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Asthma Detection Research Based on Voice Signal Processing and Machine Learning
Published on: July 22, 2025
Estimating a preference-based index for a 5-dimensional health state classification for asthma derived from the
Yaling Yang1, John E Brazier1, Aki Tsuchiya1
1Health Economics and Decision Science, School of Health and Related Research, University of Sheffield, Sheffield, United Kingdom.
Background:
This article presents a valuation study to estimate a preference-based index for a 5-dimensional health state classification for asthma (AQL-5D) derived from the Asthma Quality of Life Questionnaire (AQLQ).
Methods:
A sample of 307 members of the UK general population valued 99 asthma health states selected from the AQL-5D using the time tradeoff technique. Models were estimated to predict all possible 3125 health states defined by the AQL-5D, and the models were compared in terms of their ability to predict mean values for the 99 states.
Results:
Mean health state values ranged from 0.39 to 0.94 based on an average of 22 valuations per state. A main effects model estimated on mean health state values and adjusted for consistency had the best predictive ability (mean absolute error of 0.047 and only 9/98 states with errors >0.1) and the most logical consistency with levels of the AQL-5D. The low number of valuations per state may have resulted in unreliable estimates for the models. Preference-based condition specific measures are limited in their ability to make cross-disease comparisons.
Conclusion:
This is the first study to derive a condition-specific preference-based measure from an existing measure of health-related quality of life in asthma for use in economic evaluation.
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