Using rank and discrete choice data to estimate health state utility values on the QALY scale

Abstract

Objective: Recent years has seen increasing interest in the use of ordinal methods to elicit health state utility values as an alternative to conventional methods such as standard gamble and time trade-off. However, in order to use these health state values in cost effectiveness analysis using cost per quality adjusted life year (QALY) analysis, these values must be anchored on the full health-dead scale. This study addresses this challenge and examines how rank and discrete choice experiment data can be used to elicit health state utility values anchored on the full health-dead scale and compares the results to time trade-off (TTO) results. Methods: Two valuation studies were conducted using identical methods for two health state classification systems: asthma and overactive bladder. Each valuation study involved interviews of 300 members of the general population using ranking and TTO plus a postal survey using discrete choice experiment sent to all consenting interviewees and a "cold" sample of the general population who were not interviewed. Results: Overall DCE produced different results to ranking and time trade-off, whereas ranking produced similar results to TTO in one study, but not the other. Conclusions: Ordinal methods offer a promising alternative to conventional cardinal methods of standard gamble and TTO. However, the results do not appear to be robust across different health state classification systems and potentially different medical conditions. There remains a large and important research agenda to address