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Correcting for discounting and loss aversion in composite time trade-off
Stefan A Lipman1, Arthur E Attema1, Matthijs M Versteegh2
1Erasmus Centre for Health Economics Rotterdam, Erasmus School of Health Policy & Management, Erasmus University Rotterdam, Rotterdam, Netherlands.
Health Economics
|April 27, 2022
Summary
Correcting time trade-off utilities with a new approach reduced upward bias. This method accounts for individual loss aversion and discounting, yielding more accurate health utility values.
Area of Science:
- Health Economics
- Decision Analysis
- Psychometrics
Background:
- Time trade-off (TTO) utility measures are prone to upward bias.
- This bias stems from assuming linear utility of life duration, ignoring individual discounting and loss aversion.
- Previous work established a corrective approach for TTO in student samples.
Purpose of the Study:
- To extend the corrective approach to composite time trade-off (cTTO) methodology.
- To enable correction of utilities for health states considered worse than dead.
- To assess the impact of correcting cTTO utilities for individual discounting and loss aversion in a general public sample.
Main Methods:
- A general public sample (n=150) completed digital interviews involving cTTO tasks for six health states.
- Participants also underwent measurements of loss aversion and discounting behavior.
- cTTO utilities were corrected using these individual measurements under various specifications.
Main Results:
- Prevalence of significant loss aversion and both positive and negative discounting was observed.
- Correcting cTTO utilities generally led to a reduction in their values.
- The direction of utility adjustments made by respondents aligned with the results of the corrective approach.
Conclusions:
- The corrective approach effectively reduces upward bias in cTTO utilities, even for health states worse than dead.
- Individual characteristics like loss aversion and discounting significantly influence health utility assessments.
- This refined methodology offers more accurate health utility values for economic evaluations and policy decisions.
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