1. Health State Unable to perform some tasks at home and/or at work Able to perform all self care activities (eating, bathing, dressing) albeit with some difficulties Unable to participate in many types of leisure activities Often moderate to severe pain and/or other complaints

2. Exercise Rating scale (Q, 60y) ~ (FH, X) (Q, 60y) ~ ( (FH, 60y), p; Death )

3. Determination of QALY Weights Three Methods –Rating Scale –Time Trade-Off –Standard Gamble

4. Question Methods give systematically different results –SG > TTO > RS Which one is best?

5. Old Belief SG is best Based on EU EU is normative theory of decision under risk risk important in medical decision making

6. Problem People violate EU Inconsistencies in SG utilities

7. Llewellyn-Thomas et al. (1982) Two ways of determining U(X) –One-stage: X ~ (FH,p; Death) U(X) = p –Two-stage: X ~ (FH, q; Y) Y ~ (FH, r; Death) p = q + (1  q) r

8. Result Two-stage method gives systematically higher utilities than one-stage method Confirmed in Bleichrodt (2001) which used different experimental design

9. Dilemma Methods give different results Do not know which method is best

10. Attempt to Solve Dilemma Bleichrodt and Johannesson (1997) Idea: Utility model should explain choices Examine which method produces QALY weights that are most consistent with choices over health profiles.

11. Approach Valued BP by SG, TTO, and RS. Defined 7 health profiles 20 y. BP 18 y. FH 16 y. FH 14 y. FH 12 y. FH 8 y. FH + 8 y. BP 6 y. FH + 11 y. BP

12. Computed QALYs for each of 7 profiles based on SG, TTO, RS Led to ranking of profiles according to SG- QALYs, TTO-QALYs, and RS-QALYs Also asked subjects to rank profiles directly Compared ranking through Spearman rank- correlation coefficient

13. Results

14. Rank correlations

15. Conclusions TTO most consistent with individual preferences But why?

16. Rating Scale Easiest to use But, –No economic foundation (not choice based) –Response spreading (Bleichrodt and Johannesson (1997))

17. Hence Focus on SG and TTO Will explain why they differ and why TTO is “best”

18. Empirical Research SG > TTO Explanation based on EU: Difference due to utility curvature Concave utility for duration –risk aversion –time preference –decreasing marginal utility

19. Puzzling for EU SG consistent with EU TTO imposes restrictions But TTO more consistent with preferences

20. Will argue Common explanation is not complete because it is based on EU People violate EU Violations bias SG and TTO utilities Indication: results on consistency with

21. Reasons for violations Probability distortion Loss aversion Scale compatibility

22. Will show SG biased upwards TTO contains upward and downward biases This explains higher descriptive validity of TTO

23. Assumptions U(Q,T) = H(Q)G(T) –Common assumption in health utility measurement –Empirical support People prefer more years in full health to less

24. Standard Gamble (Q 1,T) ~ ((FH,T), p, Death) H(FH) = 1, U(Death) = 0 H(Q 1 )G(T) = pH(FH)G(T) + (1  p)U(Death) H(Q 1 ) = p

25. Time Trade-Off (Q 1,T 1 ) ~ (FH, T 2 ) G(T) = T H(Q 1 )T 1 = H(FH)T 2 H(Q 1 ) = T 2 / T 1

26. Utility Curvature If G is concave/convex then the TTO weights are biased downwards/upwards Empirical Research: –G is concave both under EU and under nonEU TTO biased downwards, SG unbiased

28. Probability distortion Empirical research: people do not evaluate probabilities linearly but weight probabilities Formal theory: Rank-dependent utility (RDU) –V((Q 1,T 1 ), p, (Q 2,T 2 )) = w(p) U(Q 1,T 1 ) + (1  w(p)) U(Q 2,T 2 ) –U = a + bU, a real, b > 0

29. Impact TTO riskless, hence no impact probability distortion SG: (Q 1,T) ~ ((FH,T), p, Death) H(FH) = 1, U(Death) = 0 H(Q 1 )G(T) = w(p) H(FH)G(T) + (1  w(p))U(Death) H(Q 1 ) = w(p)

30. Implication Suppose w(p) < p for all p Suppose (Q 1,T) ~ ((FH,T), 0.70, Death) Then H(Q 1 ) = w(0.70) < 0.70 But SG: H(Q 1 ) = 0.70

32. Empirical research w has inverse S-shape w(p) > p for p < 0.35, w(p) < p on [0.35, 1] p in SG generally exceeds 0.35 Hence, SG generally biased upwards

34. Loss Aversion Prospect Theory: people evaluate outcomes as gains and losses relative to a reference point People are loss averse: they are more sensitive to losses than to gains Much empirical evidence for loss aversion/status quo bias/endowment effects.

35. Loss Aversion Health Status Duration TT LA Q1Q1 FH T1T1

36. TTO (Q 1,T 1 ) ~ (FH,T) Gain in health status from Q 1 to FH weighted against loss in duration from T 1 to T. T will rise by loss aversion Hence T LA /T 1 > T/T 1 And thus TTO biased upwards by loss aversion

37. Standard Gamble (Q 1,T) ~ ((FH,T), p, Death) Individual trades-off possible gain from (Q 1,T) to (FH,T) against possible loss from (Q 1,T) to death p > p Loss Aversion induces upward bias in SG utilities

38. Scale Compatibility Attribute gets more weight if it is used as a response scale Formal theory: Tversky, Sattath & Slovic (1988) Empirical evidence: Tversky et al., Delquié (1993, 1997), Bleichrodt & Pinto (2002)

39. Scale Compatibility Health Status Duration TT SC Q1Q1 FH T1T1

40. TTO (Q 1,T 1 ) ~ (FH,T) Response scale is duration T SC > T Hence T SC /T 1 > T/T 1 And thus TTO biased upwards by scale compatibility

41. Standard Gamble (Q 1,T) ~ ((FH,T), p, Death) Scale compatibility predicts: overweighting of probability There are three probabilities in the SG –Probability p of good outcome (FH,T) –Probability 1  p of bad outcome Death –Probability 1 of (Q 1,T) Effect scale compatibility on SG utility ambiguous

42. Conclusion SG generally upward biased In TTO both upward and downward biases Hence, TTO utility lower and more consistent with individual preferences –Do not correct TTO for utility curvature –B&J: TTO most consistent when no discounting