Building a Bridge Over Troubled QALYs: Developing Consensus

1. Third Plenary Session ISPOR 14th Annual International Meeting Building a Bridge Over Troubled QALYs: Developing Consensus

2. Effectiveness in CEA: QALYS Life expectancy multiplied by health-related quality of life: Quality-adjusted life years

3. Calculating QALYS: If, HRQL= 0.7 And, A treatment gives 10 extra years of life (@ 0.7 per year) Then…. People receiving the treatment gain an average of 7 QALYs each

4. A QALY is a QALY is a QALY #People HRQL LE = QALYs Saves100 x 0.8 x 50 = 4000 Lives Improves10,000 x 0.1 x 4 = 4000 HRQL

5. The cost-effectiveness of one thing compared to another… Cost treatment 1 – Cost treatment 2 Effectiveness treatment 1 – Effectiveness treatment 2 = COST per QALY

6. For example… CostLife ExpectancyHRQLQALYS Group A$80,000 2 Years X .6 = 1.2 Group B $ 8,000 1 Year X .8 = 0.8 Cost-effectiveness: $80,000 - $8,000 = $72,000 =$180,000/QALY1.2 – 0.8 0.4

7. INTRODUCTION TO THIS SESSION The QALY is a widely used measure of health gain. Long-standing criticism of the theoretical basis, and practical application of, QALYs.

8. ISPOR ACTIVITIES IN THE FIELD OF QALYs Plenary session, 10th Annual International Meeting (Kahneman), May 2005. Issues panel, 11th Annual International Meeting (Fryback, Kahneman, McGuire), May 2006. Two-day invitational consensus development workshop, November 2007.

9. MOVING THE QALY FORWARD: BUILDING A PRAGMATIC ROAD (Philadelphia, 2007) Funding from AHRQ and NCI. 25 participants. Discussion of: - the basics of QALYs; - the main challenges surrounding QALYs; - retaining and enhancing QALYs; - the use of QALYs in decision-making; - towards a consensus on the QALY

10. Milton C. Weinstein PhD Harvard School of Public Health, Boston MA, USA George Torrance PhD McMaster University, Hamilton, ON, Canada Alistair McGuire PhD London School of Economics, London, UK Building a Bridge Over Troubled QALYs: Developing Consensus QALYs: The Basics

11. The “Conventional QALY” • Method for valuing health effectiveness in cost-effectiveness analysis for resource allocation decisions • Values health based on time spent in health states • Endorsed by US Panel and NICE for reference case

12. The “Conventional QALY” Does Not… • Represent individual patient preferences • Reflect equity, fairness, or political goals

13. Core Concept of Conventional QALYs • Grounded in decision science (based on expected utility theory) • Individuals move through health states over time. • Each health state has a “value” • Health = value-weighted time (QALYs)

14. The Value Scale • Perfect health = 1.0, dead = 0.0 • Interval scale properties • e.g., 0.2  0.4 = 0.6  0.8 • States worse than dead have negative value

15. What Is Value? • Value = preference (desirability) • Valued by whom? • individuals experiencing a health state or illness • individual who may or may not experience that health state in the future • individuals considering the health of a community • (Values are for health states, not for changes in health states)

16. How Are QALYs Constructed? • What is being valued? • Whom do we ask? • What do we ask? • How are health outcomes defined?

17. How Are QALYs Constructed? • What is being valued? • Whom do we ask? • How are health outcomes defined? • Conventional QALYs allow for different answers to these questions • The answer depends on the question being asked

18. What Is the Question? • Societal resource allocation: priority setting across proposed programs or interventions • Societal (programmatic) audit: evaluation of ongoing activities/programs • Personal clinical decisions or decisions about insurance coverage

19. What is Being Valued? • Personal clinical/insurance choice • desirability of health outcomes to the individual • ex ante perspective

20. What is Being Valued? • Societal/program audit • current health of affected population members, as valued by themselves • ex post perspective (i.e. patient preferences/experience utility)

21. What is Being Valued? • Societal resource allocation • individual health (aggregated) or community health • ex ante or ex post

22. Whom to Ask? • Personal clinical/insurance • the individual, +/- informed by patients/disabled people

23. Whom to Ask? • Societal/program audit • members of the affected population

24. Whom to Ask? • Societal/individual health (aggregated) or • Societal/community health • representative sample of population • including patients/disabled people • informed by patients/disabled people

25. Multi-Attribute Utility Instruments • HUI-2 • HUI-3 • SF-6D • QWB • EQ-5D • 15D • AQOL • patient  health state • community survey  value score • US Panel and NICE reference case method • different instruments give different results • value scores may be population-specific

26. How are the health outcomes defined? • Health states • valuation independent of duration or sequence

27. How might the health outcomes defined? Health states conventional QALY approach valuation independent of duration or sequence Health paths (profiles) theoretically superior practical problem: large number of paths Health changes can incorporate equity or fairness practical problem: large number of changes order of changes matters

28. Time Preference in Conventional QALYs • QALYs should be discounted at the same rate as costs (US Panel, NICE)

29. Erik Nord PhD Norwegian Institute of Public Health, Oslo, Norway Norman Daniels PhD Department of Population and International Health, Harvard School of Public Health, Boston, MA, USA Mark Kamlet PhD Heinz School of Public Policy and Management, Carnegie Mellon University, Pittsburgh, PA,USA Building a Bridge Over Troubled QALYs: Developing Consensus QALYs: Some Challenges

30. The Conventional QALY Defined as expressing the personal utility of health outcomes as judged ex ante, “on average,” by the general public, from behind a veil of ignorance, about future health, based on self interest.

31. Issues: (i) Substantial, empirical inter-method variation in ex ante assessment SG yields higher values than TTO and greater in turn than rating scale Which one is “right”? (ii) Empirical unwillingness to trade-off lifetime Means that less is invested in preventing the outcome “confined to a wheel chair” Use of “experience” utility disfavors prevention, use of ex-ante utility doesn’t capture adaptation/foregone opportunities

32. iii. Concerns for fairness No consideration for pretreatment health state At odds with ethical theory/public opinion that suggests that in setting priorities societies often emphasize how bad off individuals would be without intervention i.e. concern for “severity”

33. iii.Concerns for fairness Conventional QALY model implies that the value of an intervention is proportional to the beneficiary’s capacity to benefit At odds with theory/public opinion that it should not be held again people that they have conditions for which there are no complete cures or whose remaining lifetime is shorter Similarly, life years gained for those at full health valued more than life years gained for those at less than full health Conflicts with equal right to protection of life by all

34. iv. Subtraction doesn’t “add up” Standard QALYs measure differences in health states, not gains in health Ex ante preference elicitation on health states and subsequent subtraction of health state values from one another Decreases data requirements, i.e. the number of possible changes is much highter than the number of possible states Nonetheless, this is a proxy approach, yet to be validated in the health economics literature

35. Incorporating concerns for fairness Count as “1” all gained life years if good enough to be desired by affected persons Leads to inconsistencies with individual preferences Place less weight on the duration of health benefits in comparisons of programs for patients with different life expectancies Add explicit equity weights Overload the model? Different “priority classes” for QALYS with different ratio cut-offs Treat “prevention” differently than “treatment”

36. Joseph Lipscomb PhD Department of Health Policy and Management, Rollins School of Public Health, Emory University, Atlanta, GA, USA Dennis Fryback PhD University of York, York, UK Marthe Gold MD, MPH University of Wisconsin, Madison, WI, USA Dennis Revicki PhD City University of New York Medical School, New York, NY, USA Building a Bridge Over Troubled QALYs: Developing Consensus Retaining & Enhancing The QALY

37. Overview For analyses requiring a summary measure of health that integrates quantity of life and quality of life, QALY is arguably the gold standard. But should it truly be the coin of the realm? Substantive concerns have been raised Our conclusion (in preview): These conceptual and methods issues signal opportunities for making important incremental improvements in the QALY – rather than abandoning the construct.

38. QALY Concern #1: Debate continues, and cOnsensus awaits, on certain key Methods issues surrounding the “conventional QALY” (QALYconv) Conceptualization and construction of health states - Which domains? - Which health levels within each domain? Psychometric approaches for eliciting preferences Statistical strategies for deriving overall value weights for QALYconv

39. QALY Concern #2: QALYconv assumes away some important issues, ignores others For example…… Highly simple model structure: QALYconv linearly additive function of time in health states, with an exponential discounting factor to reflect time preference Distributional and other ethical issues not formally integrated into model Some suggest that the value component of QALY should be “experience-based” (from real-time perspective) rather than “ex ante”

40. QALY Concern #3: Collectively, these “sins of commission and omission” have interfered with adoption of QALYs for public and private decision making In fact, QALYconv plays important role in regulatory and purchasing decisions in many industrialized nations But push back with NICE Non-QALY approaches being taken in France/Germany Much less in U.S: Not (yet) by FDA Not (yet) by Center for Medicare & Medicaid Service Not (yet) by most private payers Recent studies suggest that resistance to CEA may be less than suggested particularly given serious cost issues within public programs and employers Should we abandon the QALY?

41. No! Instead, Retain and Enhance the QALY QALYconv has proved to be serviceable vehicle for quantifying joint mortality-morbidity impacts at individual and population level To abandon QALYconv now is to sever link to hundreds of published studies & multiple ongoing investigations – including many capitalizing on data now collected in national surveys, clinical trials, observational studies….. A more productive pathway: pursue program of research that takes QALYconv as starting point for “continuous QALY improvement” over time

42. Research Topic IHealth State Definition and Description Prominent “health measurement systems” (e.g., HUI2/3, EQ-5D, QWB, and also SF-36) are the major engines behind preference-based assessments, including CEAs and population surveillance Multiple applications now in national surveys of health (e.g.,MEPS, U.S.-Canada Joint Survey, Medicare HOS) But, basic issues about what exactly to measure remain active topics for investigation All major systems view health as multidimensional concept, but domains vary across systems Even for similar domains (e.g., Mobility/Ambulation) item content differs across systems

43. Health State Definition and DescriptionInresponse… Variations in domain structure allows selection of particular QALYconv deemed best for application at hand – but does not promote comparability across studies. Solutions? Work toward “consensus domain structure” as one aspect of community-based deliberative processes to identify and codify citizen perspectives on health measurement, or else Cross-walk QALY scores between measurement systems To appraise, and improve, item content (within a domain), apply well-defined psychometric methods Mixed qualitative-quantitative approaches to improve content and construct validity e.g. HUI2/3 and SF36v1/v2 Promising development: application of item response theory (irt) methods, e.g., Pickard et al. to study 3-Level vs. 5-Level EQ-5D

44. Research Topic IIValuation of Health States Across the major health measurement systems, derivation of the value component of QALYconv (the “Q part”) varies in important ways: Method for eliciting preferences - Standard gamble vs. time-tradeoff vs. visual analog scale - Assumed duration of health state (1 day, 1 year, 10 years) Deriving aggregate QALY score for a multidimensional health state - Multi-attribute utility modeling (HUI2/3) - Econometric modeling (EQ-5D, QWB, SF-6D) States worse than death - EQ-5D and HUI2/3 allow for them - QWB, SF-6D, HALex do not

45. Valuation of Health StatesIn response…. Cross-walk scores across measurement systems Predicting one set of QALY scores from another via regression modeling (e.g., an EQ-5D to SF-6D mapping) Hierarchical irt modeling (a la Fryback et al) to map (for example) from EQ-5D to irt-derived latent variable continuum to SF-6D or……. Initiate consensus process leading to “Reference Case” QALY, establishing baseline expectations about health state definition and valuation

46. Valuation of Health StatesIn further response… Additional issues raised about QALYconv No health state duration or sequencing effects incorporated Investigate preferences over multi-state health profiles, with states drawn from current measurement systems (e.g., from the EQ-5D) Value component of QALYconv based (typically) on community-derived health state preferences Instead, draw community preferences from those who’ve experienced the states of health (Nord proposes SAVE) Instead, of using ex ante community preferences, use experience-based valuations (Dolan and Kahneman) (The challenge is how to operationalize for efficient application to health program evaluation)

47. Research Topic IIIAddressing Distributional and Other Equity Considerations Fairness matters – but it is not a matter that can be settled by QALYconv In response…. Equity Weighting: Factor fairness directly into the preference weighting process (e.g., approaches advanced by Nord, by Wagstaff, and by Johannesson) Constrained Optimization Modeling: Maximizing QALY improvement, subject to meeting equity conditions (e.g., as illustrated by Stinnett and Paltiel and by Chen and Bush) Community-Based Deliberative Processes where the implications of cost-effectiveness decisions based on QALYconv can be examined for fidelity to public values (e.g. Citizen’s Councils)

48. In sum… Must one decide between “building a bridge over troubled QALYs” and “sailing off into the less-charted waters” of non-QALY approaches? False Choice! Instead, cross that bridge and boldly set sail to new lands, (BUT treat the conventional QALY as the point of departure for the development of new models in order to capitalize on what has been learned across many years. This will also allow us to maintain continuity/comparability in tracking of trends in population health and in CEAs.)

49. Paul Kind University of York, York, UK Jennifer Elston Lafata PhD Center for Health Services Research, Henry Ford Health System, Detroit, MI, USA Karl Matuszewski MS, PharmD Elsevier/Gold Standard, Tampa, FL, USA Dennis Raisch BSPharm, MS, PhD University of New Mexico, Albuquerque, MN, USA Building a Bridge Over Troubled QALYs: Developing Consensus Use of QALYs in Decision-making

50. Decision Makers!!! Who are they? Faceless bureaucrats? Company management? Health plan CEOs? Mysterious, nameless committees? Doctors & hospitals? Patients? All of the above?