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Medical Decision Making
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Article

Comparison of 5 Health-Related Quality-of-Life Indexes Using Item Response Theory Analysis

Dennis G. Fryback*, Mari Palta, Dasha Cherepanov, Daniel Bolt, and Jee-Seon Kim

* To whom correspondence should be addressed. E-mail: dfryback{at}wisc.edu.


   Abstract
Background. Five health-related quality-of-life (HRQoL) indexes—EQ-5D, HUI2, HUI3, QWB-SA, and SF-6D—are each used to assign community-based utility scores to health states, although these scores differ. Objective. The authors transform these indexes to a common scale to understand their interrelationships. Methods. Datawerefromthe National Health Measurement Study, a telephone survey of 3844 US adults. The 5 indexes were analyzed using item response theory analysis to estimate scores on an underlying construct of summary health, {theta}. Unidimensionality was evaluated using nonlinear principal components analysis. Index scores were plotted against the estimated scores on the common underlying construct. In addition, scores on the Health and Activities Limitation Index (HALex), the Centers for Disease Control and Prevention Healthy Days questions, and self-rated health on a 5-category scale ranging from excellent to poor were plotted. Results. SF-6D and QWB-SA are nearly linear across the range of {theta} but with a shallow slope; EQ-5D, HUI2, and HUI3 are linear with a steep slope from low {theta} (poor health) into midrange of {theta}, then approximately linear with a less steep slope for higher {theta} (health just below to well above average), although the inflection points differ by index. Conclusion. Simple linear functions may serve as crosswalks among these indexes only for lower health states, albeit with low precision. Ceiling effects make crosswalks among most of the indexes ill specified above a certain level of health. Although each index measures generic health on a utility scale, these indexes are not identical but are relatively simply, if imprecisely, related.

First published on October 20, 2009
Medical Decision Making 2009, doi:10.1177/0272989X09347016


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