Preference-Based Measures in Economic Evaluation in Health Care

Abstract

Estimating preferences for states of health has been an active area of research in recent years. Unlike psychophysical approaches, which discriminate levels of health status, preference-based approaches incorporate values or utilities for health outcomes and can be used in cost-effectiveness analyses to aid resource allocation decisions. This chapter considers issues and controversies involved in using preference-based measures in economic evaluation in health care, with a particular emphasis on cost-utility analysis and the estimation of quality-adjusted life years. Topics considered include techniques for measuring preferences, the use of preference-based classification systems, the relationship between patient and community preferences, methods for obtaining utilities from clinical trials, mapping health status from health utilities, the development of "off-the-shelf" preference weights, and proposed alternatives to quality-adjusted life years. We also consider applications of cost-utility analyses to public health interventions. Although cost-utility analyses have become more popular recently, many challenges remain for the field. Widespread acceptance of the methodology likely awaits more consensus on measurement techniques, as well as educational efforts in the public health and medical communities on the usefulness of the approach.

QLU-C10D: a health state classification system for a multi-attribute utility measure based on the EORTC QLQ-C30

“…Second, it is interpreted as a cardinal scale with two key anchor points: 1 is equivalent to full health (the maximum possible value) and 0 is equivalent to being dead (health states worse than death have negative values) [4]. Third, obtaining utilities requires stated preference-based assessment methods, or valuation tasks [9], i.e. standard gamble [10], time trade-off [11] or discrete choice experiments [12; 13].…”

Health impact and economic analysis of NGO-supported neurosurgery in Bolivia

“…Utilities are most commonly derived from population preference weights, and the enormous variability among nations and cultures has already been described. 15 Furthermore, country-specific thresholds often differ significantly from societally determined willingness to pay. In the US, for example, willingness to pay often far exceeds the $50,000/QALY convention.…”

Decision analysis, economic evaluation, and newborn screening: challenges and opportunities

“…21 If health outcomes are measured using a preference-based measure, such as quality-adjusted life years, which integrate morbidity and mortality, then the analysis is considered to be a cost-utility analysis, a special case of cost-effectiveness analysis. [20][21][22] Quality-adjusted life years are calculated by multiplying the value for each health state, called a "health utility, " by the duration of the health state. 23 The "health utility" is scaled between 1.0, which represents perfect health, and 0.0, which represents a health state equivalent to being dead, although health states can be assigned a value less than zero, which represents a state of health considered as being "worse than dead. "…”

“…23 The "health utility" is scaled between 1.0, which represents perfect health, and 0.0, which represents a health state equivalent to being dead, although health states can be assigned a value less than zero, which represents a state of health considered as being "worse than dead. " 22 For newborn screening applications, cost-effectiveness is calculated by dividing the net costs by the net health benefits of newborn screening for a disorder, or set of screened disorders, as compared with clinical identification of the specified disorder(s), assuming that both the numerator and denominator are positive. If the health denominator is negative, the potential harms of the screening program outweigh projected health benefits and screening would be considered to be "dominated" by clinical identification, and no ratio is calculated.…”