George W. Torrance

BACKGROUND: The Health Utilities Index Mark 3 (HUI3) is a generic multiattribute preference-based measure of health status and health-related quality of life that is widely used as an outcome measure in clinical studies, in population health surveys, in the estimation of quality-adjusted life years, and in economic evaluations. HUI3 consists of eight attributes (or dimensions) of health status: vision, hearing, speech, ambulation, dexterity, emotion, cognition, and pain with 5 or 6 levels per attribute, varying from highly impaired to normal. OBJECTIVES: The objectives are to present a multiattribute utility function and eight single-attribute utility functions for the HUI3 system based on community preferences. STUDY DESIGN: Two preference surveys were conducted. One, the modeling survey, collected preference scores for the estimation of the utility functions. The other, the direct survey, provided independent scores to assess the predictive validity of the utility functions. MEASURES: Preference measures included value scores obtained on the Feeling Thermometer and standard gamble utility scores obtained using the Chance Board. RESPONDENTS: A random sample of the general population (> or =16 years of age) in Hamilton, Ontario, Canada. RESULTS: Estimates were obtained for eight single-attribute utility functions and an overall multiattribute utility function. The intraclass correlation coefficient between directly measured utility scores and scores generated by the multiattribute function for 73 health states was 0.88. CONCLUSIONS: The HUI3 scoring function has strong theoretical and empirical foundations. It performs well in predicting directly measured scores. The HUI3 system provides a practical way to obtain utility scores based on community preferences.

This is a review of the Health Utilities Index (HUI) multi-attribute health-status classification systems, and single- and multi-attribute utility scoring systems. HUI refers to both HUI Mark 2 (HUI2) and HUI Mark 3 (HUI3) instruments. The classification systems provide compact but comprehensive frameworks within which to describe health status. The multi-attribute utility functions provide all the information required to calculate single-summary scores of health-related quality of life (HRQL) for each health state defined by the classification systems. The use of HUI in clinical studies for a wide variety of conditions in a large number of countries is illustrated. HUI provides comprehensive, reliable, responsive and valid measures of health status and HRQL for subjects in clinical studies. Utility scores of overall HRQL for patients are also used in cost-utility and cost-effectiveness analyses. Population norm data are available from numerous large general population surveys. The widespread use of HUI facilitates the interpretation of results and permits comparisons of disease and treatment outcomes, and comparisons of long-term sequelae at the local, national and international levels.

Utilities and quality-adjusted life years (QALYs) are reviewed, with particular focus on their use in technology assessment. This article provides a broad overview and perspective on these two techniques and their interrelationship, with reference to other sources for details of implementation. The historical development, assumptions, strengths/weaknesses, and applications of each are summarized. Utilities are specifically designed for individual decision-making under uncertainty, but, with additional assumptions, utilities can be aggregated across individuals to provide a group utility function. QALYs are designed to aggregate in a single summary measure the total health improvement for a group of individuals, capturing improvements from impacts on both quantity of life and quality of life--with quality of life broadly defined. Utilities can be used as the quality-adjustment weights for QALYs; they are particularly appropriate for that purpose, and this combination provides a powerful and highly useful variation on cost-effectiveness analysis known as cost-utility analysis.