title: Are Quality-Adjusted Life Years a Good Proxy Measure of Individual Capabilities?
abstract: BACKGROUND
  There is a debate in the health economics literature concerning the most appropriate way of applying Amartya Sen's capability approach in economic evaluation studies. Some suggest that quality-adjusted life years (QALYs) alone are adequate while others argue that this approach is too narrow and that direct measures of capability wellbeing provide a more extensive application of Sen's paradigm.
  
  
  OBJECTIVE
  This paper empirically explores whether QALYs provide a good proxy for individual capabilities.
  
  
  METHODS
  Data is taken from a multinational cross-sectional survey of individuals with seven health conditions (asthma, arthritis, cancer, depression, diabetes, hearing loss, heart disease) and a healthy population. Each individual completed the ICECAP-A measure of capability wellbeing for adults and six health utility instruments that are used to generate QALYs, including EQ-5D and SF-6D. Primary analysis examines how well health utility instruments can explain variation in the ICECAP-A using ordinary least squares regression.
  
  
  RESULTS
  The findings show that all seven health conditions have a negative association on overall capability as measured by the ICECAP-A index. Inclusion of health utility instruments into separate regressions improves the predictive power of capability but on average, explains less than half of the variation in capability wellbeing. Individuals with arthritis appear to be less inhibited in terms of capability losses when accounting for health utility, yet those who have depression record significant reductions in capability relative to the healthy population even after accounting for the most commonly used health utility instruments.
  
  
  CONCLUSIONS
  The study therefore casts doubt on the ability of QALYs to act as a reliable proxy measure of individuals' capability.
authors.affiliation: Health Economics at Bristol (HEB), School of Social and Community Medicine, University of Bristol, Bristol, UK. paul.mitchell@bristol.ac.uk.|The National Institute for Health Research Collaboration for Leadership in Applied Health Research and Care West (NIHR CLAHRC West), University Hospitals Bristol NHS Foundation Trust, Bristol, UK. paul.mitchell@bristol.ac.uk.|UK Renal Registry, Southmead Hospital, Bristol, UK. paul.mitchell@bristol.ac.uk.
authors.forename: Paul Mark
authors.initials: PM
authors.lastname: Mitchell
authors.affiliation: Department of Global Health and Social Medicine, King's College London, London, UK.
authors.forename: Sridhar
authors.initials: S
authors.lastname: Venkatapuram
authors.affiliation: Centre for Health Economics, Monash University, Melbourne, VIC, Australia.
authors.forename: Jeff
authors.initials: J
authors.lastname: Richardson
authors.affiliation: Centre for Health Economics, Monash University, Melbourne, VIC, Australia.
authors.forename: Angelo
authors.initials: A
authors.lastname: Iezzi
authors.affiliation: Health Economics at Bristol (HEB), School of Social and Community Medicine, University of Bristol, Bristol, UK.|The National Institute for Health Research Collaboration for Leadership in Applied Health Research and Care West (NIHR CLAHRC West), University Hospitals Bristol NHS Foundation Trust, Bristol, UK.
authors.forename: Joanna
authors.initials: J
authors.lastname: Coast
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D003430:Cross-Sectional Studies; D005260:Female; D006304:Health Status; D006801:Humans; D016018:Least-Squares Analysis; D008297:Male; D008875:Middle Aged; D011788:Quality of Life; D019057:Quality-Adjusted Life Years; D011795:Surveys and Questionnaires; D055815:Young Adult