1 / 42

Evaluating QALY Weights: Understanding the Differences Between SG, TTO, and RS Methods

This publication explores the determination of Quality-Adjusted Life Years (QALY) weights using three methods: the Standard Gamble (SG), Time Trade-Off (TTO), and Rating Scale (RS). Each method produces different results, making it challenging to identify the best approach for medical decision-making. This research focuses on empirical evaluations and behavioral observations to ascertain which method aligns most accurately with individual health preferences. The findings suggest the TTO provides higher consistency with individual preferences compared to SG, influenced by utility curvature and potential biases.

kumiko
Download Presentation

Evaluating QALY Weights: Understanding the Differences Between SG, TTO, and RS Methods

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  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

  27. 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

  28. 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)

  29. 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

  30. 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

  31. 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.

  32. Loss Aversion Health Status FH Q1 Duration T1 T TLA

  33. 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

  34. 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

  35. 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)

  36. Scale Compatibility Health Status FH Q1 Duration T1 T TSC

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

  38. 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

  39. 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

More Related