Toward Improved Methods for Measurement of Utility: Automated Repair of Errors in Elicitations

Abstract

This study examines the effects of use of an automated computer protocol to correct a common error in utility elicitations--namely, scoring of a health state with a greater impairment as being more desirable than one with lesser impairment. The authors studied the protocol in a sample of 563 members of the Internet-using public. Results revealed that errors were common (17% of ratings) but were typically successfully repaired (individuals who made only 1 or 2 errors had a 75% chance of repairing them). The values of individuals who repaired errors were similar to those without apparent error. In contrast, individuals who refused to repair errors had lower scores for the best health state in the series and higher ones for the worst health state. Results suggest that the repair procedures were successful and that inclusion of utility scores from individuals who fail to repair illogically ordered ratings may bias estimates of mean utilities.