Health State

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. TTO most consistent with individual preferences But why? Conclusions

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 • (Q1,T) ~ ((FH,T), p, Death) • H(FH) = 1, U(Death) = 0 • H(Q1)G(T) = pH(FH)G(T) + (1p)U(Death) • H(Q1) = p

25. Time Trade-Off • (Q1,T1) ~ (FH, T2) • G(T) = T • H(Q1)T1 = H(FH)T2 • H(Q1) = T2 / T1

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((Q1,T1), p, (Q2,T2)) = w(p) U(Q1,T1) + (1w(p)) U(Q2,T2) • U = a + bU, a real, b > 0

29. Impact • TTO riskless, hence no impact probability distortion • SG: (Q1,T) ~ ((FH,T), p, Death) • H(FH) = 1, U(Death) = 0 • H(Q1)G(T) = w(p) H(FH)G(T) + (1w(p))U(Death) • H(Q1) = w(p)

30. Implication • Suppose w(p) < p for all p • Suppose (Q1,T) ~ ((FH,T), 0.70, Death) • Then H(Q1) = w(0.70) < 0.70 • But SG: H(Q1) = 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 FH Q1 Duration T1 T TLA

36. TTO • (Q1,T1) ~ (FH,T) • Gain in health status from Q1 to FH weighted against loss in duration from T1 to T. • T will rise by loss aversion • Hence TLA/T1 > T/T1 • And thus TTO biased upwards by loss aversion

37. Standard Gamble • (Q1,T) ~ ((FH,T), p, Death) • Individual trades-off possible gain from (Q1,T) to (FH,T) against possible loss from (Q1,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 FH Q1 Duration T1 T TSC

40. TTO • (Q1,T1) ~ (FH,T) • Response scale is duration • TSC > T • Hence TSC/T1 > T/T1 • And thus TTO biased upwards by scale compatibility

41. Standard Gamble • (Q1,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 (Q1,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