.euroqol.org>.

10 A detailed analysis of the criticisms of QALYs is beyond the scope of this thesis. However, some brief comments can be made. First, the presumption of ‘additivity’ for QALYs is an oversimplification, in that certain health states may be perceived as having more severity, the longer they are experienced:

see HJ Sutherland and others “Attitudes toward quality of survival—the concept of ‘maximal endurable time” (1982) 2 Med Decis Making 299 at 299; BJ O'Brien and others “Is there a kink in consumers' threshold value for cost-effectiveness in health care?” (2002) 11 Health Econ 175. Second, QALYs may be perceived as discriminating against interventions for older and sicklier people who would benefit less from interventions compared with younger and healthier persons: see PJ Neumann and MC Weinstein “Legislating against use of cost-effectiveness information” (2010) 363 N Engl J Med 1495 at 1496. Nevertheless, it is possible to use different ‘weightings’ to QALYs in order to make adjustments that reflect society’s values and can balance the interests of various stakeholders. For example, if society rates health changes in certain groups as more important than others, such as if a person starts life in poorer health or is a member of a vulnerable group, this can be reflected by an increased weighting to changes in those health states: see Nord, above n 7, at S13.

11See C McCabe, K Claxton and AJ Culyer “The NICE cost-effectiveness threshold: what it is and what that means” (2008) 26 Pharmacoeconomics 733.

Wealthier societies may apply an increased QALY threshold, which reflects a willingness to pay a higher price to add one year of healthy life. In practice, however, the application of QALY thresholds by payers is controversial and not officially endorsed by payers.¹²

(ii) Condition-specific metrics

The general applicability and relative simplicity of measuring QALYs means they can lack the specificity required to delineate incremental improvements in health, particularly for certain conditions.¹³ In that event, it may be more appropriate to use the condition-specific health metrics typically used to measure clinical trial outcomes which are submitted to the FDA or Medsafe in order to obtain regulatory approval.¹⁴ For example, these can include progression-free-survival or overall survival, which are used in clinical trials of cancer therapeutics,¹⁵ the Crohn’s Disease Activity Index used in clinical trials for Crohn’s disease,¹⁶ and biomarkers such as cholesterol levels used in clinical trials of cardiovascular disease.¹⁷ The use of condition-specific health metrics to determine rewards under a proposed optimal prize-based incentive mechanism will be discussed in Chapter Seven.

Summary

Health metrics are an important tool to compare efficacy of new medical therapies and determine the appropriate level of rewards for innovators. QALYs attempt to quantify abstract concepts like ‘health status’ and ‘quality of life’. The main benefits                                                                                                                

12 KL Rascati "The $64,000 question - What is a quality-adjusted life-year worth?" (2006) 28 Clinical therapeutics 1042 at 1042. Some commentators in the United States have argued that QALY thresholds could result in inefficiencies. It in particular, if the threshold is below the economic value of the health benefit to society, this can result in underinvestment in R&D, whereas if the threshold is too high, this may result in inefficient wastage of R&D spending: see JA Vernon, R Goldberg and J Golec

“Economic evaluation and cost-effectiveness thresholds: signals to firms and implications for R & D investment and innovation” (2009) 27 Pharmacoeconomics 797 at 797, 804.

13 Whitehead, above n 4, at 10.

14 Guidance for Industry Clinical Trial Endpoints for the Approval of Cancer Drugs and Biologics (Food and Drug Administration, May 2007) at 5. It should be noted that QALYs are also used globally by researchers and many of the largest pharmaceutical companies to monitor outcomes in clinical trials: Rabin and de Charro, above n 8, at 341.

15 Progression-free survival (PFS) is the length of time after treatment which a cancer tumor does not increase in size. This is correlated with the length of overall survival (OS). OS is more important but takes longer to measure than PFS: see Guidance for Industry Clinical Trial Endpoints for the Approval of Cancer Drugs and Biologics at 5, 8.

16 Crohn’s disease Activity Index is a composite of various clinical and non-clinical measurements which assign a score to rate the severity of a flare of Crohn’s disease, an autoimmune disorder. A score above 250 points is indicative of active disease while a score below 150 is indicative of remission.

17 Biomarkers are measured characteristics which are linked to the presence of disease. High cholesterol levels are useful biomarkers for predicting the risk of cardiovascular disease, therefore, a drug which lowers cholesterol would conceivably lower disease risk.

of QALYs are that they are administratively simple to measure and can be used as a

‘universal health metric’ to assess the efficacy of different therapies across various disease states. However, QALYs are a blunt tool for measuring incremental improvements, therefore other condition-specific health metrics may be used to measure incremental health impact, although these are less useful for comparing efficacy of a therapeutic intervention between different diseases.

(b) Pharmacoeconomic analysis

QALYs are a fundamental part of pharmacoeconomic analysis. For example, ‘Cost-Utility-Analysis’ (CUA) uses QALYs to determine the cost-effectiveness of medical interventions. In particular, CUA compares medical interventions by using an incremental cost-effectiveness ratio (ICER).¹⁸ ICER is calculated as the difference between the cost of two treatments divided by the difference between their effectiveness. This can compare an old and new medicine to determine whether the incremental health improvements provided by a new medicine falls within a particular cost per QALY threshold.¹⁹

Because regulatory approval in most countries is only based on demonstrating superiority to placebo, pricing and reimbursement decisions by payers based on ICER are an important market-based mechanism to incentivise drug companies to develop new drugs which are superior or cost-effective compared to existing medicines. As will be discussed below, this particularly reduces incentives to develop ‘me-too’

drugs, especially where the equivalent pioneer drug is close to becoming available as a generic.