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.

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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

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

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

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

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

Problem People violate EU Inconsistencies in SG utilities

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

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

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

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.

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

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

Results

Rank correlations

Conclusions TTO most consistent with individual preferences But why?

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

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

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

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

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

Reasons for violations Probability distortion Loss aversion Scale compatibility

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

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

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

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

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

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

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)

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

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

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.

Loss Aversion Health Status Duration TT LA Q1Q1 FH T1T1

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

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

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)

Scale Compatibility Health Status Duration TT SC Q1Q1 FH T1T1

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

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

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