Time preference, duration and health state valuations

Health Econ. 1995 Jul-Aug;4(4):289-99. doi: 10.1002/hec.4730040405.

Abstract

There is increasing interest in health status measurement and the relative weights that people attach to different states of health and illness. One important issue which has been raised is the effect that the time spent in a health state may have on the way that state is perceived. Previous studies have suggested that the worse a state is, the more intolerable it becomes as it lasts longer. However, for most of these studies, it is impossible to determine how much of what was observed is attributable to the time spent in the state and how much is attributable to when it was occurring. This paper reports on a pilot study designed to test the feasibility of using the Time Trade-Off (TTO) method to isolate the effect of pure time preference from the effect of duration per se. Interviews were conducted with 39 members of the general population who were asked to rate 5 health states for durations of one month, one year and ten years. In aggregate, rates of time preference were very close to zero which suggests that the implicit assumption of the TTO method that there is no discounting may be a valid one. However, that more respondents had negative (rather than positive) rates, casts some doubt on the axions of discounted utility theory. In addition, implied valuations for states lasting for short periods were often counter-intuitive which questions the feasibility of using the TTO method to measure preferences for temporary health states.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Cost-Benefit Analysis / economics
  • Feasibility Studies
  • Female
  • Health Priorities / economics
  • Health Services Research / economics
  • Health Services Research / methods*
  • Health Status Indicators*
  • Humans
  • Male
  • Matched-Pair Analysis
  • Middle Aged
  • Models, Econometric*
  • Pilot Projects
  • Quality-Adjusted Life Years*
  • Statistics, Nonparametric
  • Time Factors
  • United Kingdom