A Condition-Specific Preference-Based Instrument: The Asthma Quality of Life Utility Index (AQL-5D)
Posted: 12 Jun 2007
Background: The quality-adjusted life year (QALY) is typically used in economic evaluation among health care interventions, which relies on some generic preference-based measures of health, such as EQ-5D, HUI and SF-6D etc. However, it has been widely assumed that those generic preference-based measurements may not adequately cover important consequences for some specific medical conditions thus they may lack ability to test changes of health status over time or discriminate different severity groups of patients. A new classification system known as AQL-5D, has been derived from Asthma Quality of Life Questionnaire (AQLQ), based on Rasch analysis and other psychometric evidence. AQL-5D contains 5 attributes, each with 5 levels.
Objectives: The objective of the study is to obtain a preference-based algorithm for AQL-5D based on a valuation survey of the UK general population; then to compare psychometric property of AQL-5D with the EQ-5D in terms of discrimination and responsiveness.
Methods: Valuation: A valuation interview survey of members of the public in South Yorkshire was undertaken, using time trade-off technique. Each respondent was randomly allocated to one of 14 blocks, and valued 7 states each, so that a total of 98 states were valued. A random effect with no interactions was the main regression model, alongside alternative specifications and data transformations. Models were compared using a set of criteria and the best model was selected, which established the asthma-specific preference-based utility algorithm AQL-5D. Application: The AQL-5D was applied to two datasets which cover a wide range of asthma patients. One dataset contains two asthma measures AQLQ and the Newcastle Symptom Scores (NASS), and two generic measures (SF-36 and EQ-5D). This dataset was used to examine the discriminative ability of the AQLQ scores, EQ-5D indices, and AQL-5D indices by dividing patients into groups using the SF-36 generic health question and the NASS. Mean, standard deviation and effect sizes by patient groups were calculated for each instrument and compared. The second dataset contains AQLQ and mapped EQ-5D indices at baseline and 12 weeks follow-up. Effect sizes by AQLQ scores, AQL-5D indices and mapped EQ-5D indices were calculated to test responsiveness over time.
Results: Valuation: The sample consists of 308 respondents (40% response rate), with an average of 22 valuations per state. Mean health state valuations range from 0.39 to 0.94, and standard deviations ranging from 0.2 to 0.4, with a negative skew. A random effects model without a constant was the best model and used to build AQL-5D algorithm.
Application: In the first dataset, Standard deviations (SD) for AQL-5D values were consistently smaller than those for EQ-5D, and showed better discrimination ability between groups based on NASS. Performance of AQL-5D indices was comparable to AQLQ overall scores. In the second dataset, effect size of AQL-5D indices over time were slightly smaller (0.51) compared with AQLQ (0.61) and the mapped EQ-5D (0.5).
Conclusion: It is possible to estimate a preference-based scoring algorithm for condition-specific measures for use in economic evaluations. AQL-5D showed good discriminative and responsive ability.
Keywords: AQL-5D, condition-spedific, utility, health state valuation
JEL Classification: A12
Suggested Citation: Suggested Citation