Statistical alchemy: conceptual validity and mapping to generate health state utility values

Abstract

Mapping between non-preference- and preference-based health-related quality-of-life instruments has become a common technique for estimating health state utility values for use in economic evaluations. Despite the increased use of mapped health state utility estimates in health technology assessment and economic evaluation, the methods for deriving them have not been fully justified. Recent guidelines aim to standardise reporting of the methods used to map between instruments but do not address fundamental concerns in the underlying conceptual model. Current mapping methods ignore the important conceptual issues that arise when extrapolating results from potentially unrelated measures. At the crux of the mapping problem is a question of validity; because one instrument can be used to predict the scores on another, does this mean that the same preference for health is being measured in actual and estimated health state utility values? We refer to this as conceptual validity. This paper aims to (1) explain the idea of conceptual validity in mapping and its implications; (2) consider the consequences of poor conceptual validity when mapping for decision making in the context of healthcare resource allocation; and (3) offer some preliminary suggestions for improving conceptual validity in mapping.