Browse by author
Lookup NU author(s): Professor Laura Ternent
Full text for this publication is not currently held within this repository. Alternative links are provided below where available.
Background. Typical health state valuation exercises use tradeoff methods, such as the time tradeoff or the standard gamble, involving a series of iterated questions so that a value for each health state by each individual respondent is elicited. This iterative process is a source of potential biases, but this has not received much attention in the health state valuation literature. The issue has been researched widely in the contingent valuation (CV) literature, which elicits the monetary value of hypothetical outcomes. Methods. The lessons learned in the CV literature are revisited in the context of the design and administration of health state valuations. The article introduces the main known biases in the CV literature and then examines how each might affect conventional iterative health state valuations. Results. Of the 8 main types of biases, starting point bias, range bias, and incentive incompatibility bias are found to be potentially relevant. Furthermore, the magnitude and direction of the bases are unlikely to be uniform and depend on the range of the value (e. g., between 0 and 0.5). Limitation. This is an overview article, and the conclusions drawn need to be tested empirically. Conclusions. Health state valuation studies, like CV studies, are susceptible to a number of possible biases that affect the resulting values. Their magnitude and direction are unlikely to be uniform, and thus empirical studies are needed to diagnose the problem and, if necessary, to address it.
Author(s): Ternent L, Tsuchiya A
Publication type: Article
Publication status: Published
Journal: Medical Decision Making
Print publication date: 01/05/2013
Online publication date: 03/03/2013
ISSN (print): 0272-989X
ISSN (electronic): 1552-681X
Altmetrics provided by Altmetric